U.S. patent application number 16/657982 was filed with the patent office on 2020-02-13 for wearable gait monitoring apparatus, systems, and related methods.
The applicant listed for this patent is Vision Service Plan. Invention is credited to Richard Chester Klosinski, JR., Meghan Kathleen Murphy, Jay William Sales, Matthew David Steen, Matthew Allen Workman.
Application Number | 20200046260 16/657982 |
Document ID | / |
Family ID | 55436366 |
Filed Date | 2020-02-13 |
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United States Patent
Application |
20200046260 |
Kind Code |
A1 |
Sales; Jay William ; et
al. |
February 13, 2020 |
WEARABLE GAIT MONITORING APPARATUS, SYSTEMS, AND RELATED
METHODS
Abstract
Eyewear or any other suitable wearable device may include one or
more sensors for monitoring the gait of an individual. Information
from the one or more sensors is analyzed to identify one or more
medical conditions associated with the individual or to assess an
individual's recovery from a particular injury or medical
procedure.
Inventors: |
Sales; Jay William;
(Sacramento, CA) ; Klosinski, JR.; Richard Chester;
(Sacramento, CA) ; Workman; Matthew Allen;
(Sacramento, CA) ; Murphy; Meghan Kathleen;
(Davis, CA) ; Steen; Matthew David; (Sacramento,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Vision Service Plan |
Rancho Cordova |
CA |
US |
|
|
Family ID: |
55436366 |
Appl. No.: |
16/657982 |
Filed: |
October 18, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14550406 |
Nov 21, 2014 |
10448867 |
|
|
16657982 |
|
|
|
|
62046406 |
Sep 5, 2014 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06K 9/00604 20130101;
A61B 5/6803 20130101; A61B 5/7278 20130101; A61B 5/7282 20130101;
G09B 5/00 20130101; A61B 5/0402 20130101; G06K 9/00597 20130101;
G08B 21/0476 20130101; A61B 5/1103 20130101; A61B 5/117 20130101;
A61B 5/0077 20130101; A61B 5/14552 20130101; G16H 40/63 20180101;
A61B 5/0816 20130101; A61B 5/4884 20130101; A61B 5/4076 20130101;
G06F 21/35 20130101; G06K 9/6201 20130101; A61B 5/0022 20130101;
A61B 5/4266 20130101; G09B 5/06 20130101; A61B 2562/0257 20130101;
A61B 2576/00 20130101; A61B 5/0476 20130101; A61B 7/04 20130101;
A61F 2/76 20130101; A61B 5/443 20130101; A61B 5/024 20130101; A61B
2560/0475 20130101; G09B 19/0092 20130101; A61F 2002/7695 20130101;
A63B 24/0062 20130101; A61B 5/112 20130101; A61B 5/1176 20130101;
G06K 9/00348 20130101; A61B 5/1116 20130101; A61B 2562/0219
20130101; A61B 5/1128 20130101; A61B 5/486 20130101; G08B 21/0423
20130101; A61B 5/1118 20130101; G16H 40/67 20180101; G06K 9/00664
20130101; G07C 9/37 20200101; G08B 21/02 20130101; A61B 2562/0223
20130101; G02C 11/10 20130101; H04L 63/0861 20130101; A61B 5/0205
20130101; A61B 5/1032 20130101; G06K 9/00617 20130101; A61B 3/112
20130101; A61B 5/165 20130101; G16H 20/40 20180101; A61B 5/0531
20130101; G08B 21/0461 20130101; A61B 5/7246 20130101; G16H 50/20
20180101; A61B 5/0002 20130101; G06F 19/3481 20130101; A61B 5/1114
20130101 |
International
Class: |
A61B 5/11 20060101
A61B005/11; A61B 5/00 20060101 A61B005/00; G06K 9/00 20060101
G06K009/00; G16H 40/63 20060101 G16H040/63; G16H 50/20 20060101
G16H050/20; A61B 5/117 20060101 A61B005/117; A61B 3/11 20060101
A61B003/11; A61B 5/0402 20060101 A61B005/0402; A61B 5/0476 20060101
A61B005/0476; A61B 5/103 20060101 A61B005/103; A61B 5/1171 20060101
A61B005/1171; A61B 5/16 20060101 A61B005/16; A61B 7/04 20060101
A61B007/04; G09B 5/00 20060101 G09B005/00; A61B 5/1455 20060101
A61B005/1455; G06K 9/62 20060101 G06K009/62; G08B 21/04 20060101
G08B021/04; A63B 24/00 20060101 A63B024/00; G09B 5/06 20060101
G09B005/06; G09B 19/00 20060101 G09B019/00; G06F 21/35 20060101
G06F021/35; G07C 9/00 20060101 G07C009/00; G08B 21/02 20060101
G08B021/02; H04L 29/06 20060101 H04L029/06; G16H 20/40 20060101
G16H020/40 |
Claims
1. A non-transitory computer-readable medium storing
computer-executable instructions for: receiving, at a gait server,
information obtained from at least one sensor worn adjacent the
individual's head; using, by the gait server, the information to
assess the gait of the individual; analyzing, by the gait server,
the assessed gait using regression analysis techniques to determine
whether the assessed gait includes one or more particular gait
patterns that are associated with a particular medical condition;
and in response to determining that the assessed gait includes the
one or more gait patterns, generating an alert that the individual
may have the particular medical condition.
