U.S. patent application number 14/273010 was filed with the patent office on 2014-11-13 for system and methods for measuring propulsive force during ambulation and providing real-time feedback.
The applicant listed for this patent is The Regents of the University of Colorado, a body corporate. Invention is credited to Jason R. Franz, Rodger Kram.
Application Number | 20140336003 14/273010 |
Document ID | / |
Family ID | 51865196 |
Filed Date | 2014-11-13 |
United States Patent
Application |
20140336003 |
Kind Code |
A1 |
Franz; Jason R. ; et
al. |
November 13, 2014 |
SYSTEM AND METHODS FOR MEASURING PROPULSIVE FORCE DURING AMBULATION
AND PROVIDING REAL-TIME FEEDBACK
Abstract
The invention measures propulsive force of an ambulating subject
to provide real-time feedback, which may be used for clinical
assessment or rehabilitation/training such as that related to
walking ability, or any other form of ambulation. Subjects with
propulsive deficits have a considerable and underutilized
propulsive reserve available during level ambulation. The invention
uses real-time propulsive feedback as a therapeutic strategy to
encourage a subject to access the propulsive reserve and improve
forward propulsion during ambulation.
Inventors: |
Franz; Jason R.; (Madison,
WI) ; Kram; Rodger; (Nederland, CO) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
The Regents of the University of Colorado, a body
corporate |
Denver |
CO |
US |
|
|
Family ID: |
51865196 |
Appl. No.: |
14/273010 |
Filed: |
May 8, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61820743 |
May 8, 2013 |
|
|
|
Current U.S.
Class: |
482/8 |
Current CPC
Class: |
A63B 2071/0625 20130101;
A63B 2220/833 20130101; A63B 2220/806 20130101; A63B 22/0235
20130101; A63B 2225/50 20130101; G09B 19/0038 20130101; A63B
2220/836 20130101; A63B 2071/0666 20130101; A63B 71/0686 20130101;
A61B 5/112 20130101; A63B 2220/52 20130101; A61B 5/0488 20130101;
A63B 71/0622 20130101; A63B 2022/0092 20130101; A61B 5/486
20130101; A61B 5/1038 20130101; A63B 2225/20 20130101; A63B 2225/54
20130101 |
Class at
Publication: |
482/8 |
International
Class: |
A63B 22/02 20060101
A63B022/02; A63B 24/00 20060101 A63B024/00 |
Claims
1. A propulsion system for measuring propulsive force and providing
feedback real-time to improve ambulation of a subject, comprising:
an ambulation device that facilitates the subject walking, the
ambulation device further comprising a force detection device that
measures ground reaction force data as the subject walks on the
ambulation device and an activity detection device that measures
electromyographic signal data from one or more muscles as the
subject walks on the ambulation device; and a computer device
including a processor and a user interface, the processor receives
and analyzes real-time the ground reaction force data and the
electromyographic signal data to produce a feedback output
displayed on the user interface.
2. The propulsion system according to claim 1 wherein the
ambulation device is a motorized treadmill.
3. The propulsion system according to claim 1 wherein the force
detection device is a force platform or force transducers.
4. The propulsion system according to claim 1 wherein the activity
detection device are electrodes with differential amplifiers.
5. The propulsion system according to claim 1 wherein the one or
more muscles are the soleus muscles of the legs.
6. The propulsion system according to claim 1 wherein the one or
more muscles are the gastrocnemius muscles of the legs.
7. The propulsion system according to claim 1 wherein the feedback
output is a graphic illustration or an auditory cue of one or more
selected from the group comprising: the ground reaction force data,
the electromyographic signal data, and stride frequency.
8. The propulsion system according to claim 1 wherein the processor
analyzes real-time the ground reaction force data to calculate a
propulsive peak force or propulsive impulse from an
anterior-posterior ground reaction force.
9. The propulsion system according to claim 1 wherein the processor
analyzes real-time the electromyographic signal data to calculate a
mean push-off electromyographic signal.
10. A method for measuring propulsive force and providing feedback
real-time to improve ambulation of a subject, comprising the steps
of: providing an ambulation device to facilitate the subject
walking, using a force detection device to measure ground reaction
force data as the subject walks on the ambulation device; utilizing
an activity detection device to measure electromyographic signal
data from one or more muscles as the subject walks on the
ambulation device; analyzing real-time by a processor the ground
reaction force data and the electromyographic signal data to
produce a feedback output; and communicating the feedback output on
a user interface.
11. The method according to claim 10 wherein the analyzing step
further comprises the step of calculating a propulsive peak or a
propulsive impulse of an anterior-posterior ground reaction
force.
12. The method according to claim 10 wherein the analyzing step
further comprises the step of computing a mean push-off
electromyographic signal.
13. The method according to claim 10 wherein the one or more
muscles are the soleus muscles of the legs.
