U.S. patent application number 13/421049 was filed with the patent office on 2013-09-19 for systems and methods for measuring, analyzing, and providing feedback for movement in multidimensional space.
This patent application is currently assigned to The Board of Trustees of the Leland Stanford Junior University. The applicant listed for this patent is Thomas Andriacchi, Ariel Veronica Dowling, Julien Favre. Invention is credited to Thomas Andriacchi, Ariel Veronica Dowling, Julien Favre.
Application Number | 20130244211 13/421049 |
Document ID | / |
Family ID | 49157964 |
Filed Date | 2013-09-19 |
United States Patent
Application |
20130244211 |
Kind Code |
A1 |
Dowling; Ariel Veronica ; et
al. |
September 19, 2013 |
SYSTEMS AND METHODS FOR MEASURING, ANALYZING, AND PROVIDING
FEEDBACK FOR MOVEMENT IN MULTIDIMENSIONAL SPACE
Abstract
The present invention provides systems and methods that measure
and analyze a user's movement during a specific activity, then
provide immediate, focused feedback as to how the user can modify
the movement.
Inventors: |
Dowling; Ariel Veronica;
(Stanford, CA) ; Favre; Julien; (Stanford, CA)
; Andriacchi; Thomas; (Los Altos Hills, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Dowling; Ariel Veronica
Favre; Julien
Andriacchi; Thomas |
Stanford
Stanford
Los Altos Hills |
CA
CA
CA |
US
US
US |
|
|
Assignee: |
The Board of Trustees of the Leland
Stanford Junior University
Palo Alto
CA
|
Family ID: |
49157964 |
Appl. No.: |
13/421049 |
Filed: |
March 15, 2012 |
Current U.S.
Class: |
434/247 |
Current CPC
Class: |
G16H 20/30 20180101 |
Class at
Publication: |
434/247 |
International
Class: |
A63B 69/00 20060101
A63B069/00 |
Claims
1. A method for training a subject to avoid joint injuries,
comprising: gathering raw data from at least one sensor attached to
a subject, to an interface, or in the subject's environment where
the at least one sensor allows quantifying at least one parameter
associated with a movement known to correspond to a risk of joint
injury; transmitting the raw data to at least one processor;
evaluating the risk of injury by comparing the raw data or
processed raw data to a stored model; providing feedback to the
subject based on the evaluated risk of injury so the subject can
alter the movement and reduce the risk of joint injury; and storing
at least one of the raw data, the processed raw data, the evaluated
risk data and the feedback data.
2. The method of claim 1, wherein at least five sensors or more are
used.
3. The method of claim 2, wherein at least ten sensors or more are
used.
4. The method of claim 1, wherein the at least one sensor is a
gyroscope, an accelerometer, a magnetometer, an electrode, a
pressure sensor, a force sensor, a torque sensor, a force platform,
a speed sensor, a goniometer, a camera, or a thermometer.
5. The method of claim 1, wherein the movement is performed during
walking, jogging, running, jumping, throwing, swinging, kicking,
swimming, rowing, squatting, lifting, pushing, climbing, cutting,
blocking, skiing, snowboarding, punching, sitting, typing, cycling,
or dancing.
6. The method of claim 1, wherein the at least one parameter is
selected from joint kinematics, joint kinetics, body segment
posture, body segment kinematics, body segment kinetics.
7. The method of claim 6, wherein the at least one parameter is
selected from ankle flexion, eversion, rotation angle, angular
velocity, angular acceleration, force, moment, or power; knee
flexion, abduction, rotation angle, angular velocity, angular
acceleration, force, moment, or power; hip flexion, abduction,
rotation angle, angular velocity, angular acceleration, force,
moment, or power; spine flexion, lateral bending, rotation angle,
angular velocity, angular acceleration, force, moment, or power;
shoulder flexion, abduction, rotation angle, angular velocity,
angular acceleration, force, moment, or power; elbow flexion,
abduction, rotation angle, angular velocity, angular acceleration,
force, moment, or power; wrist flexion, abduction, rotation angle,
angular velocity, angular acceleration, force, moment, or power;
neck flexion, lateral bending, rotation angle, angular velocity,
angular acceleration, force, moment, or power; foot position,
velocity, acceleration, jerk, orientation, angular velocity,
angular acceleration, or angular jerk; shank position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; thigh position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; pelvis position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; trunk position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; upper arm position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; forearm position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; hand position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; or head position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk.
8. The method of claim 6, wherein the at least one parameter is
selected from force, pressure, or moment between the subject and an
interface or the environment.
9. The method of claim 6, wherein the at least one parameter is
selected from muscle activity.
10. The method of claim 1, wherein the feedback provided is
visual.
11. The method of claim 10, wherein the feedback provided is a
graph.
12. The method of claim 10, wherein the feedback provided is an
avatar.
13. The method of claim 10, wherein the feedback provided is three
dimensional.
14. The method of claim 1, wherein the feedback provided is
auditory.
15. The method of claim 1, wherein the feedback provided is tactile
or haptic.
16. The method of claim 1, wherein the joint injury is selected
from a joint injury to a knee, elbow, wrist, ankle, hip, shoulder,
or spine.
17. A body movement training system comprising: at least one sensor
configured to measure at least one parameter associated with a
movement known to correspond to risk of joint injury; transmitters
associated with the at least one sensor to transmit raw data
related to the at least one parameter to at least one processor; at
least one processor configured to receive the raw data from the
transmitters, process the raw data, compare the raw data or
processed raw data to a stored model, evaluate the risk of joint
injury based on the comparison of the raw data or processed raw
data to the stored model, and generate feedback data; a display or
interface device to provide immediate feedback to the subject based
on the feedback data so the subject can alter the movement and
reduce the risk of joint injury; and a storage medium to record the
raw data, the processed raw data, the evaluated risk data and the
feedback data.
18. The body movement training system of claim 17, wherein at least
five or more sensors are used.
19. The body movement training system of claim 18, wherein at least
ten or more sensors are used.
20. The body movement training system of claim 17, wherein the at
least one sensor is a gyroscope, an accelerometer, a magnetometer,
an electrode, a pressure sensor, a force sensor, a torque sensor, a
force platform, a speed sensor, a goniometer, a camera, or a
thermometer.
21. The body movement training system of claim 17, wherein the
movement measured is performed during walking, jogging, running,
jumping, throwing, swinging, kicking, swimming, rowing, squatting,
lifting, pushing, climbing, cutting, blocking, skiing,
snowboarding, punching, sitting, typing, cycling, or dancing.
22. The body movement training system of claim 17, wherein the at
least one parameter is selected from joint kinetics, joint
kinematics, body segment posture, body segment kinematics, body
segment kinetics.
23. The body movement training system of claim 22, wherein the at
least one parameter is selected from ankle flexion, eversion,
rotation angle, angular velocity, angular acceleration, force,
moment, or power; knee flexion, abduction, rotation angle, angular
velocity, angular acceleration, force, moment, or power; hip
flexion, abduction, rotation angle, angular velocity, angular
acceleration, force, moment, or power; spine flexion, lateral
bending, rotation angle, angular velocity, angular acceleration,
force, moment, or power; shoulder flexion, abduction, rotation
angle, angular velocity, angular acceleration, force, moment, or
power; elbow flexion, abduction, rotation angle, angular velocity,
angular acceleration, force, moment, or power; wrist flexion,
abduction, rotation angle, angular velocity, angular acceleration,
force, moment, or power; neck flexion, lateral bending, rotation
angle, angular velocity, angular acceleration, force, moment, or
power; foot position, velocity, acceleration, jerk, orientation,
angular velocity, angular acceleration, or angular jerk; shank
position, velocity, acceleration, jerk, orientation, angular
velocity, angular acceleration, or angular jerk; thigh position,
velocity, acceleration, jerk, orientation, angular velocity,
angular acceleration, or angular jerk; pelvis position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; trunk position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; upper arm position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; forearm position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; hand position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; or head position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk.
24. The body movement training system of claim 22, wherein the at
least one parameter is selected from force, pressure, or moment
between the subject and an interface or the environment.
25. The body movement training system of claim 22, wherein the at
least one parameter is selected from muscle activity.
26. The body movement training system of claim 17, wherein the
feedback provided is visual.
27. The body movement training system of claim 26, wherein the
feedback provided is a graph.
28. The body movement training system of claim 26, wherein the
feedback provided is an avatar.
29. The body movement training system of claim 26, wherein the
feedback provided is three dimensional.
30. The body movement training system of claim 17, wherein the
feedback provided is auditory.
31. The body movement training system of claim 17, wherein the
feedback provided is tactile or haptic.
32. The body movement training system of claim 17, wherein the
joint injury is selected from a joint injury to a knee, elbow,
wrist, ankle, hip, shoulder, or spine.
Description
FIELD OF THE INVENTION
[0001] This invention relates to systems and methods that measure,
analyze, and provide feedback for one or more users during specific
activities.
BACKGROUND OF THE INVENTION
[0002] In the following discussion, certain articles and methods
will be described for background and introductory purposes. Nothing
contained herein is to be construed as an "admission" of prior art.
Applicant expressly reserves the right to demonstrate, where
appropriate, that the articles and methods referenced herein do not
constitute prior art under the applicable statutory provisions.
[0003] In recent years, increasing numbers of people of all ages
have become active for all of the health benefits exercise has to
offer. However, for some people these health benefits come at a
price: joint injuries. The term joint injury, in the broadest
sense, refers to all kinds of injuries that affect a joint. In the
context of sports, some joint injuries are due to accidents; others
are due to poor training practices, improper technique, lack of
conditioning and the like. Even harmless repetitive movements
associated with sport practices can induce injuries over the time
if they are not performed correctly. These mechanisms of joint
injury also apply for certain physical activities, not primarily
associated with sports but associated with occupational tasks or
rehabilitation that require consistent repetitions of specific body
motions. Some examples of such specific body motions are walking;
running; jumping; moving laterally; swinging a baseball bat, golf
club or tennis racket; kicking a ball; lifting; and typing.