2. The non-transitory computer-readable medium of claim 1, wherein
the at least one sensor is embedded into a pair of glasses worn by
the individual.
3. The non-transitory computer-readable medium of claim 2, wherein
the at least one sensor is a gyroscope.
4. The non-transitory computer-readable medium of claim 1, wherein
the step of using the information to assess the gait of the
individual comprises: using the information to assess one or more
movements of the individual's head as the individual ambulates; and
using the one or more movements of the individual's head to assess
the gait of the individual.
5. The non-transitory computer-readable medium of claim 1, wherein
the step of analyzing the assessed gait to determine whether the
assessed gait includes one or more particular gait patterns that
are associated with a particular medical condition comprises: using
the information to assess one or more movements of the individual's
head as the individual ambulates; and comparing the one or more
movements of the individual's head with one or more head movements
that are associated with the particular medical condition; and at
least partially in response to determining that the one or more
movements of the individual's head are at least similar to one or
more head movements that are associated with the particular medical
condition, determining that the assessed gait includes one or more
particular gait patterns that are associated with the particular
medical condition.
6. The non-transitory computer-readable medium of claim 1, wherein
the one or more gait patterns is foot drop.
7. The non-transitory computer-readable medium of claim 6, wherein
the particular medical condition is a medical condition selected
from a group consisting of: stroke, amyotrophic lateral sclerosis,
muscular dystrophy, Charcot Marie Tooth disease, multiple
sclerosis, cerebral palsy, hereditary spastic paraplegia, and
Friedrich's ataxia.
8. The non-transitory computer-readable medium of claim 1, wherein
the one or more gait patterns is propulsive gait.
9. The non-transitory computer-readable medium of claim 8, wherein
the particular medical condition is a medical condition selected
from a group consisting of: carbon monoxide poisoning, manganese
poisoning, and Parkinson's disease.
10. The non-transitory computer-readable medium of claim 1, wherein
the one or more gait patterns is waddling gait.
11. The non-transitory computer-readable medium of claim 10,
wherein the particular medical condition is a medical condition
selected from a group consisting of: congenital hip dysplasia,
muscular dystrophy, and spinal muscle atrophy.
12. The non-transitory computer-readable medium of claim 1, wherein
the step of analyzing the assessed gait to determine whether the
assessed gait includes one or more particular gait patterns that
are associated with a particular medical condition comprises:
comparing one or more particular gait patterns from the assessed
gait of the individual with the one or more gait patterns that are
associated with the particular medical condition; and in response
to determining that the one or more particular gait patterns are at
least substantially similar to the one or more gait patterns that
are associated with the particular medical condition, determining
that the assessed gait includes one or more particular gait
patterns that are associated with a particular medical
condition.
13. The non-transitory computer-readable medium of claim 12,
wherein the step of comparing one or more particular gait patterns
from the assessed gait of the individual with the one or more gait
patterns that are associated with the particular medical condition
comprises comparing one or more relative peaks in linear
acceleration associated with the assessed gait of the individual
with one or more relative peaks in linear acceleration of the one
or more gait patterns that are associated with the particular
medical condition.
14. A system for monitoring a gait of an individual, the system
comprising: a pair of glasses comprising means for determining gait
information to assess the gait of the individual, the gait
information comprising at least first gait information associated
with a first period of time and second gait information associated
with a second period of time; one or more processors operatively
coupled to the means for determining gait information; memory
operatively coupled to the one or more processors, wherein the
system comprises: means for analyzing the gait information to
determine whether the assessed gait includes one or more particular
gait patterns that are associated with a particular medical
condition; and means for, at least partially in response to
determining that the assessed gait includes the one or more gait
patterns, generating an alert that the individual may have the
particular medical condition.
15. The method of claim 14, wherein the means for determining gait
information comprises at least one sensor embedded into the glasses
worn by the individual.
16. The method of claim 15, wherein the first gait information and
the second gait information comprises information corresponding to
one or more movements of the individual's head as the individual
ambulates, and wherein the means for analyzing the gait information
to determine whether the assessed gait includes one or more
particular gait patterns that are associated with the particular
medical condition comprises utilizing regression analysis
techniques to identify a first slope of a first line corresponding
to one or more relative peaks in linear acceleration of the head of
the individual over the first period of time to identify a first
gait pattern of the individual; identify a second slope of a second
line corresponding to one or more relative peaks in linear
acceleration of the head of the individual over the second period
of time to identify a second gait pattern of the individual;
compare the first gait pattern to the second gait pattern by
comparing the first slope of the first line to the second slope of
the second line; in response to comparing the first gait pattern to
the second gait pattern, identifying the second gait pattern as an
irregular gait pattern; and analyzing, by the gait server, the
irregular gait pattern to determine whether the irregular gait
pattern includes one or more particular gait patterns that are
associated the particular medical condition.