14. The method according to claim 10 wherein the one or more
muscles are the gastrocnemius muscles of the legs.
15. The method according to claim 10 wherein the communicating step
further comprises the step of displaying a graphic illustration of
one or more selected from the group comprising: the ground reaction
force data, the electromyographic signal data, and a stride
frequency.
16. The method according to claim 10 wherein the communicating step
further comprises the step of sounding an auditory cue of one or
more selected from the group comprising: the ground reaction force
data, the electromyographic signal data, and a stride frequency.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. provisional
application 61/820,743 filed May 8, 2013, which is incorporated by
reference herein in its entirety.
FIELD OF THE INVENTION
[0002] The invention relates generally to measuring and using
propulsive forces in rehabilitation or gait training. More
specifically, the invention comprises a system and methods that
provide real-time output, or feedback, of the propulsive force
resultant from an ambulating subject. The feedback may be used for
clinical assessment and/or rehabilitation such as that related to
ambulation.
BACKGROUND OF THE INVENTION
[0003] Reduced propulsive function during the push-off phase when
ambulating plays a central role in the deterioration of ambulation
ability. For example, an injured person may have difficulty walking
at the same speed as before the injury. Specifically, a patient may
have difficulty walking after stroke, amputation, or joint
replacement. A disabled person may always walk more slowly than
others of the same physical strength. Also, an elderly person may
walk at a slow speed due to age or fatigue. Furthermore, all of
these subjects may have even greater difficulty walking or running
uphill.
[0004] Compromised ambulation ability ultimately predicts health
and survival. For example, among older adults, compromised walking
ability is ultimately predictive of health problems and reduced
survival. The prevalence of walking ability limitations among old
adults is profound: 17%, 28% and 47% of people aged 65-74, 75-84,
and 85+ years, respectively, report that walking difficulties
interfere with their daily activities.
[0005] Considerable research has demonstrated that a reduction in
propulsion during the push-off phase of walking, even in otherwise
healthy old adults, plays a central role in the deterioration of
walking ability with age. Specifically, old adults exert smaller
peak propulsive force, perform less trailing leg positive
mechanical work, and generate less ankle power than young adults
walking at the same speed. Eventually, the propulsive deficits of
old adults may lead to slower walking speeds on the level,
inability to walk uphill, and an associated loss of independence in
the community. It is typically presumed that sarcopenia and leg
muscle weakness are responsible for these changes. Such a
presumption has understandably led to the widespread prescription
of muscle strengthening programs for old adults.
[0006] While these programs improve muscle strength and mitigate
sarcopenia, strengthening alone generally fails to improve the
walking ability of old adults. Those outcomes suggest that factors
other than sarcopenia bring the propulsive deficits of older
adults. Furthermore, some metrics of propulsion such as ankle power
generation, require complex calculations that are impractical to
implement using real-time feedback.
[0007] There is a need for real-time feedback of propulsive forces
to strategically tap into a subject's underutilized, but
considerable, propulsive reserve during level ambulation to improve
forward propulsion, which may be used in the development of more
effective rehabilitative and prehabilitative therapies in order to
improve ambulation in subjects. The invention satisfies this
need.
SUMMARY OF THE INVENTION
[0008] For purposes of this application, the invention is discussed
in reference to improving ambulatory activity of subjects that are
human, but the discussion is merely exemplary. The invention is
applicable to a wide range of subjects including animals. In
addition, the term "ambulate" refers to any locomotion, such as
walking, running, or even moving with crutches. Old subjects who
exhibit diminished forward propulsion when ambulating over level
ground at a comfortable speed can both voluntarily ambulate faster
and ambulate uphill evidencing an underutilized propulsive reserve
available during ambulation. As an example, compared to level
walking, old subjects increase their peak propulsive ground
reaction forces (GRFs), trailing leg positive mechanical work, and
average ankle power generation during push-off by 69%, 115%, and
44% to walk uphill, respectively.
[0009] According to the invention, real-time propulsive feedback in
the form of metrics related to ground reaction forces (GRFs) and
ankle extensor (plantar flexor) muscle activities are used to
exhibit that old subjects have an underutilized propulsive reserve.
Old subjects can increase their peak propulsive GRFs and ankle
extensor muscle activities during level ambulation. Real-time
feedback elicits peak propulsive GRFs comparable to young adults.
Forward propulsion during ambulation predictably decreases as
people take progressively shorter steps at the same speed and, for
many reasons, old subjects typically choose shorter steps. Thus,
auditory cues such as those from a metronome may be used to
encourage old subjects to take slower, longer steps than normal to
increase forward propulsion.