[0004] In the past decade, numerous systems have been proposed to
simplify the measurement of human movement and to monitor users in
their natural environment with little or no intervention from
external personnel. However, such systems do not generally contain
an independent evaluation module because their purpose is only to
measure movement and not to interpret or analyze such movement
without external assistance. Feedback systems have also been
developed for training interventions for repetitive exercises, such
as walking or running, and for use in rehabilitation. However these
feedback systems typically use external measurements taken by
and/or evaluated by professional personnel, such as a coach,
physical therapist, exercise physiologist, and the like.
[0005] Thus, there is a need in the art for systems and methods to
measure, assess, and provide feedback regarding an athlete's or
individual's movements so as to prevent injuries and/or improve
performance. The present invention addresses this need.
SUMMARY OF THE INVENTION
[0006] This Summary is provided to introduce a selection of
concepts in a simplified form that are further described below in
the Detailed Description, and is not intended to identify key or
essential features of the claimed subject matter, nor is it
intended to be used to limit the scope of the claimed subject
matter. Other features, details, utilities, and advantages of the
claimed subject matter will be apparent from the following written
Detailed Description including those aspects illustrated in the
accompanying drawings and defined in the appended claims.
[0007] The present invention provides systems and methods that
measure, analyze, and evaluate a user's movement during a specific
activity to determine his or her risk for injury (traumatic or due
to repetitive motion), then optionally provide focused feedback as
to how the user can modify the movement. The evaluation and
feedback are immediate, quantitative, and objective in nature. The
feedback concentrates on modifying the user's technique in order to
reduce his or her risk for injury and, optionally, to improve his
or her performance. The systems and methods of the present
invention give the user individualized training as the feedback
provided is based on measurements taken from the user. Further,
because the evaluation criteria, movement modifications and
training strategies are embedded in the system, the present
invention can be used without the supervision of an expert observer
or professional while delivering consistent, objective, and quality
guidance. The systems and methods comprise four
modules--Measurement, Processing, Feedback and Display, and
Recording--that can be configured in many embodiments without
significant hardware modifications to analyze a variety of
different parameters associated with a host of different movements,
particularly movements that permit assessment of risk for injury
and training to reduce this risk.
[0008] In one embodiment, the invention provides a method for
training a subject to avoid joint injuries, comprising: gathering
raw data from at least one sensor attached to a subject, to an
interface, or in the subject's environment where the at least one
sensor allows quantifying at least one parameter associated with a
movement known to correspond to arisk of joint injury; transmitting
the raw data to at least one processor; evaluating the risk of
injury by comparing the raw data or processed raw data to a stored
model; providing feedback to the subject based on the evaluated
risk of injury so the subject can alter the movement and reduce the
risk of joint injury; and storing at least one of the raw data, the
processed raw data, the evaluated risk data and the feedback
data.
[0009] In some aspects of this embodiment, at least five sensors or
more are used; and in some other aspects of this embodiment, at
least ten, fifteen, twenty sensors or more are used.
[0010] In various aspects of this embodiment of the invention, the
at least one sensor is a gyroscope, an accelerometer, a
magnetometer, an electrode, a pressure sensor, a force sensor, a
torque sensor, a force platform, a speed sensor, a goniometer, a
camera, or a thermometer or various combinations of these
sensors.
[0011] Various aspects of this embodiment of the invention quantify
a movement performed during walking, jogging, running, jumping,
throwing, swinging, kicking, swimming, rowing, squatting, lifting,
pushing, climbing, cutting, blocking, skiing, snowboarding,
punching, sitting, typing, cycling, or dancing.
[0012] In aspects of this embodiment of the invention, the at least
one parameter is selected from joint kinematics, joint kinetics,
body segment posture, body segment kinematics, body segment
kinetics, and in some aspects of the invention, the at least one
parameter is selected from ankle flexion, eversion, rotation angle,
angular velocity, angular acceleration, force, moment, or power;
knee flexion, abduction, rotation angle, angular velocity, angular
acceleration, force, moment, or power; hip flexion, abduction,
rotation angle, angular velocity, angular acceleration, force,
moment, or power; spine flexion, lateral bending, rotation angle,
angular velocity, angular acceleration, force, moment, or power;
shoulder flexion, abduction, rotation angle, angular velocity,
angular acceleration, force, moment, or power; elbow flexion,
abduction, rotation angle, angular velocity, angular acceleration,
force, moment, or power; wrist flexion, abduction, rotation angle,
angular velocity, angular acceleration, force, moment, or power;
neck flexion, lateral bending, rotation angle, angular velocity,
angular acceleration, force, moment, or power; foot position,
velocity, acceleration, jerk, orientation, angular velocity,
angular acceleration, or angular jerk; shank position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; thigh position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; pelvis position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; trunk position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; upper arm position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; forearm position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; hand position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; or head position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk. In certain aspects of the invention,
the at least one parameter is selected from force, pressure, or
moment between the subject and an interface or the environment. In
certain aspects of the invention, the at least one parameter is
selected from muscle activity. In some aspects, two, three, four,
five, ten, or twenty or more of these parameters are measured.
[0013] In some aspects, the methods are used to increase a
subject's performance in addition to reducing the risk of joint
injuries.
[0014] In some aspects of the invention, the feedback provided is
visual, and some aspects of the invention, the visual feedback is a
graph, an avatar, is three dimensional and/or any combination of
these. In some aspects, the feedback provided is auditory or is
tactile or haptic or a combination of any of these, or any
combination of these with visual feedback configurations.
[0015] In some aspects of this embodiment of the invention, the
joint injury is selected from a joint injury to a knee, elbow,
wrist, ankle, hip, shoulder, or spine.
[0016] Other embodiments of the invention provide a body movement
training system comprising: at least one sensor configured to
measure at least one parameter associated with a movement known to
correspond to risk of joint injury; transmitters associated with
the at least one sensor to transmit raw data related to the at
least one parameter to at least one processor; at least one
processor configured to receive the raw data from the transmitters,
process the raw data, compare the raw data or processed raw data to
a stored model, evaluate the risk of joint injury based on the
comparison of the raw data or processed raw data to the stored
model, and generate feedback data; a display or interface device to
provide immediate feedback to the subject based on the feedback
data; and a storage medium to record the raw data, the processed
raw data, the evaluated data and the feedback data.
[0017] In some aspects, the body movement measurement system uses
at least five or more sensors, and in some aspects, at least ten,
fifteen, twenty or more sensors are used.
[0018] In some aspects of this embodiment, the at least one sensor
is a gyroscope, an accelerometer, a magnetometer, an electrode, a
pressure sensor, a force sensor, a torque sensor, a force platform,
a speed sensor, a goniometer, a camera, or a thermometer.
[0019] In various aspects of this embodiment, the movement measured
is performed during walking, jogging, running, jumping, throwing,
swinging, kicking, swimming, rowing, squatting, lifting, pushing,
climbing, cutting, blocking, skiing, snowboarding, punching,
sitting, typing, cycling, or dancing.
[0020] In some aspects, the at least one parameter is selected from
joint kinetics, joint kinematics, body segment posture, body
segment kinematics, body segment kinetics; and in some aspects, the
at least one parameter is selected from ankle flexion, eversion,
rotation angle, angular velocity, angular acceleration, force,
moment, or power; knee flexion, abduction, rotation angle, angular
velocity, angular acceleration, force, moment, or power; hip
flexion, abduction, rotation angle, angular velocity, angular
acceleration, force, moment, or power; spine flexion, lateral
bending, rotation angle, angular velocity, angular acceleration,
force, moment, or power; shoulder flexion, abduction, rotation
angle, angular velocity, angular acceleration, force, moment, or
power; elbow flexion, abduction, rotation angle, angular velocity,
angular acceleration, force, moment, or power; wrist flexion,
abduction, rotation angle, angular velocity, angular acceleration,
force, moment, or power; neck flexion, lateral bending, rotation
angle, angular velocity, angular acceleration, force, moment, or
power; foot position, velocity, acceleration, jerk, orientation,
angular velocity, angular acceleration, or angular jerk; shank
position, velocity, acceleration, jerk, orientation, angular
velocity, angular acceleration, or angular jerk; thigh position,
velocity, acceleration, jerk, orientation, angular velocity,
angular acceleration, or angular jerk; pelvis position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; trunk position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; upper arm position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; forearm position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; hand position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk; or head position, velocity,
acceleration, jerk, orientation, angular velocity, angular
acceleration, or angular jerk, force, pressure, or moment between
the subject and an interface or the environment, muscle
activity.
[0021] In some aspects, the feedback provided is visual, including
but not limited to graphs, avatars, three dimensional graphics
and/or combinations thereof. In some aspects, the feedback provided
is auditory, tactile or haptic or combinations of any of these.
[0022] In some aspects, the joint injury is a joint injury to a
knee, elbow, wrist, ankle, hip, shoulder, or spine.
[0023] In some aspects, system is used to increase a subject's
performance in addition to reducing the risk of joint injuries.
[0024] Yet other embodiments and aspects of the invention are
described in the Detailed Description below.
DESCRIPTION OF THE FIGURES
[0025] FIG. 1 is a simple flow chart showing the modules of the
present invention.
[0026] FIG. 2 shows an exemplary experimental protocol for a
testing session using the systems and methods of the invention.
Vertical arrows indicate when feedback may be given to subjects in
this exemplary protocol.
[0027] FIG. 3 is a table showing a standardized set of movement
modifications for a training session for reducing the risk of
anterior cruciate ligament (ACL) injury.
[0028] FIG. 4 shows graphs of time continuous parameters and
associated discrete metrics for one subject during one jump.