17. The method of claim 15, wherein the one or more gait patterns
is selected from a group consisting of: foot drop, propulsive gait,
and waddling gait.
18. A system for monitoring a gait of an individual, the system
comprising: a pair of glasses comprising one or more sensors for
assessing the gait of the individual; a computer system comprising
a processor, the computer system being configured for: analyzing
the assessed gait using regression analysis techniques to determine
whether the assessed gait includes one or more gait patterns that
are consistent with a particular medical state of an individual;
and in response to determining that the assessed gait includes the
one or more gait patterns, generating an alert that communicates
the particular medical state.
19. The system of claim 18, wherein the particular medical state
includes an indication of the level of an individual's recovery
from a medical procedure or from a particular injury.
20. The computer-readable medium of claim 18, wherein the step of
analyzing the assessed gait to determine whether the assessed gait
includes one or more particular gait patterns that are consistent
with a particular medical state of an individual comprises: using
the information to assess one or more movements of the individual's
head as the individual ambulates; and comparing the one or more
movements of the individual's head with one or more head movements
that are consistent with a particular medical state of an
individual; and at least partially in response to determining that
the one or more movements of the individual's head are consistent
with the particular medical state, determining that the assessed
gait includes one or more particular gait patterns that are
consistent with the particular medical state.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 14/550,406, filed Nov. 21, 2014, entitled
"WEARABLE GAIT MONITORING APPARATUS, SYSTEMS, AND RELATED METHODS,"
which also claims the benefit of priority to U.S. Provisional
Patent Application Ser. No. 62/046,406, filed Sep. 5, 2014, and
entitled "WEARABLE HEALTH COMPUTER APPARATUS, SYSTEMS, AND RELATED
METHODS," the disclosures of which are incorporated herein by
reference in their entirety.
BACKGROUND
[0002] Observing a person's gait is often an important clinical
step in diagnosing certain types of musculoskeletal and
neurological conditions. Proper gait diagnosis may also be valuable
in properly fitting a patient with a prosthesis. Currently, gait
analysis is largely dependent on the subjective perception of a
trained professional. Such manual diagnosis methods may rely on a
small set of observable activities and may have inherent
inaccuracies, creating the potential for misdiagnosis and the delay
of proper treatment. Thus, there is currently a need for improved
systems and methods for diagnosing the gait of an individual.
SUMMARY OF VARIOUS EMBODIMENTS
[0003] It should be appreciated that this Summary is provided to
introduce a selection of concepts in a simplified form that are
further described below in the Detailed Description. This Summary
is not intended to be used to limit the scope of the claimed
subject matter.
[0004] A non-transitory computer-readable medium storing
computer-executable instructions is provided for receiving
information obtained from at least one sensor worn adjacent the
individual's head. The information is used to assess the gait of
the individual. The assessed gait is analyzed using regression
analysis techniques to determine whether the assessed gait includes
one or more particular gait patterns that are associated with a
particular medical condition. In response to determining that the
assessed gait includes the one or more gait patterns, an alert is
generated that the individual may have the particular medical
condition.
[0005] A system for monitoring a gait of an individual is provided.
The system includes a pair of glasses having means for determining
gait information to assess the gait of the individual. The gait
information includes at least first gait information associated
with a first period of time and second gait information associated
with a second period of time. One or more processors are
operatively coupled of the means for determining gait information.
Memory is operatively coupled to the one or more processors. The
system includes means for analyzing the gait information to
determine whether the assessed gait includes one or more particular
gait patterns that are associated with a particular medical
condition. The system further includes means for, at least
partially in response to determining that the assessed gait
includes the one or more gait patterns, generating an alert that
the individual may have the particular medical condition.
[0006] A system for monitoring a gait of an individual is provided.
The system includes a pair of glasses having one or more sensors
for assessing the gait of the individual. A computer system having
a processor is configured for analyzing the assessed gait using
regression analysis techniques to determine whether the assessed
gait includes one or more gait patterns that are consistent with a
particular medical state of an individual. In response to
determining that the assessed gait includes the one or more gait
patterns, generating an alert that communicates the particular
medical state.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] Various embodiments of systems and methods for monitoring an
individual's gait are described below. In the course of this
description, reference will be made to the accompanying drawings,
which are not necessarily drawn to scale and wherein:
[0008] FIG. 1 is a block diagram of an exemplary system for
monitoring an individual's gait in accordance with an embodiment of
the present system;
[0009] FIG. 2 is a block diagram of a gait analysis server that may
be used in the system shown in FIG. 1; and
[0010] FIG. 3 depicts a flowchart that generally illustrates a
method of monitoring an individual's gait.