[0010] In one embodiment, the invention is directed to a propulsion
system for measuring propulsive forces and providing feedback in
real-time to improve ambulation of a subject. The system includes
an ambulation device such as a motorized treadmill, and a computer
device. The ambulation device facilitates a subject ambulating. The
ambulation device further comprises a force detection device and a
muscle activity detection device. The force detection device
measures ground reaction force data as the subject ambulates on the
ambulation device. The activity detection device measures
electromyographic signal data from one or more muscles, such as the
soleus muscle or gastrocnemius muscle, as the subject ambulates on
the ambulation device. A computer device receives and analyzes in
real-time the ground reaction force data and the electromyographic
signal data. The computer may analyze real-time the ground reaction
forces data to calculate a propulsive peak or a propulsive impulse
from an anterior-posterior ground reaction force or the
electromyographic signal data to compute a mean push-off
electromyographic signal. The computer device produces a feedback
output displayed on the user interface. Feedback output may
include, for example, a graphic illustration or an auditory cue of
the ground reaction force data, the electromyographic signal data,
or stride frequency. The feedback allows the subject to adjust its
ambulation, for example, to take slower, longer steps, to utilize
the propulsive reserve available to ultimately improve the forward
propulsion of the subject.
[0011] Certain examples of the ambulation device include a
treadmill, moving walkway or sidewalk. Certain examples of the
force detection device include a force platform, one or more force
transducers, a scale apparatus, or custom insoles of footwear.
Certain examples of the activity detection device include a cuff
with a sensor, an electrode equipped with an amplifier such as a
differential amplifier, or a camera.
[0012] Feedback regarding the performance of a subject's activity
may be communicated, for example through a user interface. For
purposes of this application, an interface is any system or
component by which a subject can receive visual, aural, or other
sensory information including vibration or other tactile
information. Examples of user interfaces include a television, a
monitor, a screen, a touchscreen, a wearable visual user interface
such as Google Glass.TM., and any other desktop, portable, or
mobile device. It is also contemplated that the user interface may
allow a subject to enter information about their health or their
ambulatory activities. In other embodiments, information about the
ambulatory activities may be obtained by a computer device or
directly from an ambulation device.
[0013] According to the invention, real-time feedback of propulsive
effort may supplant the distal to proximal redistribution of muscle
recruitment, thereby enabling old subjects to increase their
forward propulsion.
[0014] According to the invention, three different approaches to
increase propulsion in old subjects are considered: force feedback,
EMG feedback, and auditory stride frequency cueing.
[0015] One objective of certain embodiments of the invention is to
measure the propulsive effort being made by a person that is
ambulating and communicate that effort as real-time feedback in
order to enhance the forward propulsion and thereby the ambulatory
activity of the person.
[0016] Another objective of certain embodiments of the invention is
to provide information regarding the propulsive effort being made
by a person while ambulating in a form that is easy to understand
and thereby permit the person to make real-time corrections and
increase their forward propulsion.
[0017] An additional objective of the invention is to provide
information to a person during ambulation such that the person can
improve his or her strength, health, and independence.
[0018] One advantage of certain embodiments of the invention is
that through the use of the ambulation propulsion system a person
may improve their overall ambulation, including for example,
walking or running speed.
[0019] Another advantage of certain embodiments of the invention is
that through the use of the ambulation propulsion system a person
may improve their uphill ambulation ability.
[0020] Another advantage of certain embodiments of the invention is
that through the use of the system and methods, feedback regarding
propulsive force or other aspect of ambulation provided to the user
may result in improved speed while walking or running.
[0021] Another advantage of certain embodiments of the invention is
that through the use of the system and methods, feedback regarding
propulsion force or other aspect of ambulation provided to the
subject may result in ambulation becoming easier, such that the
person consumes less oxygen while walking.
[0022] The invention and its attributes and advantages will be
further understood and appreciated with reference to the detailed
description below of presently contemplated embodiments, taken in
conjunction with the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0023] The preferred embodiments of the invention will be described
in conjunction with the appended drawings provided to illustrate
and not to the limit the invention, where like designations denote
like elements, and in which:
[0024] FIG. 1 is a block diagram of one embodiment of a propulsion
system according to the invention.
[0025] FIG. 2 is a flow chart of one embodiment of a propulsion
system method according to the invention.
[0026] FIG. 3 is a schematic of a subject and the propulsion system
according to the invention.
[0027] FIG. 4 is a graph illustrating mean peak propulsive force
according to one embodiment of the invention.
[0028] FIG. 5 is a graph illustrating push-off muscle activity
according to one embodiment of the invention.
[0029] FIG. 6 is a graph illustrating mean stance phase ground
reaction force (GRF) profiles according to one embodiment of the
invention.
[0030] FIG. 7 is a graph illustrating mean stance phase medial
gastrocnemius and soleus activity according to one embodiment of
the invention.
[0031] FIG. 8 is a graph illustrating post-feedback retention
according to one embodiment of the invention.
[0032] FIG. 9 illustrates an embodiment of a computer device
according to the invention.
[0033] FIG. 10 illustrates an exemplary cloud computing system
according to the invention.