Figures above the graphs illustrate jump sequence, and the grey box
indicates stance phase. GC=Ground Contact, ED=End of Deceleration,
TO=Toe Off.
[0029] FIG. 5 shows graphs of four feedback variables as measured
in a testing session for one subject. For each variable, the first
data point (first x) indicates mean baseline value, subsequent data
points (x's) indicate training jump values, and the last data point
(circle) indicates the most recently completed training jump.
Shading indicates lower risk range. For thigh coronal velocity,
0.degree./sec was the target value and for jump height, the subject
was asked to maintain the mean baseline value.
[0030] FIG. 6 shows a feedback history for a full test (baseline to
follow-up) for a typical subject. For each feedback variable, the
first data point (circle) indicates mean baseline value, subsequent
data points (triangles) indicate training jump value, and the last
data point (cross) indicates the mean follow-up value. Shading
indicates lower risk range.
[0031] FIG. 7 shows the change in knee flexion angle, trunk lean,
and thigh coronal angular velocity by subject from baseline to
follow-up. Shading indicates lower risk range.
[0032] FIGS. 8 A and B are tables. FIG. 8A is a table listing knee
flexion angle, trunk lean, and jump height at baseline and
follow-up. Number at risk indicates number of subjects outside the
low risk ranges. Two stars (**) indicate significant difference
between baseline and follow-up (p<0.001). FIG. 8B is a table
listing thigh coronal angular velocity and knee abduction moment at
baseline and follow-up. For thigh coronal angular velocity, change
was calculated as the difference between the absolute value at
baseline and the absolute value at follow-up. Knee abduction moment
was split into at-risk (ABD Baseline) and not-at-risk (ADD
Baseline) cohorts. The at-risk cohort had a positive (abduction)
peak moment at baseline while the not-at-risk cohort had a negative
(adduction) peak moment at baseline. One star (*) indicates
significant difference between baseline and follow-up (p<0.01),
and one hat ( ) indicates a trend to significant difference between
baseline and follow-up (p=0.06).
[0033] FIG. 9 are bar graphs showing the change in knee abduction
moment by subject from baseline to follow-up, split into at-risk
and not-at-risk cohorts at baseline. The at-risk cohort (top) had a
positive (abduction) peak moment at baseline while the not-at-risk
cohort (bottom) had a negative (adduction) peak moment at baseline.
Shading indicates lower risk range.
[0034] FIG. 10 shows the six phases of the pitching motion: windup
(A), early cocking (B), late cocking (C), acceleration (D),
deceleration (E), and follow-through (F). The windup begins when
the pitcher initiates his motion and ends when he removes the ball
from his glove. In the early cocking stage, the stride leg extends
toward the batter, the knee and hip of the pivot leg extend as
well, and the body is propelled forward into the stride. The early
cocking (stride) phase ends when the stride foot contacts the
ground. During late cocking, the trunk rotates forward, while the
shoulder achieves a position of maximal external rotation. In the
acceleration phase, the shoulder is powerfully internally rotated;
and, following ball release, strong deceleration forces are then
applied to the shoulder as it internally rotates. When the arm
reaches a position of 0.degree. internal rotation, the deceleration
phase is complete. During the less violent follow-through phase,
the arm is adducted across the pitcher's body (see Park et al.,
Bull. Hosp. Jt. Dis. 61:1-2 (2002-2003)).
DETAILED DESCRIPTION OF THE INVENTION
[0035] The practice of the techniques described herein may employ,
unless otherwise indicated, conventional techniques and
descriptions of biomechanics, rehabilitation, neurobiology,
physiology, electrophysiology, physical conditioning, data
analysis, or signal processing, all of which are within the skill
of those who practice in the art. Specific illustrations of
suitable techniques can be had by reference to the Examples herein;
however, other equivalent conventional procedures can, of course,
also be used. Such conventional techniques and descriptions can be
found in standard manuals and texts such as Winter, Biomechanics
and motor control of human movement, Fourth Ed., 2009 (John Wiley
& Sons); Mow et al., Basic orthopaedic biomechanics &
mechano-biology, Third Ed., 2005 (Lippincott Williams &
Wilkins); Kenney, et al., Physiology of Sport and Exercise, Fifth
Ed., 2011 (Human Kinetics); Eston and Reilly (Eds.),
Kinanthropometry Laboratory Manual: Anthropometry and Exercise
Physiology, 2009 (Rutledge); Hamilton, et al., Kinesiology:
Scientific Basis of Human Motion, 2007 (McGraw Hill); ACSM, ACSM's
Guidelines for Testing and Prescription, Eighth Ed., 2005
(Lippincott Williams and Wilkins); Heyward, Advanced Fitness
Assessment and Exercise Prescription, Sixth Ed., 2010 (Human
Kinetics); Baechle and Earle, Essentials of Strength Training and
Conditioning, Third Ed., 2008 (Human Kinetics); Blazevich, Sports
Biomechanics: The Basics: Optimizing Human Performance, 2010
(A&C Black); Hay, Biomechanics of Sports Techniques, Fourth
Ed., 1993 (Benjamin Cummings); and Bartlett and Bussey, Sports
Biomechanics: Reducing Injury Risk and Improving Sports
Performance, 2011 (Rutledge); Fayyad et al., Advances in knowledge
discovery and data mining, 1996 (MIT Press); Proakis et al.,
Digital signal processing, Fourth Ed. (Lavoisier), all of which are
herein incorporated in their entirety by reference for all
purposes.
[0036] Note that as used herein and in the appended claims, the
singular forms "a," "an," and "the" include plural referents unless
the context clearly dictates otherwise. Thus, for example,
reference to "a metric for ACL injury" refers to one or more
metrics for ACL injury, and reference to "administering" or
"administration" includes reference to equivalent steps and methods
known to those skilled in the art, and so forth.
[0037] Unless defined otherwise, all technical and scientific terms
used herein have the same meaning as commonly understood by one of
ordinary skill in the art to which this invention belongs. All
publications mentioned herein are incorporated by reference for the
purpose of describing and disclosing devices, formulations and
methodologies that may be used in connection with the presently
described invention.
[0038] Where a range of values is provided, it is understood that
each intervening value, between the upper and lower limit of that
range and any intervening value in that stated range is encompassed
within the invention. The upper and lower limits of these smaller
ranges may independently be included in the smaller ranges, and are
also encompassed within the invention subject to any specifically
excluded limit in the stated range. Where the stated range includes
one or both of the limits, ranges excluding either both of those
included limits are also included in the invention.
[0039] In the following description, numerous specific details are
set forth to provide a more thorough understanding of the present
invention. However, it will be apparent to one of skill in the art
that the present invention may be practiced without one or more of
these specific details. In other instances, features and procedures
well known to those skilled in the art have not been described in
order to avoid obscuring the invention.
The Invention in General
[0040] The present invention provides systems and methods that
measure, analyze, and evaluate a user's movement during a specific
activity to assess his or her risk for injury, including joint
injuries, then optionally provide focused and immediate feedback as
to how the user can modify the movement. The evaluation and
feedback are both quantitative and objective. The feedback
concentrates on modifying the user's technique in order to reduce
his or her risk for injury, as well as optionally improve his or
her performance. "Immediate" means providing feedback where the
processing system responds as rapidly as necessary to the subject's
movement; in some embodiments (such as described in Examples 2 and
4 herein), feedback is provided in real-time while the subject is
performing the movement(s), and in other embodiments (such as
Examples 1 and 3 herein), the feedback is provided directly
following the subject's performance of the movement. The systems
and methods of the present invention give the user individualized
training as the feedback provided is based on measurements of the
individual. Furthermore, because the evaluation criteria, movement
modifications and training strategies are embedded in the system,
the present invention can be used without the supervision of an
expert observer or professional while delivering consistent and
quality guidance. The systems and methods generally comprise four
modules--Measurement, Processing, Feedback and Display, and
Recording (see FIG. 1)--that typically can be configured without
significant hardware modifications to analyze a variety of
different movements, including movements that permit assessment or
training relative to risk for injury, performance or both.
[0041] The movements that can be measured and evaluated by the
present invention are almost endless and include a broad range of
sports activities, such as throwing (baseball, football, tennis
serves), jumping (basketball, volleyball), sprinting (track,
soccer, football), and weight lifting (squatting, free weights, and
the like). Furthermore, the invention also may assess
rehabilitation movements as well as movements associated with
repetitive occupational tasks such as lifting and other tasks
associated with ergonomic evaluations. Conditions associated with
aging, such as risk of falls or diminution of balance, as well as
assessment of compensatory movements, also may be monitored by the
systems and methods of the invention. The critical problem
addressed by the present invention is how to provide individualized
measurement, analysis, evaluation, and feedback on movement
technique any time and virtually anywhere without external
assistance from a third party such as a coach, physical therapist
or other professional.
[0042] The methods and systems of the present invention can be used
to train individuals to move in a way that is less likely to result
in injury, for example, joint injuries, bone fatigue fractures,
muscle strains and the like.
[0043] One preferred application of the systems and methods of the
present invention is to reduce the risk of joint injuries. The
joints of the human body are subject to many types of injuries,
including sprains (overstretching of the ligaments that hold the
bones of a joint together), strains (overstretching the tendons),
and tears or ruptures of the ligaments, tendons, articular
cartilages, or intervertebral discs. In particular, the knee joint
is one of the most commonly injured joints due to its complex
structure and the high loads that it sustains. Injuries to the knee
include sprains, tears or rupture of the anterior or posterior
cruciate ligaments, patellar tendinitis, meniscal tears, and other
knee strains. Other joints prone to injury during sports or
occupational activities include the elbow and wrist (dislocations,
sprains, strains), the ankle (Achilles tendinitis, sprains, and
strains), the hip (dislocation), the shoulder (dislocations,
strains, sprains, rotator cuff tears, separated shoulder), and the
spine (disc herniation). Avoiding such injuries not only prevents
the direct injury, but prevents long-term deterioration and
degeneration of the joint. The systems and methods of the present
invention can be used to measure, analyze, and evaluate an
individual's unique movement, and then optionally provide focused
feedback as to how the individual can alter his or her movement to
reduce risk of injury.