DETAILED DESCRIPTION OF SOME EMBODIMENTS
[0011] Various embodiments will now be described more fully
hereinafter with reference to the accompanying drawings. It should
be understood that the invention may be embodied in many different
forms and should not be construed as limited to the embodiments set
forth herein. Rather, these embodiments are provided so that this
disclosure will be thorough and complete, and will fully convey the
scope of the invention to those skilled in the art. Like numbers
refer to like elements throughout.
Overview
[0012] A system, according to various embodiments, includes eyewear
(or any other suitable wearable device) that includes one or more
sensors (e.g., one or more heart rate monitors, one or more
electrocardiograms (EKG), one or more electroencephalograms (EEG),
one or more pedometers, one or more thermometers, one or more
transdermal sensors, one or more front-facing cameras, one or more
eye-facing cameras, one or more microphones, one or more
accelerometers, one or more blood pressure sensors, one or more
pulse oximeters, one or more respiratory rate sensors, one or more
blood alcohol concentration (BAC) sensors, one or more motion
sensors, one or more gyroscopes, one or more geomagnetic sensors,
one or more global positioning system sensors, one or more impact
sensors, or any other suitable one or more sensors) that may be
used to monitor the gait of an individual. The system may further
include one or more suitable computing devices for analyzing the
individual's gait. This information may then be used, for example,
to: (1) identify one or more medical conditions associated with the
individual; (2) assess the fit of a prosthetic device worn by the
individual, and/or (3) assess an individual's recovery from a
particular injury or medical procedure.
Exemplary Technical Platforms
[0013] As will be appreciated by one skilled in the relevant field,
the present invention may be, for example, embodied as a computer
system, a method, or a computer program product. Accordingly,
various embodiments may take the form of an entirely hardware
embodiment, an entirely software embodiment, or an embodiment
combining software and hardware aspects. Furthermore, particular
embodiments may take the form of a computer program product stored
on a computer-readable storage medium having computer-readable
instructions (e.g., software) embodied in the storage medium.
Various embodiments may take the form of internet-implemented
computer software. Any suitable computer-readable storage medium
may be utilized including, for example, hard disks, compact disks,
DVDs, optical storage devices, and/or magnetic storage devices.
[0014] Various embodiments are described below with reference to
block diagrams and flowchart illustrations of methods, apparatuses
(e.g., systems) and computer program products. It should be
understood that each block of the block diagrams and flowchart
illustrations, and combinations of blocks in the block diagrams and
flowchart illustrations, respectively, can be implemented by a
computer executing computer program instructions. These computer
program instructions may be loaded onto a general purpose computer,
special purpose computer, or other programmable data processing
apparatus to produce a machine, such that the instructions which
execute on the computer or other programmable data processing
apparatus to create means for implementing the functions specified
in the flowchart block or blocks.
[0015] These computer program instructions may also be stored in a
computer-readable memory that can direct a computer or other
programmable data processing apparatus to function in a particular
manner such that the instructions stored in the computer-readable
memory produce an article of manufacture that is configured for
implementing the function specified in the flowchart block or
blocks. The computer program instructions may also be loaded onto a
computer or other programmable data processing apparatus to cause a
series of operational steps to be performed on the computer or
other programmable apparatus to produce a computer implemented
process such that the instructions that execute on the computer or
other programmable apparatus provide steps for implementing the
functions specified in the flowchart block or blocks.
[0016] Accordingly, blocks of the block diagrams and flowchart
illustrations support combinations of mechanisms for performing the
specified functions, combinations of steps for performing the
specified functions, and program instructions for performing the
specified functions. It should also be understood that each block
of the block diagrams and flowchart illustrations, and combinations
of blocks in the block diagrams and flowchart illustrations, can be
implemented by special purpose hardware-based computer systems that
perform the specified functions or steps, or combinations of
special purpose hardware and other hardware executing appropriate
computer instructions.
Example System Architecture
[0017] FIG. 1 is a block diagram of a Wearable Gait Monitoring
System 100 according to a particular embodiment. As may be
understood from this figure, the Wearable Gait Monitoring System
100 includes one or more computer networks 115, one or more Third
Party Servers 140a, 140b, 140c, a Gait Server 120, a Database 130,
one or more remote computing devices 110a, 110b (e.g., such as a
smart phone, a tablet computer, a wearable computing device, a
laptop computer, etc.), and one or more wearable gait monitoring
device(s) 150, which may, for example, be embodied as eyewear
(e.g., glasses or goggles), clothing, a watch, a hat, a cast, an
adhesive bandage, a piece of jewelry (e.g., a ring, earring,
necklace, etc.), and/or any other suitable wearable device.