DETAILED DESCRIPTION
[0034] One embodiment the invention is directed to a propulsion
system 100 as shown in FIG. 1. The propulsion system 100 includes
an ambulation device 102 and a computer device 150. The ambulation
device 102 further comprises a force detection device 104 and an
activity detection device 106. Although the invention is described
below with respect to ambulation in the form of walking, any
locomotion is envisioned such as running or even moving with
crutches.
[0035] The ambulation device 102 is a device that facilitates a
subject walking on, for example a motorized treadmill. The
ambulation device 102 includes a force detection device 104 and an
activity detection device 106. The force detection device 104
measures three-dimensional ground reaction force (GRFs) data as the
subjects walks on the ambulation device 102.
[0036] One embodiment of a force detection device 104 is a force
platform. The activity detection device 106 is a wearable device
that measures electromyographic (EMG) signal data produced by
muscles as the subject walks on the ambulation device.
[0037] One embodiment of an activity detection device 106 is an
electrode equipped with a differential amplifier. The activity
detection device 106 may be positioned on leg muscles of the
subject such as the soleus (SOL) and medial gastrocnemius (MG).
[0038] A computer device 150 is operably linked with the ambulation
device 102, for example, electronically (wired) or wirelessly
(e.g., using Bluetooth, ZigBee, radio signal, Wireless USB, RFID,
IR, Wi-Fi, local area networks, wide area networks, or other
wireless systems known in the art).
[0039] Specifically, the computer device 150 receives the
measurements of the GRF data and EMG signal data from the force
detection device 104 and activity detection device 106,
respectively. The computer device 150 receives the GRF data and EMG
signal data in real-time and further analyzes the data real-time.
One analysis of the data uses an algorithm to calculate the
propulsive peak of the anterior-posterior GRF and/or the mean
push-off EMG. It is also envisioned that the algorithm may be used
to calculate a propulsive impulse of the anterior-posterior
GRF.
[0040] The computer device produces a feedback output displayed on
the user interface. Feedback output may include, for example, a
graphic illustration or an auditory cue of the ground reaction
force data, the electromyographic signal data, or stride
frequency.
[0041] FIG. 2 illustrates the steps of a propulsion system method
170 according to the invention. The method is directed to measuring
propulsive force and providing feedback real-time to improve
ambulation of a subject. An ambulation device is provided at step
171 that facilitates a subject walking. At step 173 a force
detection device is used to measure ground reaction force data as
the subject walks on the ambulation device. At step 175, an
activity detection device is utilized to measure electromyographic
signal data from one or more muscles, such as the soleus muscle or
the medial gastrocnemius muscle, as the subject walks on the
ambulation device. The ground reaction force data and the
electromyographic signal data are analyzed real-time at step 177.
The data analysis at step 177 may include calculation a propulsive
peak of an anterior-posterior ground reaction force or computing a
mean push-off electromyographic signal. The real-time analysis
provides a feedback output that is communicated such as through a
display device or speakers to the subject at step 179. For example,
the feedback output may be displayed as a graphic illustration or
an auditory cue. The feedback output may include more ground
reaction force data, the electromyographic signal data, and a
stride frequency. The feedback output allows the subject to adjust
its ambulation, for example, to take slower, longer steps, to
utilize the propulsive reserve available to ultimately improve the
forward propulsion of the subject.
[0042] FIG. 3 illustrates a schematic of a subject and the
propulsion system 200 according to the invention. After preparing
the skin with fine sandpaper and alcohol, single differential
electrodes 206 with wireless preamplifiers are positioned over old
subjects' right leg soleus and bilaterally over their medial
gastrocnemius (MG), and sampled at 2000 Hz. Electrode positions and
signal quality may be verified by visual inspecting the
electromyographic (EMG) signals while a subject performs standing
calf raises. A force platform 204 mounted under the right side of a
custom dual-belt motorized treadmill 202 records the
three-dimensional ground reaction forces (GRF) for each subject's
right leg at 1000 Hz. To synchronize the data, the GRF signals are
delayed to account for the 300 ms transmission delay inherent to
the wireless single preamplifiers of the differential electrodes
206.
[0043] An algorithm is used to continuously process and monitor the
GRF data and EMG signal data. The script low-pass filters the GRF
signals (fourth-order Butterworth, 20 Hz cut-off) and demeans,
band-pass filters (20-450 Hz), and full-wave rectifies the EMG
signals. The algorithm relies on the stance phase timing provided
by the force platform 204 mounted under the right belt of the
treadmill 202. Accordingly, the script extracts the data from each
right leg stance phase in real-time, based on a 20 N vertical GRF
threshold. At the instant of each toe-off, the real-time algorithm
calculates and stores: 1) the propulsive peak of the
anterior-posterior GRF and 2) the mean push-off MG activity (i.e.,
that over the second half of stance) as show by 225 in FIG. 3.