[0044] Another preferred application of the systems and methods of
the present invention is the use of the invention to improve or
optimize performance. For example, during sports where an athlete
must move quickly with high accuracy, it is of interest to be able
to measure the timing, accuracy, and consistency of the phases of
the athlete's movement, for example: swinging a golf club or tennis
racket, passing a football, serving a volleyball or tennis ball,
jumping to spike a volleyball or shoot a basket, performing a turn
in swimming, and other such movements. Consistent timing and body
positioning are cornerstones for repeatability of performance, and
muscle memory is key to consistent timing and body positioning.
Through training, conditioning, analysis, and feedback, an
athlete's variations in technique can be reduced, and a proper
movement ingrained. Additionally, such training does not only apply
to athletes, but can be used to train non-athletes, such as
individuals going through rehabilitation after a stroke or other
physical challenge, or individuals who perform repetitive
occupational tasks.
[0045] In some embodiments, the device focuses only on evaluating
the risk of injury or the performance and does not provide any
feedback to the subject on how to alter the movement. In these
embodiments, the primary function of the device is to provide only
an assessment of the subject's movements. This assessment may be
used to determine if the subject is at risk for a specific injury,
to identify subjects that need to be enrolled in an injury
prevention program, or to monitor changes in a subject's risk of
injury over a period of time. These embodiments also can be used to
determine if the performance of the subject is improving, to
determine if the risk of injury is changing as the performance
changes, or to track a subject's performance as they progress
through a training program. In these cases, the invention will
serve as a quantitative assessment tool that may provide valuable
information to the subject as well as to trained professionals
assisting the subject. The assessment provided may then be used to
determine a future plan for the subject, alter the current plan, or
determine if the subject needs additional training for injury
prevention or performance enhancement.
[0046] FIG. 1 is a simple flow chart showing the Modules of the
methods 100 of the present invention. In its simplest form, the
systems and methods of the present invention provide modules to
measure 120 the signal from sensors during one or more movements
made by an individual (Measurement Module); process the data 140
acquired by the Measurement Module to obtain continuous parameters
and discrete metrics that describe the movement quantitatively,
evaluate the risk or performance, and provide data to control the
feedback associated with the one or more movements (Processing
Module); provide immediate, complex, and individualized feedback
and/or simply display the results of the risk or performance
evaluation 160 to the individual (Feedback and Display Module); and
record 180 the measurement, evaluation, feedback and other data
associated with the methods (Recording Module). Each Module is
described in more detail below.
Measurement
[0047] The Measurement Module of the present invention measures the
signal from sensors during one or more movements made by an
individual. For example, movements that may be evaluated include
but are not limited to walking; jogging; running; jumping; movement
of an arm when swinging a tennis racket, golf club or throwing a
baseball, football or serving a volleyball; kicking a ball; leg and
arm movements while swimming; rowing; squatting; lifting; pushing;
climbing; cutting; blocking; body movements during skiing or
snowboarding; shooting a basketball; aiming a gun; martial arts
punches and kicks; work related movements such as typing while
sitting or moving heavy objects; and the like. Parameters
associated with the movements generally involve joint angles, body
segment posture, body segment kinematics and kinetics, and the
like, including but not limited to: ankle, knee, hip, spine,
shoulder, elbow, wrist, and neck flexion, abduction, and internal
rotation angle, angular velocity, and angular acceleration; foot,
shank, thigh, pelvis, trunk, upper arm, forearm, hand, and head
position, velocity, acceleration, jerk, orientation, angular
velocity, angular acceleration and angular jerk; muscle activation;
and the associated kinetic parameters. The Measurement Module may
also involve sensors to measure metrics like stride length, step
length, cadence, progression line, toe-out angle, jump height and
length, and the like.
[0048] Devices used in measuring the various parameters of movement
include sensors placed on desired parts of the body segments, in
the environment, on the floor, or placed on different interfaces or
objects. These sensors include but are not limited to gyroscopes to
measure angular velocity; accelerometers to measure inclination or
linear acceleration; magnetometers to measure magnetic field
strength or direction; electrodes to measure changes in electrical
potential, muscle activation, or heart rate; pressure, force, or
torque sensors to measure kinetic interaction between body parts
and interfaces; cameras coupled with or without markers to measure
position of body segments or objects; force platform systems to
measure ground reaction forces and moments; goniometers to measure
joint angles; speed sensors to measure speed; and temperature
sensors to measure body parts or ambient heat. These sensors are
connected to one processor or to a network of processors that
acquires the movement data during the testing session by sampling
and storing the signal from the sensors at predefined sampling
frequency.
Processing: Analysis and Evaluation
[0049] In the Processing (Analysis and Evaluation) Module, data
acquired by the sensors and stored in a memory during the subject's
movement (Measurement Module) is processed to obtain specific time
continuous descriptive parameters (for example: knee angles,
position of the head, medial-lateral velocity of the subject's
center of mass, etc.). Discrete metrics are then extracted from
these parameters to quantify the movement (for example: maximum
knee flexion during stance, highest position of the head, mean
value of the medial-lateral velocity of the subject's center of
mass, etc.). This Module also uses a "comparison model" to evaluate
the risk for injury and provide data on how the user can alter his
or her technique to reduce the risk for injury. The comparison
model consists of comparing the subject's actual movement
(described by a set of discrete metrics) with a target (reference)
movement execution. Analysis of the data acquired in the
Measurement Module of the invention typically involves both
standard and custom algorithms. These algorithms include but are
not limited to altering the measurement units; calibrating the
signals to account for the location of the sensors on the body
segments, on the objects, or in the environment; smoothing or
filtering the signals; analyzing and combining the signals to
obtain the specific descriptive parameters; extracting discrete
metrics from the descriptive parameters; comparing the subject's
movement (described by a set of discrete metrics) with a target
movement using a comparison model to evaluate the risk of injury
and, optionally, the performance, and to provide data on how the
user can improve his or her technique; and finally making the
continuous parameters, discrete metrics, results of the risk or
performance evaluation, and the data for the feedback available to
the Feedback and Display Module.
[0050] The first step of the analysis is to conduct calibration
routines for each sensor to obtain signals in the proper units. The
units of the signals from the sensors are converted from the
measured units (like volt) to the desired measurement units (like
degree per second, or g-force) using predefined calibration
equations. Then, the signals are modified based on the individual
placement of the sensors and conditions of the testing session. All
calibration procedures are customized to the specific types of
sensors being used as well as the location of the sensors on the
body segments, on the objects, or in the testing environment. For
example, calibration routines for an accelerometer attached to a
body segment identify the position and orientation of the sensors
relative to the segment. Additionally, in some cases, the sensors
are adjusted based on the initial conditions of the testing session
(initial position, orientation, temperature, etc).
[0051] The data may be filtered or smoothed using either standard
signal processing filters (Butterworth filters, Gaussian filters,
etc.) or custom designed filters specific to the application.
[0052] Once the data is in the proper units and adjusted, a
customized analysis of the movement is completed, which depends on
the type of sensors used and the movement analyzed. In general, the
signals are processed to obtain specific time continuous
descriptive parameters (for example: knee angles, position of the
head, medial-lateral velocity of the subject's center of mass,
etc.), critical temporal features of the movement are then
identified (for example, the start and stop times of the movement,
and any distinctive time points like take-off, landing, ball
catching and release, etc), and discrete metrics are determined
either as values of the descriptive parameters at those critical
time points (for example: knee flexion at take-off, etc.) or
statistical reduction of the parameters between time points (for
example, the mean value of the medial-lateral velocity of the
subject's center of mass, etc.). If a desired parameter is not
measured directly, the data from the sensors is manipulated to
produce the desired parameter; for example, position may be the
desired descriptive parameter but velocity is actually measured,
therefore velocity is integrated to calculate position. The sensor
data may also be combined to reduce the error of measurement using
methods such as Kalman filtering; for example, position data
calculated from velocity may be enhanced using occasional position
data to correct for drift in the non-ideal velocity sensor.
[0053] Finally, the discrete metrics are used to compare the
subject's movement to a target execution of the movement using a
comparison model. The model typically is embedded in the system and
has been determined prior to the measurement at hand. The model
varies depending on the movement measured as well as the desired
goal of the evaluation and possible feedback (injury prevention,
performance evaluation). The model may consist of a comparison with
discrete target metrics or may consist of a data manipulation
algorithm, such as a neural network, a principal component
analysis, or the like that perform a comparison considering all the
discrete metrics simultaneously. Subject specific metrics may be
included in the model, like the subject's age, height, weight,
dominant leg/hand, ethnicity, and the like. The model may also
include reference data, which may be either ideal data generated
from computational methods or actual data collected from a variety
of exemplar subjects prior to the measurement at hand. The model
may be adjusted based on the specific circumstances of the subject,
the movement to be measured, and the desired goal of the evaluation
or feedback.
[0054] The outputs of the comparison model are an evaluation of the
risk of injury; for example, in the form of a score or of
similarities and differences compared to the target execution of
the movement using a set of the discrete metrics or other
evaluation variables. The model may also provide additional outputs
that will be used to control the feedback and indicate how the user
can modify his or her technique to be less at risk for injury, or
outputs describing the movement or the performance. Finally, the
Processing Module transmits the time continuous parameters,
temporal features, discrete metrics and the outputs of the
comparison model to the Feedback and Display Module which will use
the data to control the feedback provided to the user or display
the results of the evaluation.
Feedback and Display
[0055] The type and quantity of feedback provided depends on the
specific embodiment of the invention. The feedback is based on the
data transmitted by the Processing (analysis and evaluation)
Module. Feedback may be provided to the subject in any number of
ways. Various graphical displays may be used to provide feedback.