[0018] In various embodiments, the one or more wearable gait
monitoring device(s) 150 may further comprise at least one
processor and one or more sensors (e.g., an accelerometer, a
magnetometer, a gyroscope, a front-facing camera, a location sensor
such as a GPS unit, etc.). In particular embodiments, the system is
configured to gather data, for example, using the one or more
sensors, regarding the user's gait as the user walks or runs (e.g.,
the user's stride cadence, the user's speed (e.g., the speed of the
user's feet and/or body), the orientation of the user (e.g., the
orientation of the user's body and/or feet), the elevation of the
user's respective feet from the ground, the movement of the user's
head such as bobbing, etc.).
[0019] In various embodiments, the database is configured to store
information regarding gait patterns associated with various
predetermined medical conditions. The system is configured to store
information regarding normal gait patterns for a particular
individual or individuals who are similar in physical stature to
the particular individual. In various embodiments, the database
stores past information regarding an individual's gait and may
include recent gait measurements for the individual, which may, for
example, be used to track the individual's progress in improving
their gait (e.g., after an injury or a medical procedure).
[0020] The one or more computer networks 115 may include any of a
variety of types of wired or wireless computer networks such as the
Internet, a private intranet, a mesh network, a public switch
telephone network (PSTN), or any other type of network (e.g., a
network that uses Bluetooth or near field communications to
facilitate communication between computers). The communication link
between the Wearable Gait Monitoring System 100 and the Database
130 may be, for example, implemented via a Local Area Network (LAN)
or via the Internet. In particular embodiments, the one or more
computer networks 115 facilitate communication between the one or
more third party servers 140a, 140b, 140c, the Gait Server 120, the
Database 130, and one or more remote computing devices 110a, 110b.
In various embodiments, the handheld device 110a is configured to
communicate with the wearable gait monitoring device 150 via, for
example, Bluetooth. In various other embodiments, the wearable gait
monitoring device 150 may communicate with a remote server, for
example, the Gait Server 120, via a cellular communication or
wireless Internet connection. In yet other embodiments, the system
may be further configured to allow the wearable gait monitoring
device 150 to communicate with the remote server (e.g., the Gait
Server 120), without the intermediary handheld device 110a.
[0021] FIG. 2 illustrates a diagrammatic representation of a
computer architecture that can be used within the Wearable Gait
Monitoring System 100, for example, as a client computer (e.g., one
of computing devices 110a/110b or wearable gait monitoring devices
150), or as a server computer (e.g., the Gait Server 120) as shown
in FIG. 1. In particular embodiments, the Gait Server 120 may be
suitable for use as a computer, within the context of the wearable
gait monitoring system 100, that is configured to record medical
information for use in gait analysis and to provide communication
between one or more users and healthcare practitioners.
[0022] In particular embodiments, the Gait Server 120 may be
connected (e.g., networked) to other computers in a LAN, an
intranet, an extranet, and/or the Internet. As noted above, the
Gait Server 120 may operate in the capacity of a server or a client
computer in a client-server network environment, or as a peer
computer in a peer-to-peer (or distributed) network environment.
The Gait Server 120 may be a desktop personal computer (PC), a
tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA),
a cellular telephone, a web appliance, a server, a network router,
a switch or bridge, or any other computer capable of executing a
set of instructions (sequential or otherwise) that specify actions
to be taken by that computer. Further, while only a single computer
is illustrated, the term "computer" shall also be taken to include
any collection of computers that individually or jointly execute a
set (or multiple sets) of instructions to perform any one or more
of the methodologies discussed herein.
[0023] An exemplary Gait Server 120 includes a processing device
202, a main memory 204 (e.g., read-only memory (ROM), flash memory,
dynamic random access memory (DRAM) such as synchronous DRAM
(SDRAM) or Rambus DRAM (RDRAM), etc.), a static memory 206 (e.g.,
flash memory, static random access memory (SRAM), etc.), and a data
storage device 218, which communicate with each other via a bus
232.
[0024] The processing device 202 represents one or more
general-purpose processing devices such as a microprocessor, a
central processing unit, or the like. More particularly, the
processing device 202 may be a complex instruction set computing
(CISC) microprocessor, reduced instruction set computing (RISC)
microprocessor, very long instruction word (VLIW) microprocessor,
or processor implementing other instruction sets, or processors
implementing a combination of instruction sets. The processing
device 202 may also be one or more special-purpose processing
devices such as an application specific integrated circuit (ASIC),
a field programmable gait array (FPGA), a digital signal processor
(DSP), network processor, or the like. The processing device 202
may be configured to execute processing logic 226 for performing
various operations and steps discussed herein.
[0025] The Gait Server 120 may further include a network interface
device 208. The Gait Server 120 also may include a video display
unit 210 (e.g., a liquid crystal display (LCD) or a cathode ray
tube (CRT)), an alphanumeric input device 212 (e.g., a keyboard), a
cursor control device 214 (e.g., a mouse), and a signal generation
device 216 (e.g., a speaker).