Although the algorithm uses MG activity based on the fact that the
gastrocnemius muscle is considerably involved in forward
propulsion, it is also contemplated that EMG data from both the MG
and SOL due to their combined contribution to generating ankle
power during push-off may be utilized.
[0044] Finally, a computer device 250 positioned in front of the
treadmill 202 displays points each corresponding to a n-stride
average of those measurements (i.e., one dot appears every n
strides, scrolling from right to left). Here, "n" represents an
integer that can be varied according to the needs of the
application. To preserve the ordinate scaling across condition on
the user interface of the computer device 250, the algorithm
considers the magnitude, variability, and target percent increases
of each measure. Therefore, the scaling of each subject's feedback
data on the user interface can be normalized by setting the
ordinate range from the minimum value during normal walking to the
largest target plus half the range observed during normal
walking.
[0045] Three different approaches to increase propulsion in old
adults are contemplated: force feedback, EMG feedback, and auditory
stride frequency cueing.
[0046] In one embodiment of the invention performed, referred to as
"Normal 1 trial", subjects walk normally for five minutes at 1.25
m/s on the treadmill 202 to allow their movement patterns to
stabilize. GRF of old and young subjects is collected and EMG data
of old subjects are collected during the final 30 seconds of the 5
minute trial. Young subjects walking normally are tested only to
provide reference GRF values. For older subjects, the data from
Normal 1 trial is used to calculate targets for the first pair of
visual feedback trials--force or EMG, depending on a randomized
trial order. Prior to starting the visual feedback trials, the gait
cycle is described to each subject in which the late stance phase
is emphasized. The late stance phase occurs during which the ankle
extends and the muscles of the leg generate a propulsive force on
the ground. Each subject is further instructed to more vigorously
extend their ankles and push their legs backwards during late
stance without excessively vaulting themselves vertically.
[0047] For each visual feedback trial, the subjects are asked to
match a target line set to 20% and 40% greater than their normal
walking for two minutes denoted by: force--F20 and F40 or
EMG--EMG20 and EMG40.
[0048] To determine whether subjects can maintain a more vigorous
push-off after removing visual feedback, the visual feedback is
turned off and the subjects are requested to maintain the same
exaggerated push-off for one minute. Some subjects can retain a
more vigorous push-off for several minutes even after returning to
normal walking. After resting for five minutes, the subjects then
walk normally on the motorized treadmill for one minute, referred
to as "Normal 2 trial". The Normal 2 trial is used to calculate
targets for an alternate pair of visual feedback trials.
[0049] In other trials, in order to promote longer steps, the
subjects are asked to walk for one minute while matching their
steps to the beat of an audio metronome set to step frequencies 10%
and 20% slower than normal walking denoted by SF10 and SF20,
respectively. The metronome is subsequently turned off and the
subjects asked to maintain that same step frequency for one
minute.
[0050] An algorithm, such as a custom script, analyzes the data and
calculates stride-averaged values over the final minute of each
normal walking trial, the second minute of each visual feedback
trial, and the final 30 seconds of each auditory cueing trial.
Starting with the first stride after the visual feedback or
auditory cueing is removed, stride-by-stride values of peak
propulsive force are calculated, along with push-off MG activity,
and stride time during the final minute of the F20/F40,
EMG20/EMG40, and SF10/SF20 trials, respectively. Average values are
reported for each stride up to the fewest number of strides taken
by a subject during this minute, which is approximately 40
strides.
[0051] After the data are collected, the individual limbs method
(ILM) is used to calculate the instantaneous rates of mechanical
work performed by the legs for each condition from the
stride-averaged GRF data. The first calculation is the velocity of
the body's center of mass (CoM) by integrating the GRF with respect
to time. The next calculation is the mechanical work rates over an
average stride as the dot product of the three-dimensional right
leg GRF and CoM velocity.
[0052] Evaluating the distribution of all measurements using a
Shapiro-Wilk's test, all outcome measures are normally distributed
except for mean push-off MG activity during trials with visual EMG
feedback (P<0.01 for EMG20 and EMG 40). The primary outcome
measures (peak propulsive GRF and mean push-off MG activity) do not
differ between the Normal 1 trial and the Normal 2 trial (P=0.109
and P=0.083, respectively). Because subjects complete the Normal 2
trail after their first round of visual feedback, the Normal 1
trial is used as the baseline condition for all comparisons to
avoid any possible confounding factors. It is also confirmed that
subjects respond to force and EMG feedback symmetrically.
[0053] FIG. 4 is a graph 300 illustrating mean peak propulsive
force. As shown in FIG. 4, the graph 300 includes bars 302, 304,
306, 308. Bar 302 illustrates old subjects walking normally. Bar
304 illustrates peak propulsive GRF when the subject is provided
with visual force feedback. Bar 306 illustrates peak propulsive GRF
when the subject is provided with EMG feedback, and bar 308
illustrates peak propulsive GRF when the subject is provided with
stride frequency cueing. FIG. 4 also illustrates the peak
propulsive force of younger subjects walking normally.