For example, feedback may be provided by displaying the outputs of
the comparison model in chart or graph form, as shown in FIGS. 4
and 5, on a monitor or other display. The charts or graphs may
display not only the most recent variables, but a series of
variables taken over time (as shown in FIG. 5), as well as risk,
target, desired and/or optimal performance ranges for those
variables, and the like. Alternatively or in addition, the
graphical display may include images of the subject (or an avatar)
performing the movement, with superimposed visual indicators
showing optimal movement accomplishment. In some embodiments, the
display may use perspective techniques to display a
three-dimensional animation such that body movements can be seen
from different points of view in a three-dimensional space.
Furthermore, the graphical display may include videos of other
subjects performing ideal or non-ideal jumps with explanations
and/or comparisons to the current subject's movement. In addition,
information such as text or a cartoon might be provided. The
graphical display may be on a computer monitor, a TV, a smartphone,
provided by a projector, or other type of display platform. Similar
visual methods to the methods presented in this paragraph are used
to communicate the results of the risk or performance evaluation to
the user.
[0056] In addition to using graphical displays, feedback may also
be provided to the subject by way of audio signals, such as bells,
beeps, buzzers, chimes, alarms, a synthetic voice giving
instructions, or other suitable sounds. In some embodiments, the
sounds audible to the subject can be descriptive: one sound (e.g.,
a clicking sound, a buzz, a beep of one tonality) can indicate that
a movement has been performed inappropriately; another sound (e.g.,
a swoosh sound, a pleasant chord, or a beep of a different
tonality) can indicate that the movement has been performed
appropriately. In some embodiments, the pitch, intensity, and/or
frequency of the sound can change to provide information about how
much the subject's movement and/or position varies from a certain
value or range of values or to provide other information to the
subject. Audio feedback may be provided from feedback devices
located on the subject's body or separated from the body.
[0057] Other sensory cues can be used as an alternative to or in
addition to graphical or auditory signals. For example, feedback
mechanisms may comprise haptic devices that provide vibrations,
forces, or pressure that can be detected by the subject. The
feedback may include one or more vibration devices placed on the
body of the subject that can indicate if the movement has been
performed appropriately; the type and strength of the vibration can
also be used to provide information to the subject. Alternatively
or additionally, this feedback might include resistive or
constructive forces to the subject's body to indicate the desired
ideal movements or to prevent the subject from moving in a
non-ideal manner. These resistive or constructive forces may be
produced by a variety of actuators, and may be controlled by a
variety of control mechanisms. The feedback may also be pressure
actuators that apply pressure to the body to indicate how the
subject should conduct the movement. These pressure actuators may
also vary in location and intensity based on the desired feedback
necessary for the subject.
[0058] In some embodiments, the visual, audio, or other types of
feedback can also be used prescriptively. For example, a series of
sounds can be emitted that correspond to the proper rhythm of the
movement, and the subject can match the movement to the cadence of
the sounds. Visual and haptic indicators can be prescriptive or
descriptive as well.
Recording
[0059] The data produced by the systems and methods of the present
invention can be recorded, stored, and retrieved using hardware and
software well known to those skilled in the art. Generally, the
systems of the present invention comprise a storage device such as
a disk drive, RAM, or memory card. The storage device records the
data acquired and analyzed by the system and also provides access
to the data.
EXAMPLES
[0060] The following examples are put forth so as to provide those
of ordinary skill in the art with a complete disclosure and
description of how to make and use the present invention, and are
not intended to limit the scope of what the inventors regard as
their invention, nor are they intended to represent or imply that
the experiments below are all of or the only experiments performed.
It will be appreciated by persons skilled in the art that numerous
variations and/or modifications may be made to the invention as
shown in the specific embodiments without departing from the spirit
or scope of the invention as broadly described. The present
embodiments are, therefore, to be considered in all respects as
illustrative and not restrictive. Efforts have been made to ensure
accuracy with respect to numbers used but some experimental errors
and deviations should be accounted for.
Example 1
Anterior Cruciate Ligament (ACL) Injury Prevention
[0061] Extensive sections of the following example is excerpted
from Dowling A V, Favre J, Andriacchi T P, entitled "Inertial
sensor-based feedback can reduce key risk metrics for ACL injury
during jump landings." The final definitive version of this paper
is in press to be published in the American Journal of Sports
Medicine, by SAGE Publications, Inc., all rights reserved.
[0062] The anterior cruciate ligament (ACL) is the most commonly
injured ligament of the knee, and loss of this ligament often leads
to premature degenerative arthritis of the knee. As such,
researchers have developed intervention programs that can
successfully decrease the incidence of ACL injury. These preventive
programs are generally six to eight weeks in duration and require
two to three training sessions per week that are focused on
altering lower extremity biomechanics. Most of these training
sessions occur during team practices because the participants
cannot perform the intervention training independently. As a
result, compliance rates can be as low as 28% (see, Myklebust, et
al., Clin J. Sport Med, 13(2):71-78 (2003)). Further, either an
instructor or a physical therapist must be present to coach the
participants in order to ensure that they are properly performing
the training intervention. Coaching generally consists of verbal
instructions based on visual observations. Therefore, such coaching
is not quantitative in nature and can vary depending on the skill
of the observer. The independent and quantitative feedback systems
and methods of the present invention greatly improve these
intervention programs by allowing the subjects to conduct the
training sessions on their own while receiving consistent,
objective instructions based on measurements from the subject.
[0063] Many successful intervention programs emphasize proper jump
landing technique because landing from a jump is one of the primary
non-contact ACL injury mechanisms. Specific kinematic and kinetic
risk factors, such as a small knee flexion angle, small trunk
flexion angle, and large knee abduction moment, have been shown to
increase the risk for ACL injury during a jump landing.
Consequently, these risk factors have been the focus of several
intervention studies; however, measuring these parameters using
prior art methods and systems required a complex setup (e.g., gait
laboratory) as well as a substantial amount of time to prepare the
subject and process the data. Thus, in general, these parameters
are not rigorously measured outside of a research environment and
are instead estimated through visual observation.
[0064] The study described herein provided immediate visual
feedback based on measurements of parameters (knee flexion angle,
trunk lean, and thigh coronal angular velocity) using a simple
inertial sensor-based system to modify specific ACL injury risk
parameters (knee flexion angle, trunk lean, knee abduction moment)
during jump landing.
Protocol
[0065] Subjects
[0066] Seventeen subjects (7 male and 10 female) with an average
age of 27.5.+-.2.9 years and BMI of 22.8.+-.2.3 were selected for
this study. All were regular participants in sports involving
jumping maneuvers at the recreational level. Subjects with previous
lower limb musculoskeletal injuries requiring surgery or any
current symptoms of pain or injury were excluded.
[0067] Movement
[0068] The movement considered in this study was a bilateral
support drop jump maneuver in a gait laboratory. For this task,
each subject dropped off a 36 cm box, landed with both feet on the
ground, and then immediately performed a maximum height vertical
jump. The landing directly after the drop from the box was used for
the analysis (FIG. 4). The jump was considered acceptable if the
subject dropped off the box with both feet at the same time and
fully impacted a force plate embedded in the ground with their
right-side foot.
[0069] Experimental Design
[0070] The experimental protocol consisted of seven parts (see FIG.
2). During the preparation part, the embodiment of the invention
and reflective markers for an optoelectronic system (Qualisys
Medical, Gothenburg, SE) were placed on the subjects. The subjects
then performed a short warm-up consisting of light jogging and/or
squatting. When the subjects felt ready, calibration procedures
were performed for the feedback and optoelectronic systems. After
that, the jumping task was explained to the subjects, and they were
allowed to practice until they felt confident with the task. At
this point, the subjects conducted a baseline testing session
consisting of three drop jumps. For the baseline session, no
landing instructions were provided and the subjects were not aware
of what the feedback variables would be. Following the baseline
testing, the subjects completed a training session of 15 to 20
jumps within approximately 30 minutes where they received feedback
on their jumping technique. Immediately after the training session,
the subjects conducted a follow-up session also consisting of three
drop jumps to assess the change of injury risk after training. For
the follow-up testing, the subjects were asked to maintain the
jumping technique that they learned during the training session.
The subjects also had the opportunity to repeat a jump during this
session if they felt that they did not successfully accomplish the
movement modification.
[0071] Once the baseline testing was complete, the results of the
risk evaluation (based on the three baseline jumps) were shown to
the subjects. The principle of the feedback and the feedback
variables were then verbally explained to the subject using a
standardized speech. The subjects were told they would have between
15 and 20 jumps to incorporate the modifications into their jumping
technique. When the subjects achieved a jumping technique that
optimized all the feedback variables to the best of their ability,
or when they reached 20 training jumps, they were asked to maintain
that technique for the follow-up trials.
EMBODIMENT OF THE INVENTION
[0072] Measurement Module
[0073] In this embodiment of the invention, three small inertial
measurement units (Physilog.RTM., BioAGM, CH) affixed on the chest,
thigh, and shank segments respectively were used to measure the
movement. These units were connected to a computer that recorded
the signal from the inertial sensors at 240 Hz during the jump
task.
[0074] Processing Module
[0075] Using custom software, the raw signals coming from the
inertial sensors were adjusted to be insensitive to the actual
placement of the sensors on the body segment (functional
calibration). Then the knee flexion angle, trunk lean, and coronal
thigh angular velocity continuous descriptive parameters (FIG. 4)
were calculated immediately after the subject completed the jump
trial based on the signals from the inertial sensors. One
characteristic discrete metric previously identified as being
associated with ACL injury was then extracted from each kinematic
time series (FIG. 4). For the knee flexion angle and trunk lean,
the maximum values achieved during stance were chosen because they
have been suggested as risk factors for ACL injury and are common
components of intervention programs. For the thigh coronal angular
velocity, the first maximum (inward) peak during stance was
selected because it is correlated to the knee abduction moment,
which is a strong predictor of ACL injury risk. Additionally, jump
height was included as another metric to monitor the overall
performance of the jump. The technical details of this system, as
well as its validation for drop jump analysis, have been previously
described (see, e.g., Dowling, et al., J. Biomech Eng.,
133(7):071008; Dowling, et al., J. Biomech., in review, both of
which are incorporated herein in their entirety for all
purposes).