[0026] The data storage device 218 may include a non-transitory
computer-accessible storage medium 230 (also known as a
non-transitory computer-readable storage medium or a non-transitory
computer-readable medium) on which is stored one or more sets of
instructions (e.g., software 222) embodying any one or more of the
methodologies or functions described herein. The software 222 may
also reside, completely or at least partially, within the main
memory 204 and/or within the processing device 202 during execution
thereof by the Gait Server 120--the main memory 204 and the
processing device 202 also constituting computer-accessible storage
media. The software 222 may further be transmitted or received over
a network 115 via a network interface device 208.
[0027] While the computer-accessible storage medium 230 is shown in
an exemplary embodiment to be a single medium, the terms
"computer-accessible storage medium" and "computer-readable medium"
should be understood to include a single medium or multiple media
(e.g., a centralized or distributed database, and/or associated
caches and servers) that store the one or more sets of
instructions. The term "computer-accessible storage medium" and
"computer-readable medium" should also be understood to include any
medium that is capable of storing, encoding or carrying a set of
instructions for execution by the computer and that cause the
computer to perform any one or more of the methodologies of the
present invention. The terms "computer-accessible storage medium"
and "computer-readable medium" should accordingly be understood to
include, but not be limited to, solid-state memories, optical and
magnetic media, etc.
More Detailed Description of Gait Monitoring Functionality
[0028] Various embodiments of a system for the monitoring the gait
of an individual are described below and may be implemented in any
suitable context. For example, particular embodiments may be
implemented to: (1) identify one or more medical conditions
associated with the individual; (2) assess the fit of a prosthetic
device worn by the individual, and/or (3) assess an individual's
recovery from a particular injury or medical procedure.
[0029] Various aspects of the system's functionality may be
executed by certain system modules, including the Gait Monitoring
Module 300. The Gait Monitoring Module 300 is discussed in greater
detail below.
Gait Monitoring Module
[0030] Referring to FIG. 3A, when executing the Gait Monitoring
Module 300, the system begins, in various embodiments, at Step 305
by receiving data from a wearable device worn by an individual
whose gait is to be monitored by the system. In particular
embodiments, the system is configured to receive data from one or
more sensors (e.g. an accelerometer, a gyroscope, a position
locating device and/or magnetometer) while: (1) the individual is
wearing the wearable device adjacent the user's face and/or head;
and (2) the individual is walking or running. In particular
embodiments, the system is configured to receive the data while the
individual is walking or running within the context of their
typical daily routine, and not within the context of a medical
diagnostic visit. The system may also or alternatively be
configured to receive data within the context of a medical
diagnostic visit (e.g., at a doctor's office, hospital, or other
medical facility).
[0031] In particular embodiments, the one or more of the system's
sensors may be embedded in, or otherwise attached to, eyewear or
other wearable device (e.g., another wearable device worn adjacent
the individual's head or another suitable part of the individual's
body). In particular embodiments, at least one or more of the
system's sensors may be incorporated into a prosthesis or into a
portion of the individual's shoes. In certain embodiments, the
system may include one or more sensors that are incorporated into
(e.g., embedded in, or attached to) a plurality of wearable devices
(e.g., eyewear and the individual's shoes) that are adapted to be
worn simultaneously by the user while the system retrieves signals
from the sensors to assess the individual's gait.
[0032] In particular embodiments, the system may include a set of
eyewear that includes one or more motion sensors (e.g.,
accelerometers, gyroscopes, or location sensors) for sensing the
movement of the head of an individual who is wearing the eyewear as
the individual walks. The system may then use this head movement
information (e.g., using any suitable technique, such as any
suitable technique described herein) to determine whether the user
has a gait abnormality. The system may do this, for example, by
comparing one or more of the measured head motions of an individual
(e.g., as measured when the individual is walking or running) with
the actual or typical head motions experienced by individuals with
gait abnormalities as those individuals walk or run.
[0033] In various embodiments, the system is configured to measure
and receive at least one of the velocity, height, and orientation
of one or more of the individual's feet. For example, in certain
embodiments, the system is configured to measure and receive (e.g.,
using the suitable sensors) the linear acceleration of each of the
individual's feet, the height of each of the feet from the ground,
and/or the position and/or orientation of each of the feet relative
to the central axis of the individual's body as the individual
walks or runs.
[0034] The system continues at Step 310 by using the data received
from the system's sensors to identify one or more relative peaks in
linear acceleration of the individual's body and/or head as the
user ambulates (e.g., walks or runs). In various embodiments, the
system may do this by processing the data received from the
sensor(s) in Step 305, and then isolating the relative peaks in the
data. Such peaks represent the relative maxima and minima of the
linear acceleration of the user's head, body, and/or one or more of
the individual's lower body parts (e.g., knee, ankle, or foot) as
the user ambulates. Alternatively or additionally, the system may
be configured to identify the relative peaks in linear acceleration
by identifying the slope of the line formed by regression analysis
of the data received from the sensors. This regression analysis may
indicate the change in magnitude of the linear acceleration with
time.