[0054] FIG. 5 is a graph 350 illustrating push-off muscle activity.
As shown in FIG. 5, the graph 350 includes bars 352, 354, 356, 358.
As shown in FIG. 5, bar 352 illustrates old subjects walking
normally. Bar 354 illustrates push-off muscle activity when the
subject is provided with visual force feedback. Bar 356 illustrates
push-off muscle activity when the subject is provided with EMG
feedback, and bar 358 illustrates push-off muscle activity when the
subject is provided with stride frequency cueing.
[0055] As can be seen in FIG. 4, old subjects walking normally
exerted 12.5% smaller peak propulsive GRFs than young adults
(P<0.01). However, when provided with real-time propulsive
feedback, old subjects significantly increased their propulsive
GRFs 304 (FIG. 4) and push-off muscle activities 354 (FIG. 5).
Force feedback elicited propulsive GRFs that are either equal to or
10.5% greater than those of young adults walking normally (F20,
P=0.87; F40, P=0.02). Those conditions also elicited significant
increases in push-off muscle activity (FIG. 5). With EMG feedback,
old subjects significantly increased their push-off muscle
activities but without increasing their propulsive GRFs (FIG. 5).
Force feedback also elicited greater mechanical power generation to
propel the body's CoM forward during the push-off phase of walking
and to raise the CoM vertically during single support.
[0056] FIG. 6 illustrates the mean stance phase ground reaction
force (GRF) profiles for old subjects walking with visual force and
EMG feedback and auditory stride frequency cueing. FIG. 7
illustrates the mean stance phase gastrocnemius and soleus
activity, or EMG profiles for old subjects walking with visual
force and EMG feedback and auditory stride frequency cueing. FIG. 8
is a graph illustrating post-feedback retention. Specifically, FIG.
8 shows mean stride-by-stride values of peak propulsive force,
push-off gastrocnemius activity, and stride time during the minute
after the feedback--visual or auditory cueing--is removed. The
horizontal dashed lines in FIG. 8 indicate target percent increase.
The results for force feedback, EMG feedback, and stride frequency
cueing are shown in FIG. 6, FIG. 7, and FIG. 8 for trials directed
to the subject matching a target line set to 20% and 40% greater
than its normal walking for two minutes denoted by: force--F20 and
F40 and EMG--EMG20 and EMG40, in addition to the subject matching
its steps to the beat of an audio metronome set to step frequencies
10% and 20% slower than normal walking denoted by SF10 and
SF20.
[0057] Likely because both muscles are involved in forward
propulsion, feedback of gastrocnemius activity elicited similar
increases in soleus muscle activity during push-off (FIG. 7). Old
adults generally increased their propulsive function with force and
EMG feedback but they did not quite reach the 20% and 40% targets.
On average, old subjects increased their propulsive GRF by 15% and
26% for F20 and F40 and their push-off MG activity by 19% and 30%
for EMG20 and EMG40, respectively. Moreover, subjects can maintain
this more vigorous push-off for at least 40 strides after force
feedback is removed (FIG. 8A) or EMG (FIG. 8B) feedback. Only for
F40 did subjects show a significant decrease in stride-by-stride
propulsive forces after visual feedback is removed (P=0.03).
[0058] Auditory stride frequency cueing elicited smaller increases
in propulsive GRFs and push-off muscle activities in old adults
than walking with feedback of those measures directly (FIG. 4, FIG.
5). Old subjects walked with 8% (P<0.01) and 23% (P<0.01)
slower, longer steps than normal for SF10 and SF20, respectively.
Similarly, step times are 6% (P=0.01) and 15% (P<0.01) slower
than normal for F20 and F40, respectively.
[0059] The invention supports that old subjects with propulsive
deficits (compared to young subjects) actually have a considerable
and underutilized propulsive reserve available during level
walking. Further, real-time visual feedback of propulsive effort
can effectively call upon this reserve. The subjects are able to
significantly and dramatically increase their peak propulsive GRFs
and ankle extensor muscle activities when provided with real-time
force and EMG feedback compared to normal walking. Moreover,
real-time force feedback in old subjects elicited peak propulsive
GRFs that were equal to and even greater than those of young
subjects. Thus, old subjects with propulsive deficits are not
explicitly limited in their capacity to increase forward propulsion
during level walking. To the contrary, the subjects have a reserve
of at least 26% for exerting greater propulsive GRFs and 49% for
increasing ankle extensor muscle recruitment. Remarkably, when
provided with feedback, healthy and active old subjects can walk
with as vigorous a push-off as young subjects, but do not naturally
do so.