[0076] The comparison model consisted of comparing the maximum knee
flexion, maximum trunk lean and peak thigh angular velocity metrics
with predetermined target values. Based on the literature, a
direction associated with a higher risk for injury was determined
for the three metrics (i.e., knee extension, backward trunk lean
and inward thigh coronal angular velocity). The actual target
values for the evaluation were determined based on previous
research on healthy subjects conducting drop jumps that used the
same inertial sensor-based system (see, e.g., Dowling, et al., J.
Biomech Eng., 133(7):071008). Knee flexion angle and trunk lean
have been widely documented in the context of ACL injury; therefore
"lower risk" ranges were defined for these two parameters and the
subjects were considered as being at greater risk for injury if
their metrics were outside these ranges. The lower risk ranges,
[88.degree.; 120.degree.] for the knee flexion angle and
[25.degree.; 60.degree.] for the trunk lean, corresponded to the
upper half [median; maximum] of the data previously collected with
healthy subjects. No target range was defined for the thigh coronal
angular velocity because a risk threshold has never been reported
for this parameter nor has it been used in an intervention program.
Instead, the level of risk for this metric was determined based on
its difference compared to a neutral landing (i.e., with the first
peak of the thigh coronal angular velocity equal to 0.degree./sec);
the greater the difference, the greater the risk.
[0077] Finally, the Processing module transmitted the outputs of
the risk analysis as well as the jump height to the Feedback and
Display module.
Feedback and Display Module
[0078] For this embodiment, the feedback consisted of a projector
displaying graphs showing time series (one data point per jump) of
the feedback variables as well as target values (FIG. 5). After
each jump, the display was immediately updated to add the results
of the latest jump to the subject's training history. Subjects were
instructed to modify their mechanics in order to be to be within
those targets and they were provided with a standardized set of
movement modifications for each variable that would reduce their
risk of injury (FIG. 3). The feedback variables consisted of the
three kinematic metrics used for the risk evaluation (maximum knee
flexion angle, maximum trunk lean, and peak coronal thigh angular
velocity) plus jump height. The target values for the maximum knee
flexion and maximum trunk lean were the lower risk ranges
previously described, the target value for the peak thigh angular
velocity was the neutral landing, and the target for the jump
height was the values of the jumps height during the baseline
session (i.e., the athlete was ask to maintain his or her jump
height). For the knee flexion angle and trunk lean, the lower risk
range was shaded. This visual feedback is illustrated in FIG. 5.
The subjects were instructed to modify their landing mechanics in
order, starting with the knee flexion angle (if necessary), then
the trunk lean (if necessary), and finally the thigh coronal
angular velocity (if necessary). Regarding the jump height, the
subjects were instructed to maintain their baseline height during
all the jumping trials. In this experimental study, examiners
assisted the subjects during the training by repeating the
standardized set of movement modifications as many times as
requested by the subjects. Also, if the examiners observed that the
subjects were demonstrating a consistent landing technique and were
not progressing anymore, the examiners would suggest to the
subjects that they could move on to the next feedback parameter.
However, the systems and methods of the invention can be configured
to provide such information to the subjects in, e.g., the Feedback
Module.
[0079] Recording Module
[0080] For this embodiment of the invention, the raw and adjusted
signals from the sensors, the time continuous parameters, the
discrete metrics, the feedback variables, and the feedback targets
were stored in a memory after each jumping trial.
Auxiliary Evaluation System
[0081] The system of the present invention analyzed the first peak
of the thigh coronal angular velocity because this parameter has
been shown to be associated with the peak knee abduction moment
during a drop jump landing, which is a strong predictor of ACL
injury risk. However, the thigh coronal angular velocity has never
been directly related to ACL injury nor has the effect of a
modification of this parameter on the knee abduction moment been
investigated. Therefore, an auxiliary system was used to measure
the knee kinetics in order to determine whether the intervention
decreased the risk of injury in terms of the knee abduction moment.
This auxiliary system consisted of an optoelectronic motion capture
system (Qualisys Medical, Gothenburg, SE) with ten infrared cameras
collecting at 120 Hz and one force plate (Bertec, Columbus, Ohio)
collecting at 1200 Hz. The point cluster technique was used to
track the orientation of the foot, shank, and thigh frames (see
Andriacchi, et al., J. Biomech. Eng., 120(6)743-49 (1998)), and the
knee abduction moment was calculated using an inverse dynamic
approach. The subjects demonstrated two landing strategies for the
knee abduction moment: some subjects landed with primarily an
abduction moment while others landed with primarily an adduction
moment. To preserve these strategies, the average moment during the
deceleration phase of the landing was calculated. If this average
was positive (mainly in abduction), then the maximum value
(abduction peak) was reported; otherwise the minimum value
(adduction peak) was reported. To allow for comparison between
subjects, the knee abduction moment was normalized to percent
bodyweight and height (% BW*Ht).
Stastical Analysis
[0082] For each of the five metrics considered in this study (knee
flexion angle, trunk lean, thigh coronal angular velocity, knee
abduction moment, and jump height), during both the baseline and
the follow-up sessions the values from the three jumps were
averaged in order to have one mean value per subject per session.
Paired Student t-tests (baseline vs. follow-up) were used to
evaluate the effects of the training. All statistical tests were
performed in MATLAB version R2010b (The Mathworks, Natick, Mass.)
and the significance level was set a priori to 0.05.
Results
[0083] Within a 20 jump training session, all of the subjects were
able to respond to the feedback from the inertial sensor-based
system in terms of the knee flexion angle and the trunk lean, and
most of the subjects also were able to change the amplitude of
their thigh coronal angular velocity. The feedback history for a
full test (baseline to follow-up) is shown for a typical subject in
FIG. 6. In terms of the maximum knee flexion angle, at baseline
some subjects were outside the lower risk range, and at follow-up
all subjects were inside the pre-defined range (see FIGS. 7 and
8A). All but one subject increased their knee flexion angle during
the training (average change: 16.2.degree., p<0.001), and the
one subject that did not had a relatively high baseline value
(104.degree.). The results were similar for the maximum trunk lean.
At baseline, some subjects were outside the lower risk range, and
at follow-up all subjects were inside the range (see FIGS. 7 and
8A). All 17 subjects increased their trunk lean during the training
(average change: 17.4.degree., p<0.001). In terms of thigh
coronal angular velocity, at baseline 16 subjects had a positive
value (indicating an inward movement of the thigh after initial
contact) and one subject had a negative value (indicating an
outward movement of the thigh after initial contact). After
training, 13 subjects landed with a more neutral thigh coronal
angular velocity, and 4 subjects were not able to complete the
third modification. Overall, the subjects decreased the absolute
amplitude of the first peak of the thigh coronal angular velocity
by 20.1.degree./sec (p<0.01) (see FIGS. 7 and 8B). The subjects
also maintained the same jump height from baseline to follow-up
(p=0.6), and the average change in jump height was 0.5 cm.
[0084] Regarding the peak knee abduction moment, the average change
for all the subjects was -0.5% BW*Ht (p<0.001). For further
analysis, the subjects were split into two cohorts based on their
baseline values because previous work has shown that only an
abduction moment increases the risk of ACL injury. At baseline, 8
subjects had an abduction (positive) moment and were classified as
"at-risk", whereas 9 subjects had an adduction (negative) moment
and were classified as "not-at-risk" (FIG. 9). For the at-risk
cohort, 6 subjects had decreased their knee abduction moment at
follow-up (-1.2% BW*Ht) while 2 had increased their knee abduction
moment (0.4% BW*Ht). For the entire at-risk cohort, the average
change was -0.8 BW*Ht (trend to significance: p=0.06) (see FIGS. 8B
and 9). Moreover, two of the subjects in the baseline at-risk
cohort had an adduction (not-at-risk) moment after the training.
None of the subjects in the baseline not-at-risk cohort had an
abduction (at-risk) moment at follow-up, and the average change for
this cohort was not statistically significant (FIG. 9).
[0085] The results from this study show that the subjects could
effectively respond to the feedback from the sensor-based system of
the present invention in a single training session of up to 20
training jumps while maintaining the same jump height. The subjects
were able to positively modify their jumping technique in terms of
three key risk metrics for ACL injury based on the quantitative
feedback from the system combined with a set of instructions. All
of the subjects were able to maintain or to modify their knee
flexion angle and trunk lean to be within the lower risk ranges
after training. For the thigh coronal angular velocity, 13 subjects
(77% of the cohort) were able to modify their jumping technique in
order to land with more neutral velocity, suggesting that this
parameter was more difficult to alter; however, it is important to
note that the subjects were instructed to modify their landing
mechanics one parameter at a time and that the thigh coronal
angular velocity was the final parameter.
[0086] At follow-up, the subjects significantly reduced key risk
metrics for ACL injury in terms of the kinematic risk factors.
After training, the subjects increased both their maximum knee
flexion angle and their maximum trunk lean during stance. The
16.2.degree. increase obtained for the knee flexion angle is
comparable to previous intervention programs consisting of a single
training session reported in Mizner et al., J. Orthop. Sports Phys.
Ther., 38(6):353-61 (2008), where a change of 11.3.degree. was
observed for female athletes instructed to increase their knee
flexion angle during a drop jump landing. Another study by Onate
that investigated different combinations of feedback during a
vertical jumping task reported changes in knee flexion angle
between 27.degree. and 40.degree. (Onate, et al., Am. J. Sports
Med., 33(6):831-42 (2005)). Although no study has directly reported
the change in trunk lean after an intervention, the 17.4.degree.
increase observed in this study agrees with the change reported by
Blackburn et al. (Clin. Biomech., 23(3):313-19 (2008)) for trunk
flexion angle during a controlled drop jump landing task.
