Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention.
Identifieur interne : 000676 ( PubMed/Corpus ); précédent : 000675; suivant : 000677Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention.
Auteurs : Pete B. Shull ; Wisit Jirattigalachote ; Michael A. Hunt ; Mark R. Cutkosky ; Scott L. DelpSource :
- Gait & posture [ 1879-2219 ] ; 2014.
English descriptors
- KwdEn :
- Adult, Ankle (physiology), Biofeedback, Psychology (instrumentation), Clothing, Craniocerebral Trauma (physiopathology), Equipment Design, Feedback, Sensory (physiology), Foot (physiology), Gait (physiology), Hemiplegia (physiopathology), Humans, Knee (physiology), Leg (physiology), Monitoring, Ambulatory (instrumentation), Movement (physiology), Movement Disorders (physiopathology), Osteoarthritis (physiopathology), Parkinson Disease (physiopathology), Reference Values, Remote Sensing Technology (instrumentation), Transducers, Walking (physiology), Weight-Bearing (physiology), Wireless Technology (instrumentation).
- MESH :
- instrumentation : Biofeedback, Psychology, Monitoring, Ambulatory, Remote Sensing Technology, Wireless Technology.
- physiology : Ankle, Feedback, Sensory, Foot, Gait, Knee, Leg, Movement, Walking, Weight-Bearing.
- physiopathology : Craniocerebral Trauma, Hemiplegia, Movement Disorders, Osteoarthritis, Parkinson Disease.
- Adult, Clothing, Equipment Design, Humans, Reference Values, Transducers.
Abstract
The proliferation of miniaturized electronics has fueled a shift toward wearable sensors and feedback devices for the mass population. Quantified self and other similar movements involving wearable systems have gained recent interest. However, it is unclear what the clinical impact of these enabling technologies is on human gait. The purpose of this review is to assess clinical applications of wearable sensing and feedback for human gait and to identify areas of future research. Four electronic databases were searched to find articles employing wearable sensing or feedback for movements of the foot, ankle, shank, thigh, hip, pelvis, and trunk during gait. We retrieved 76 articles that met the inclusion criteria and identified four common clinical applications: (1) identifying movement disorders, (2) assessing surgical outcomes, (3) improving walking stability, and (4) reducing joint loading. Characteristics of knee and trunk motion were the most frequent gait parameters for both wearable sensing and wearable feedback. Most articles performed testing on healthy subjects, and the most prevalent patient populations were osteoarthritis, vestibular loss, Parkinson's disease, and post-stroke hemiplegia. The most widely used wearable sensors were inertial measurement units (accelerometer and gyroscope packaged together) and goniometers. Haptic (touch) and auditory were the most common feedback sensations. This review highlights the current state of the literature and demonstrates substantial potential clinical benefits of wearable sensing and feedback. Future research should focus on wearable sensing and feedback in patient populations, in natural human environments outside the laboratory such as at home or work, and on continuous, long-term monitoring and intervention.
DOI: 10.1016/j.gaitpost.2014.03.189
PubMed: 24768525
Links to Exploration step
pubmed:24768525Le document en format XML
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Electronic address: pshull@sjtu.edu.cn.</nlm:affiliation></affiliation></author><author><name sortKey="Jirattigalachote, Wisit" sort="Jirattigalachote, Wisit" uniqKey="Jirattigalachote W" first="Wisit" last="Jirattigalachote">Wisit Jirattigalachote</name><affiliation><nlm:affiliation>Department of Mechanical Engineering, Stanford University, Stanford, CA, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Hunt, Michael A" sort="Hunt, Michael A" uniqKey="Hunt M" first="Michael A" last="Hunt">Michael A. Hunt</name><affiliation><nlm:affiliation>Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada.</nlm:affiliation></affiliation></author><author><name sortKey="Cutkosky, Mark R" sort="Cutkosky, Mark R" uniqKey="Cutkosky M" first="Mark R" last="Cutkosky">Mark R. Cutkosky</name><affiliation><nlm:affiliation>Department of Mechanical Engineering, Stanford University, Stanford, CA, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Delp, Scott L" sort="Delp, Scott L" uniqKey="Delp S" first="Scott L" last="Delp">Scott L. 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Shull</name><affiliation><nlm:affiliation>State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China. Electronic address: pshull@sjtu.edu.cn.