[0060] Determining whether force or EMG feedback is more effective
at improving the forward propulsion of old subjects, it is noted
that the target 20% and 40% increases for propulsive force do not
correspond to equal increases in push-off EMG. Force feedback
requires a considerably more vigorous push-off than the same target
percent increase in gastrocnemius activity using EMG feedback. Not
surprisingly, asking subjects to push-off more vigorously by
increasing MG activity also elicited similar increases in SOL
activity. However, while EMG feedback did elicit significantly
greater push-off muscle activities in old subjects, not even the
40% target increase in EMG elicited a significant increase in peak
propulsive forces or mechanical power generation. Although the
real-time propulsive force feedback may more directly and
effectively encourage old subjects to utilize their propulsive
reserve, both real-time EMG feedback and real-time stride frequency
cueing are also valuable.
[0061] The invention attempts to use real-time feedback to
encourage old subjects to increase their forward propulsion during
walking. Old subjects can maintain a more vigorous push-off for at
least 40 strides after visual feedback is removed. Although the old
subject subjects may have consumed oxygen at a faster rate while
walking in the novel way elicited by propulsive feedback compared
to walking normally, the characteristic propulsive mechanics of old
subjects may explain why they consume .about.20% more metabolic
energy than young subjects walking normally. Thus, propulsive
feedback training may both improve forward propulsion in old
subjects and reduce their metabolic cost.
[0062] Finally, sarcopenia and leg muscle weakness may more
explicitly limit propulsive GRFs and ankle power generation in
sedentary and/or frail old subjects. While resistance training in
old subjects can improve their muscle strength and mitigate
sarcopenia, strengthening alone generally fails to improve their
walking ability. Thus, frail and/or sedentary old subjects may
benefit most from leg muscle strengthening to increase their
propulsive capacity combined with propulsive feedback training to
encourage neural utilization of that capacity.
[0063] FIG. 9 illustrates an exemplary computer device 150 that may
be used to implement the methods according to the invention. One or
more computer devices 150 may carry out the methods presented
herein as computer code.
[0064] Computer device 150 includes a user interface 152 connected
to communication infrastructure 153--such as a bus--, which
forwards data such as graphics, text, and information, from the
communication infrastructure 153 or from a frame buffer (not shown)
to other components of the computer device 150. The user interface
152 may be, for example, a keyboard, touch screen, joystick,
trackball, mouse, monitor, speaker, printer, wearable visual user
interface such as Google Glass.TM., any other computer peripheral
device, or any combination thereof, capable of entering and/or
viewing data.
[0065] Computer device 152 includes one or more processors 154,
which may be a special purpose or a general-purpose digital signal
processor that processes certain information. Computer device 150
also includes a main memory 155, for example random access memory
(RAM), read-only memory (ROM), mass storage device, or any
combination thereof. Computer device 150 may also include a
secondary memory 156 such as a hard disk unit 157, a removable
storage unit 158, or any combination thereof. Computer device 150
may also include a communication interface 159, for example, a
modem, a network interface (such as an Ethernet card or Ethernet
cable), a communication port, a PCMCIA slot and card, wired or
wireless systems (such as Wi-Fi, Bluetooth, Infrared), local area
networks, wide area networks, intranets, etc.
[0066] It is contemplated that the main memory 155, secondary
memory 156, communication interface 159, or a combination thereof,
function as a computer usable storage medium, otherwise referred to
as a computer readable storage medium, to store and/or access
computer software including computer instructions. For example,
computer programs or other instructions may be loaded into the
computer device 150 such as through a removable storage device, for
example, a ZIP disk, magnetic tape, portable flash drive, optical
disk such as a CD or DVD or Blu-ray, Micro-Electro-Mechanical
Systems (MEMS), nanotechnological apparatus. Specifically, computer
software including computer instructions may be transferred from
the removable storage unit 158 or hard disc unit 157 to the
secondary memory 156 or through the communication infrastructure
153 to the main memory 155 of the computer device 150.
[0067] Communication interface 159 allows software, instructions
and data to be transferred between the computer device 150 and
external devices or external networks. Software, instructions,
and/or data transferred by the communication interface 159 are
typically in the form of signals that may be electronic,
electromagnetic, optical or other signals capable of being sent and
received by the communication interface 159. Signals may be sent
and received using wire or cable, fiber optics, a phone line, a
cellular phone link, a Radio Frequency (RF) link, wireless link, or
other communication channels.
[0068] Computer programs, when executed, enable the computer device
150, particularly the processor 154, to implement the methods of
the invention according to computer software including
instructions.
[0069] The computer device 150 described herein may perform any one
of, or any combination of, the steps of any of the methods
presented herein. It is also contemplated that the methods
according to the invention may be performed automatically, or may
be invoked by some form of manual intervention.
[0070] The computer device 150 of FIG. 9 is provided only for
purposes of illustration, such that the invention is not limited to
this specific embodiment. It is appreciated that a person skilled
in the relevant art knows how to program and implement the
invention using any computer device.