Furthermore, it is important to note that in this study the
amplitude of change for each kinematic parameter was driven by the
lower risk range; it is assumed that with enough training, any
subject could land with an exact amplitude of knee flexion angle
and trunk lean.
[0087] The decrease in the knee abduction moment between baseline
and follow-up also showed that the feedback system successfully
guided the subjects to decrease key risk metrics for ACL injury
during the training. The average decrease of 0.8% BW*Ht for the
at-risk cohort is comparable to the results from previous
intervention programs. Mizner et al. (J. Ortho. Sports Phys. Ther.,
38(6)353-61 (2008)) reported a 0.65% BW*Ht reduction in the knee
abduction moment for female athletes instructed to land softly and
avoid knee valgus during a drop jump landing. In another study,
female athletes considered at higher risk for ACL injury displayed
a decrease of 0.5% BW*Ht during a drop jump landing after a 7 week
neuromuscular training program (see Myer, et al., BMC
Musculoskelet. Disord., 8:39 (2007)).
[0088] In this study only three variables were used for the
feedback because it was anticipated that the subjects would not be
able to modify more than three variables during a single training
session. However, there are many other known ACL injury risk
factors that could be included in the feedback in order to improve
the intervention without modifying the hardware or the data
collection procedure (Measurement Module).
Example 2
Perfecting Squatting Form
[0089] The squat (and the related weighted squat) is one of the
most frequently used exercises in the field of strength and
conditioning. It is a core exercise in many training regimens
because it is biomechanically and neuromuscularly similar to a wide
range of athletic movements. It is also relevant to non-athletes
because it trains multiple muscle groups in a single maneuver,
similar to common activities of daily living like lifting packages
and picking up children. Squats have also been used to strengthen
lower-body muscles during rehabilitation after a joint injury (see
Schoenfeld, J. Strength. Cond. Res., 24:12 (2010)).
[0090] Injuries related to the squat exercise are minimal when
participants perform the exercise correctly, with proper technique
and appropriate weight. However, poor squatting technique can lead
to serious injury, especially during a weighted squat with heavy
weights. These injuries include muscle and ligament strains, and
spine maladies such as ruptured intervertebral discs,
spondylolysis, and spondylolisthesis. Therefore, it is critical
that athletes and non-athletes training with the squat exercise use
proper technique to minimize the risk of injury. The present
invention can be used to train athletes and non-athletes in ideal
squatting technique in order to prevent injuries related to poor
technique as well as to improve performance and increase
strength.
[0091] Ideal squatting technique is defined by a variety of joint
kinematic metrics during the exercise, all of which can be measured
by the current invention. Starting from the distal point of the
body, it is important that the heels remain flat on the floor
during the entire squatting exercise, as forces in the ACL are
significantly increased when squatting with elevated heels during
both ascent and descent (Toutoungi et al., Clin. Biomech. 15
(2000)). A dorsiflexion angle in the ankle of approximately
40.degree. is necessary to keep the heels on the floor.
Furthermore, the ideal placement of the feet is shoulder-width
apart, with a toe-out angle of approximately 30.degree. (see
Rippetoe et al., Starting Strength. ed. 2 (2007)). In terms of the
knee, the ideal position at the bottom of the squat is a neutral
knee (parallel with the feet) with no discernible knee abduction
angle, and the thighs will be parallel with the floor with the hip
joint below the patellarfemoral joint. Further, the knee should
extend only slightly beyond the toes, and forward knee translation
should be minimized. The trunk lean angle should be approximately
45.degree. from the horizontal at the bottom of the squat, and the
torso should remain flat and rigid. In terms of speed of the
maneuver, the entire movement should be conducted at a relatively
slow cadence (2 to 3 seconds eccentric tempo) to prevent injury,
and the hips and torso should descend and rise at the same speed
(see Rippetoe et al., supra).
[0092] The present invention can be used to monitor and provide
immediate feedback to a subject about kinematic parameters during
the execution of a squatting exercise. For this embodiment, the
Measurement Module consists of inertial measurement units
containing accelerometers and gyroscopes placed on the subject's
foot, shank, thigh, and two on the torso (lower back and sternum).
The Processing Module includes calibration routines (as described
in Example 1) to identify the locations of the sensors on the body
and to align the sensors in relation to one another and to the
global reference frame. The initial starting position of the body
is measured to determine the reference/neutral position for that
subject. The gyroscope and accelerometer measurements are combined
together (using the method described in Example 1) to measure the
kinematic time continuous parameters describing the movement of the
body segments during the squat (foot progression angle,
dorsiflexion angle, shank angle with the floor to determine knee
position relative to the foot, knee flexion and valgus angles,
trunk lean). The difference in the stationary accelerometer
measurements from the calibration position to the final position is
used to measure the subject's stance width and to determine whether
the thigh is parallel with the floor. The difference in
measurements between the two torso sensors determines if the trunk
is rigid and straight. The gyroscopes in the inertial measurement
units measure the speed of the movement for each segment by
measuring the segment angular velocity (similar to the previous
Example).
[0093] Temporal features and discrete metrics are calculated during
the execution of the movement, and a comparison model, similar to
the one presented in the previous Example, based on target values
for a set of discrete metrics is used to evaluate the risk for
injury and to produce the variables to control the feedback.
[0094] Due to the slow execution of this activity, the Feedback and
Display Module consists of true real-time feedback on body
positioning. Instead of waiting until the subject has completed the
movement (like in the previous Example), the subject receives
feedback during the movement while he or she can still adjust how
he or she is completing the exercise. Real-time feedback given
during the performance of the movement is especially beneficial for
a squat exercise because most of the success of the exercise
depends on the subject reaching target values. For example, the
squat is considered to have been executed more successfully if the
subject manages to increase his or her ankle, knee, and hip flexion
angles until his or her thighs are parallel with the ground. So for
this parameter (thigh angle), the feedback provided may be a
combination of a vibration device and auditory device. As the
subject nears the ideal position, the vibration device could
provide progressively stronger feedback to the subject indicating
that they are approaching the proper position; once they reach the
position, the auditory device could provide an auditory cue
indicating that the proper position has been reached. In this way,
the subject can adjust their movements based on the feedback while
the exercise is being executed in order to properly conduct the
movement. Furthermore, feedback may be given if the subject goes
beyond the ideal range; for example, if the subject exceeds the
desired trunk lean angle, a different auditory sound could indicate
that they are outside of the ideal range and should correct their
trunk positioning. Therefore, a combination of vibration and
auditory feedback on the various measured parameters may indicate
to the subjects during execution of the squat exercise maneuver
that the proper positioning for the movement is reached.
Furthermore, the feedback may be set to focus first on one or two
critical parameters, and additional parameters may then be added so
that the subject is not overwhelmed initially and is allowed to
master the technique in incremental steps (again similar to Example
1). Overall, teaching a subject the proper technique for a squat
exercise is yet another embodiment of the systems and methods of
the present invention and how they may be used for real-time
measurement, analysis, and feedback in order to prevent injuries
and improve performance.
[0095] For the Recording Module of this embodiment of the
invention, the raw and adjusted signals from the sensors, the time
continuous parameters, the discrete metrics, the feedback
variables, and the feedback targets are stored in a memory after
each squat.
Example 3
Optimizing Baseball Throwing Mechanics
[0096] Throwing a baseball is a coordinated motion that starts in
the toes and ends in the fingertips. A precise sequence of muscle
activity, starting in the lower body, is required to transmit
energy to the ball. Baseball pitchers complete thousands of throws
to learn the skills necessary to execute a fastball, curveball, and
the many other throws needed to play the game. Each of these throws
results in high forces in the arm and especially in the shoulder
joint, and pitchers are susceptible to significant shoulder
injuries from repetitive stress; for example, in order to achieve
ball velocity of 90 mph, the shoulder must rotate at angular
velocities of up to 7000.degree./sec and may be exposed to forces
of up to 950 N. In elite-level pitchers, there is a balance that
must be achieved between the shoulder mobility that is necessary to
reach extreme positions of rotation so that velocity can be
transmitted to the ball and the stability that is necessary to keep
the humeral head within the glenoid socket and prevent injuries.
Body rotation, timing, and positioning of the scapula are all key
components of the throwing motion, and any alterations to this
motion will have a compounded effect on the shoulder (see Braun et
al., J. Bone J. Surg. 91 (2009)).
[0097] A successful pitch involves both ball velocity and
precision. Ball velocity is most directly dependent on the amount
of external rotation achieved in the shoulder, while precision (the
ability to throw the ball at a specific location) is dependent on
the pitcher's specific arm position and timing of ball release. The
entire pitching motion consists of 6 phases: windup, early cocking,
late cocking, acceleration, deceleration, and follow-through, with
most injuries occurring during late cocking, acceleration, and
deceleration (see FIG. 10). As a result of the extensive research
conducted on pitching biomechanics, there are many different
parameters that may be monitored during a pitch. This Example
focuses on a select few parameters during the late cocking,
acceleration, and deceleration phases that are most critical to
injury and performance.