[0035] In identifying the relative peaks in linear acceleration,
the system is further configured to identify the peaks such that
the magnitude and phase of these peaks may be utilized to aid in
the diagnosis of one or more gait abnormalities by comparing the
magnitude and phase of the peaks associated with the individual's
gait with the magnitude and phase of the peaks associated with: (1)
the gait of one or more individuals who are known to have one or
more gait abnormalities; (2) a typical gait associated with
individuals who are known to have one or more gait abnormalities;
and/or (3) the individual's normal gait (which may be determined
based on data stored in system memory that the system obtained, for
example, when the individual was known to walk or run without a
gait abnormality). This comparison may be helpful in determining
whether the individual has a gait abnormality and, if so, whether
the gait abnormality exists due to an improper prosthetic fit.
[0036] In a particular embodiment, the above comparison may involve
comparing the magnitude and/or phase of peaks that represent a
user's head movement as the user ambulates with the magnitude
and/or phase of peaks that represent the head movement, during
ambulation, of (1) one or more individuals who are known to have
one or more gait abnormalities; (2) a typical individual (or model
theoretical individual) who is known to have one or more gait
abnormalities; and/or (3) the individual themself (this data may be
determined, for example, based on data stored in system memory that
the system obtained, for example, when the individual was known to
walk or run without a gait abnormality).
[0037] Continuing at Step 315, the system is configured to analyze
the received gait information to determine whether the individual
has an identifiable gait abnormality and to communicate the results
of the analysis to the user. In various embodiments, the system may
use the gait information to: (1) identify potential, previously
undiagnosed medical conditions (e.g., one or more medical
conditions, such as ALS or MS, that may be indicated by a
particular gait abnormality, such as foot drop); (2) assess the
quality of the fit of a prosthesis; and/or (3) assess the
individual's progress in recovering from an injury or medical
procedure (e.g., knee or hip surgery).
Use of System to Identify Previously Undiagnosed Medical
Condition
[0038] In identifying a potential, previously undiagnosed medical
condition, the system is configured to compare the gait of the
individual with: (1) the gait of one or more individuals who are
known to have one or more gait abnormalities (e.g., hemiplegic
gait, diplegic gait, neuropathic gait, foot drop, myopathic gait,
or ataxic gait); (2) a typical gait associated with individuals who
are known to have one or more gait abnormalities; and/or (3) the
individual's normal gait. To do this, the system may compare one or
more gait patterns of a user (e.g., in the manner discussed above
or in any other suitable way) with information regarding one or
more abnormal gait patterns that is stored in a Gait Database 130.
The system may do this, for example, by applying any suitable
mathematical or other data comparison technique to determine
whether one of more of the individual's gait patterns are at least
substantially similar to one or more abnormal gait patterns stored
in the system's Gait Database 130.
[0039] If the system determines that the individual has, or may
have, a particular gait abnormality, the system may generate and
send a notification to a suitable individual (e.g., the individual
or the individual's physician) indicating that the individual may
have a gait abnormality and/or that it may be beneficial to examine
or monitor the individual for one or more medical conditions that
are typically associated with the gait abnormality, e.g., stroke,
amyotrophic lateral sclerosis, muscular dystrophy, Charcot Manes
Tooth disease, multiple sclerosis, cerebral palsy, hereditary
spastic paraplegia, and Friedrich's ataxia. The notification may
be, for example, a suitable electronic notification (e.g., a
message on a display screen, an e-mail, a text), or any other
suitable notification.
Use of System to Determine Whether a Prosthesis Fits Correctly
[0040] In assessing the quality of fit of the prosthesis, the
system in various embodiments, may, in various embodiments, be
configured to compare the user's assessed gait with: (1) the gait
of one or more individuals who are known to have one or more gait
abnormalities that are associated with an improper prosthetic fit;
(2) a typical gait associated with individuals who are known to
have one or more gait abnormalities that are associated with an
improper prosthetic fit; and/or (3) the individual's normal gait.
This comparison may be done as discussed above or in any other
suitable way. In particular embodiments, the gait patterns that the
individual's gait patterns are compared with may be modeled, for
example, based on previously recorded data for individuals with one
or more physical attributes (e.g., height, age, weight, femur
length, etc . . . ) that are similar to that of the individual. In
various other embodiments, such patterns may be modeled from
previously recorded data for users that aren't physically similar
to the individual.
[0041] In response to determining that the individual has one or
more gait patterns that are associated with an improper prosthetic
fit, the system may generate an alert indicating that the
prosthesis may fit improperly. The system may send this alert
electronically, for example, via email, text message, or via a
display on a display screen, to the user and/or their physician or
other suitable individual.