[0071] The computer device 150 may be a handheld device and include
any small-sized computer device including, for example, a personal
digital assistant (PDA), smart hand-held computing device, cellular
telephone, or a laptop or netbook computer, hand held console or
MP3 player, tablet, or similar hand held computer device, such as
an iPad.RTM., iPad Touch.RTM. or iPhone.RTM..
[0072] FIG. 10 illustrates an exemplary cloud computing system 300
that may be used to implement the methods according to the
invention. The cloud computing system 300 includes a plurality of
interconnected computing environments. The cloud computing system
300 utilizes the resources from various networks as a collective
virtual computer, where the services and applications can run
independently from a particular computer or server configuration
making hardware less important.
[0073] Specifically, the cloud computing system 300 includes at
least one client computer 302. The client computer 302 may be any
device through the use of which a distributed computing environment
may be accessed to perform the methods disclosed herein, for
example, a traditional computer, portable computer, mobile phone,
personal digital assistant, tablet to name a few. The client
computer 302 includes memory such as random access memory (RAM),
read-only memory (ROM), mass storage device, or any combination
thereof. The memory functions as a computer usable storage medium,
otherwise referred to as a computer readable storage medium, to
store and/or access computer software and/or instructions.
[0074] The client computer 302 also includes a communications
interface, for example, a modem, a network interface (such as an
Ethernet card), a communications port, a PCMCIA slot and card,
wired or wireless systems, etc. The communications interface allows
communication through transferred signals between the client
computer 302 and external devices including networks such as the
Internet 304 and cloud data center 306. Communication may be
implemented using wireless or wired capability such as cable, fiber
optics, a phone line, a cellular phone link, radio waves or other
communication channels.
[0075] The client computer 302 establishes communication with the
Internet 304--specifically to one or more servers--to, in turn,
establish communication with one or more cloud data centers 306. A
cloud data center 306 includes one or more networks 310a, 310b,
310c managed through a cloud management system 308. Each network
310a, 310b, 310c includes resource servers 312a, 312b, 312c,
respectively. Servers 312a, 312b, 312c permit access to a
collection of computing resources and components that can be
invoked to instantiate a virtual machine, process, or other
resource for a limited or defined duration. For example, one group
of resource servers can host and serve an operating system or
components thereof to deliver and instantiate a virtual machine.
Another group of resource servers can accept requests to host
computing cycles or processor time, to supply a defined level of
processing power for a virtual machine. A further group of resource
servers can host and serve applications to load on an instantiation
of a virtual machine, such as an email client, a browser
application, a messaging application, or other applications or
software.
[0076] The cloud management system 308 can comprise a dedicated or
centralized server and/or other software, hardware, and network
tools to communicate with one or more networks 310a, 310b, 310c,
such as the Internet or other public or private network, with all
sets of resource servers 312a, 312b, 312c. The cloud management
system 308 may be configured to query and identify the computing
resources and components managed by the set of resource servers
312a, 312b, 312c needed and available for use in the cloud data
center 306. Specifically, the cloud management system 308 may be
configured to identify the hardware resources and components such
as type and amount of processing power, type and amount of memory,
type and amount of storage, type and amount of network bandwidth
and the like, of the set of resource servers 312a, 312b, 312c
needed and available for use in the cloud data center 306.
Likewise, the cloud management system 308 can be configured to
identify the software resources and components, such as type of
Operating System (OS), application programs, and the like, of the
set of resource servers 312a, 312b, 312c needed and available for
use in the cloud data center 306.
[0077] The invention is also directed to computer products,
otherwise referred to as computer program products, to provide
software to the cloud computing system 300. Computer products store
software on any computer useable medium, known now or in the
future. Such software, when executed, may implement the methods
according to certain embodiments of the invention. Examples of
computer useable mediums include, but are not limited to, primary
storage devices (e.g., any type of random access memory), secondary
storage devices (e.g., hard drives, floppy disks, CD ROMS, ZIP
disks, tapes, magnetic storage devices, optical storage devices,
Micro-Electro-Mechanical Systems (MEMS), nanotechnological storage
device, etc.), and communication mediums (e.g., wired and wireless
communications networks, local area networks, wide area networks,
intranets, etc.). It is to be appreciated that the embodiments
described herein may be implemented using software, hardware,
firmware, or combinations thereof.
[0078] The cloud computing system 300 of FIG. 10 is provided only
for purposes of illustration and does not limit the invention to
this specific embodiment. It is appreciated that a person skilled
in the relevant art knows how to program and implement the
invention using any computer device or network architecture.
[0079] While the disclosure is susceptible to various modifications
and alternative forms, specific exemplary embodiments of the
invention have been shown by way of example in the drawings and
have been described in detail. It should be understood, however,
that there is no intent to limit the disclosure to the particular
embodiments disclosed, but on the contrary, the intention is to
cover all modifications, equivalents, and alternatives falling
within the scope of the disclosure as defined by the appended
claims.
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