[0098] During late cocking, the shoulder should be between
90.degree. and 100.degree. of abduction, and should remain in this
position for the rest of the critical phases. Also during this
phase, the arm should rotate from a position of approximately
50.degree. of external rotation to about 175.degree. at maximum
external rotation, allowing the pitcher to apply a significant
force to the ball. In terms of muscle activation, the
subscapularis, pectoralis major, and latissimus dorsi provide
stability to the glenohumeral joint and should apply an anterior
force and an internal rotation torque to stabilize the joint. The
next phase, acceleration, should last only approximately 42 to 58
ms. The shoulder should be internally rotated, moving from
175.degree. of external rotation to 90.degree. or 100.degree. of
external rotation at ball release. The angular velocity of this
internal rotation should be a maximum of between 6000.degree./sec
and 7000.degree./sec. The subscapularis exhibits high activity to
position the humeral head and prevent subluxation, and high
activity in the teres minor helps to stabilize the joint by forming
a force couple with the pectoralis muscle to limit humeral head
translation (see Park et al., Bull. Hosp. Jt. Dis. 61:1-2
(2002-2003)). In the deceleration phase (50 ms after ball release),
the shoulder should continue rotating internally until the arm
reaches a position of 0.degree.. The internal rotation angular
velocity should also decrease to 0.degree./sec. The arm should
rapidly abduct about the shoulder to a position of approximately
110.degree.. The teres minor should exhibit the highest level of
activity as it acts to decelerate the arm by eccentric contraction
as well as stabilize the joint to limit humeral head translation
(see Park et al., Bull. Hosp. Jt. Dis. 61:1-2 (2002-2003)).
[0099] These parameters indicate that four measurements of the
shoulder joint are critical for pitching biomechanics; timing of
the movement, joint angles, joint angular velocity, and muscle
activation. As such, the invention described here can be used to
monitor and provide feedback to the subject about these parameters
immediately after the execution of the throw (similar to the method
described in the Example 1). The Measurement Module comprises
inertial measurement units containing accelerometers and gyroscopes
placed on the subject's shoulder and upper arm. Additional hardware
in the form of surface electromyography (EMG) electrodes are also
placed on the critical muscles (subscapularis, teres minor, etc) to
measure muscle activation. The Processing Module includes
calibration routines to identify the locations of the sensors on
the body, align the sensors in relation to one another and to the
global reference frame, and determine the maximum muscle
activations. The initial starting position of the arm is measured
to determine the reference/neutral position for that subject. The
gyroscope and accelerometer measurements are combined together
(using the method described in Example 1) to measure the kinematics
of the shoulder and arm (internal/external rotation at the
shoulder). The gyroscopes in the inertial measurement units measure
the speed of the movement of the arm by measuring the segment
angular velocity (similar to Example 1), and the surface
electromyography electrodes measure the muscle activation. Timing
is measured by the internal processor clock.
[0100] Temporal features and discrete metrics are calculated, and
then a comparison model similar to the one described in Examples 1
and 2 is used. Ideal values for each of the discrete metrics are
programmed into the model and the differences between the discrete
metrics from the subject's movement and the target metrics are the
basis of the risk and performance evaluation.
[0101] The Feedback and Display Module consists of providing
feedback to the subject immediately following the completion of the
throw (similar to Example 1). Since the ideal throwing motion
consists of ranges of acceptable values for each parameter, the
type of feedback given to the subject may resemble the feedback
provided in example 1. Visual feedback may consist of graphs
showing the subject's actual motion versus the ideal motion. The
subject may watch a video of the ideal movement superimposed over
their actual movement so that they can assess timing and angular
deviations in their movement. For example, for the internal
rotation of the arm, the subject might see how their measurements
compare to the target execution on a graph, with their previous
history also shown to represent their progress (similar to FIG. 5).
Haptic feedback to the subject might consist of vibration devices
placed on the muscles measured with the surface electromyography
electrodes; these devices could deliver vibratory feedback to
remind the subject to focus on activating those muscles. For timing
of the motion, the subject may receive auditory feedback indicating
how quickly the difference phases of the motion should be
completed. Altogether, teaching a subject the proper technique for
throwing a baseball is yet another embodiment of the present
invention and may be used for immediate measurement, analysis, and
feedback in order to prevent injuries and improve performance.
[0102] For the Recording Module of this embodiment of the
invention, the raw and adjusted signals from the sensors, the time
continuous parameters, the discrete metrics, the feedback
variables, and the feedback targets are stored in a memory after
each throw.
Example 4
Reduction of Work-Related Back Injury
[0103] It is widely documented that back injury due to occupational
tasks (e.g., muscle, tendon, or ligament strains or sprains) is a
significant socio-economical concern. For example, based on a
monograph from the National Institute for Occupational Safety and
Health (NIOSH), Monore Keyserling (American Industrial Hygiene
Association, 61: 39-50, 2000) reported that 32% of the injury and
illness cases involving days away from work resulted from
overexertion or repetitive motion. Moreover, 75% of these cases
were associated with manual materials handling (e.g., lifting or
pushing), and 13% resulted from repetitive motion (e.g., data entry
tasks or repetitive use of tools). While the actual risk factors
differ among occupational tasks, inappropriate posture and
execution of movement are almost always associated with increased
risks for back injury.
[0104] Although ideal posture and movement execution depend on the
task, some general biomechanical parameters associated with the
risks for back injury have been identified, such as the trunk
posture and movement, arm elevation, coordination between the
segments, muscle activation and fatigue, and frequency of the
repetition (Wrigley et al., Clinical Biomechanics 20: 254-263
(2005); Marras et al., Spine, 18,: 617-628 (1993)). The risks
associated with these parameters in isolation and with their
interactions are different from task to task. Therefore, this
Example is a representative embodiment of the invention where the
hardware used to measure, analyze, evaluate, and provide feedback
can be used for many different tasks without any significant
modification; only the algorithms to process the signals from the
sensors and the variables to control the feedback need to be
adjusted. In this Example, the invention is used to monitor and
provide real-time feedback to a subject during the execution of a
repetitive occupational task to reduce his or her risk for back
injury.
[0105] The Measurement Module consists of inertial measurement
units containing accelerometers and gyroscopes placed on the
pelvis, lower-trunk, upper-trunk, upper-arm, forearm, and head. In
addition, surface electromyography electrodes are placed on
important muscles of the trunk and arms, such as the longissimus,
iliocostalis, trapezius, and deltoid. For some particular tasks,
pressure outsoles, pressure mats fixed on the seat slip, or
pressure gloves are also included.
[0106] The Processing Module includes calibration routines to
identify the locations of the sensors on the body, align the
sensors with the segment frame, determine the maximum muscle
activations, and set the initial pressure conditions. Then the
Processing Module combines the signals from the sensors to obtain
specific continuous descriptive parameters. The parameters
quantifying the kinematics consist of the angles, angular
velocities, and angular accelerations of the pelvis, lower-trunk,
upper-trunk, upper-arm, forearm, and head segments in the three
anatomical planes (i.e., flexion, abduction, and rotation).
Continuous descriptive parameters for the angular movement of the
joints are also calculated, in terms of angles, angular velocities,
and angular accelerations. Based on the surface electromyography
signals and/or pressure sensors, kinematic continuous descriptive
parameters of the segments are obtained. In addition, discrete
metrics such as the frequency of the repetition are determined.
[0107] This embodiment of the invention provides real-time feedback
during the execution of the movement (similar to Example 2); as
such, the values of the continuous parameters at each time sample
are considered as discrete metrics and constitute the input of the
comparison model. Depending of the task under analysis, the
comparison model can simply compare the metrics with target values.
In terms of a lifting task, the level of risk is related to the
amount of rotation of the upper-trunk relative to the pelvis: a
large rotation towards the right, a large rotation towards the
left, or a large overall amplitude of rotation are risk factors for
back injury. Alternatively, the comparison model can use a data
manipulation algorithm, such as a neural network or a principal
component analysis. For example, while sitting at a computer, the
flexion between the pelvis and the lower-trunk, the flexion between
the lower-trunk and the upper-trunk, the flexion between the
upper-trunk and the head, the elevation of the upper-arms, the
intensity of the surface electromyography signals of the erector
spinae muscles, and the pressure recorded by the mat on the chair
can be analyzed by a neural network previously trained to estimate
the overall adequacy of the posture. For this task, an awkward
posture is associated with a higher risk of back injury.
[0108] The Feedback and Display Module consists of true immediate
feedback (similar to Example 2), meaning that the subject receives
feedback during the movement and he or she can continuously adjust
how he or she is completing the occupational task. Feedback given
during the execution of the movement is especially beneficial for
reduction of back injury during occupational activities because it
does not require the subject to stop after every couple of
repetitions to look at his or her risk evaluation. Instead, the
subject can perform his or her repetitive task normally, and if the
execution is not appropriate, a feedback signal is activated. The
feedback provided may be a combination of a vibration device and
auditory device. Overall, training a subject in the proper
technique for reducing the risk for back injury provides another
excellent example of how the present invention may be used for
immediate measurement, analysis, and feedback in order to evaluate
risk and prevent injuries.
[0109] For the Recording Module of this embodiment of the
invention, the raw and adjusted signals from the sensors, the time
continuous parameters, the discrete metrics, the feedback
variables, and the feedback targets are stored in a memory for each
time sample.
[0110] The preceding merely illustrates the principles of the
invention. It will be appreciated that those skilled in the art
will be able to devise various arrangements which, although not
explicitly described or shown herein, embody the principles of the
invention and are included within its spirit and scope.
Furthermore, all examples and conditional language recited herein
are principally intended to aid the reader in understanding the
principles of the invention and the concepts contributed by the
inventors to furthering the art, and are to be construed as being
without limitation to such specifically recited examples and
conditions. Moreover, all statements herein reciting principles,
aspects, and embodiments of the invention as well as specific
examples thereof, are intended to encompass both structural and
functional equivalents. Additionally, it is intended that such
equivalents include both currently known equivalents and
equivalents developed in the future, i.e., any elements developed
that perform the same function, regardless of structure. The scope
of the present invention, therefore, is not intended to be limited
to the exemplary aspects shown and described herein. Rather, the
scope and spirit of present invention is embodied by the appended
claims. In the claims that follow, unless the term "means" is used,
none of the features or elements recited therein should be
construed as means-plus-function limitations pursuant to 35 U.S.C.
.sctn.112, 6.
* * * * *