[0042] In various embodiments, after determining that the
individual has an abnormal gait, the system may then determine
whether the gait deviation results from an improperly fitting
prosthesis or from an injury associated with the individual (e.g.,
an infected wound adjacent the prosthesis). It is noted that an
improper fit of a prosthetic leg may result in any of a number of
gait deviations such as trans-femoral (TF) long prosthetic step, TF
excessive lumbar lordosis, TF drop off at end of stance, TF foot
slap, TF medial or lateral whips, TF uneven heel rise, etc. While
such gait deviations may result from an improper prosthetic fit,
they may also manifest from: (1) various improper actions or
movements by the amputee while the amputee is wearing the
prosthesis; or (2) an injury adjacent the prosthesis. Clinically
distinguishing an improper gait caused by a poorly fitting
prosthetic from an improper gait caused by improper use of a
properly fitted prosthesis may be important in helping the amputee
regain proper functionality of the prosthetic.
Use of System to Assess an Individual's Recovery from an Injury or
Medical Procedure
[0043] In assessing an individual's recovery from an injury or
medical procedure, the system may compare the individual's current
gait with historical gait information for the individual stored in
the Database 130. The historical gait information, in various
embodiments, may include gait pattern information taken for the
individual at some time in the past (e.g., the recent past) before
or after the user suffered the injury or underwent the medical
procedure.
[0044] The system may then analyze both sets of gait information to
determine whether the individual's gait has become more consistent
with the user's normal gait (e.g., fewer abnormalities in gait,
more regular, quicker lateral acceleration, etc.) To do this, the
system may, in various embodiments, compare the user's current gait
information with a normal gait to determine whether the user's gait
has become more consistent with a normal gait over time. In other
embodiments, the system may compare the most current gait data with
other post-procedure or post-injury gait data for the individual to
determine whether the user's gait has become more consistent with a
normal gait (e.g., the individual's normal gait).
[0045] Upon analyzing both sets of gait information, the system may
generate an appropriate assessment of the user's recovery and/or to
generate one or more treatment recommendations. The system may, in
various embodiments, generate a report that communicates the
progress of an individual's recovery. The system may also, or
alternatively, generate an alternate treatment plan for the
individual, if necessary. For example, a particular generated
report may include one or more recommendations with regard to a
particular type and length of physical therapy to be performed by
the individual, and/or one or more dietary restrictions that the
individual should implement to aid recovery to regain muscle tone
and strength in the affected limb. The system may then communicate
the report to the individual or an appropriate third party.
User Experience
Gait Abnormality Diagnosis
[0046] In a particular example, a pair of eyewear with embedded
sensors may be used to monitor the user's gait over the course of
one or more days (e.g., days, weeks, months, years, etc.). As the
sensors measure the movements of the individual's body (e.g., the
individual's head, legs, feet, etc . . . ), the system may transmit
the related movement data to a remote server where the information
is stored in a suitable database. After receiving the data, a
central server may process the data to identify one or more gait
patterns for the individual. The system may then compare one or
more of the individual's gait patterns with one or more known
irregular gait patterns to determine whether the individual has an
irregular gait pattern as discussed above.
[0047] The system may be utilized, for example, in the following
construct. A patient may present to a physician complaining of
weakness and decreased use of one leg. The physician may perform a
routine physical, ask diagnostic questions, and have the patient
walk briefly in order to physically demonstrate the purported
condition. Upon observing the patient, the doctor may decide that
the patient may potentially have a gait abnormality, but the
physician cannot isolate the specific abnormality as presented by
the patient. The physician may instruct the patient to wear the
wearable gait monitoring device over the course of one or more
days. During this time, the wearable gait monitoring device would
obtain and record information regarding the individual's gait as
discussed above.
[0048] The system may then use the information to identify one or
more gait pattern irregularities as discussed above and generate a
message to the user's treating physician indicating that the
individual appears to have an abnormal gait. The system may
optionally further display one or more potential medical conditions
associated with that gait, e.g., amyotrophic lateral sclerosis,
multiple sclerosis, etc. The physician may then meet with the
individual to discuss the individual's condition, and/or to order
additional testing to establish a particular diagnosis. For
example, the physician may review the patient's medical history,
presented gait pattern, and possible conditions contributing to the
gait abnormality to diagnose and/or to order more tests to aid in
the diagnosis of such medical conditions.
[0049] The system may similarly be used to analyze the fit of a
particular prosthetic, or a user's recovery from an injury or
surgery using similar techniques in combination with one or more of
the methods described above.
Conclusion
[0050] Many modifications and other embodiments of the invention
will come to mind to one skilled in the art to which this invention
pertains, having the benefit of the teaching presented in the
foregoing descriptions and the associated drawings. Therefore, it
is to be understood that the invention is not to be limited to the
specific embodiments disclosed and that modifications and other
embodiments are intended to be included within the scope of the
appended claims. Although specific terms are employed herein, they
are used in a generic and descriptive sense only and not for the
purposes of limitation.
* * * * *