</nlm:affiliation></affiliation></author><author><name sortKey="Jirattigalachote, Wisit" sort="Jirattigalachote, Wisit" uniqKey="Jirattigalachote W" first="Wisit" last="Jirattigalachote">Wisit Jirattigalachote</name><affiliation><nlm:affiliation>Department of Mechanical Engineering, Stanford University, Stanford, CA, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Hunt, Michael A" sort="Hunt, Michael A" uniqKey="Hunt M" first="Michael A" last="Hunt">Michael A. Hunt</name><affiliation><nlm:affiliation>Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada.</nlm:affiliation></affiliation></author><author><name sortKey="Cutkosky, Mark R" sort="Cutkosky, Mark R" uniqKey="Cutkosky M" first="Mark R" last="Cutkosky">Mark R. Cutkosky</name><affiliation><nlm:affiliation>Department of Mechanical Engineering, Stanford University, Stanford, CA, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Delp, Scott L" sort="Delp, Scott L" uniqKey="Delp S" first="Scott L" last="Delp">Scott L. Delp</name><affiliation><nlm:affiliation>Department of Mechanical Engineering, Stanford University, Stanford, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Gait & posture</title><idno type="eISSN">1879-2219</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult</term><term>Ankle (physiology)</term><term>Biofeedback, Psychology (instrumentation)</term><term>Clothing</term><term>Craniocerebral Trauma (physiopathology)</term><term>Equipment Design</term><term>Feedback, Sensory (physiology)</term><term>Foot (physiology)</term><term>Gait (physiology)</term><term>Hemiplegia (physiopathology)</term><term>Humans</term><term>Knee (physiology)</term><term>Leg (physiology)</term><term>Monitoring, Ambulatory (instrumentation)</term><term>Movement (physiology)</term><term>Movement Disorders (physiopathology)</term><term>Osteoarthritis (physiopathology)</term><term>Parkinson Disease (physiopathology)</term><term>Reference Values</term><term>Remote Sensing Technology (instrumentation)</term><term>Transducers</term><term>Walking (physiology)</term><term>Weight-Bearing (physiology)</term><term>Wireless Technology (instrumentation)</term></keywords><keywords scheme="MESH" qualifier="instrumentation" xml:lang="en"><term>Biofeedback, Psychology</term><term>Monitoring, Ambulatory</term><term>Remote Sensing Technology</term><term>Wireless Technology</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Ankle</term><term>Feedback, Sensory</term><term>Foot</term><term>Gait</term><term>Knee</term><term>Leg</term><term>Movement</term><term>Walking</term><term>Weight-Bearing</term></keywords><keywords scheme="MESH" qualifier="physiopathology" xml:lang="en"><term>Craniocerebral Trauma</term><term>Hemiplegia</term><term>Movement Disorders</term><term>Osteoarthritis</term><term>Parkinson Disease</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>Clothing</term><term>Equipment Design</term><term>Humans</term><term>Reference Values</term><term>Transducers</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The proliferation of miniaturized electronics has fueled a shift toward wearable sensors and feedback devices for the mass population. Quantified self and other similar movements involving wearable systems have gained recent interest. However, it is unclear what the clinical impact of these enabling technologies is on human gait. The purpose of this review is to assess clinical applications of wearable sensing and feedback for human gait and to identify areas of future research. Four electronic databases were searched to find articles employing wearable sensing or feedback for movements of the foot, ankle, shank, thigh, hip, pelvis, and trunk during gait. We retrieved 76 articles that met the inclusion criteria and identified four common clinical applications: (1) identifying movement disorders, (2) assessing surgical outcomes, (3) improving walking stability, and (4) reducing joint loading. Characteristics of knee and trunk motion were the most frequent gait parameters for both wearable sensing and wearable feedback. Most articles performed testing on healthy subjects, and the most prevalent patient populations were osteoarthritis, vestibular loss, Parkinson's disease, and post-stroke hemiplegia. The most widely used wearable sensors were inertial measurement units (accelerometer and gyroscope packaged together) and goniometers. Haptic (touch) and auditory were the most common feedback sensations. This review highlights the current state of the literature and demonstrates substantial potential clinical benefits of wearable sensing and feedback. Future research should focus on wearable sensing and feedback in patient populations, in natural human environments outside the laboratory such as at home or work, and on continuous, long-term monitoring and intervention.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">24768525</PMID><DateCreated><Year>2014</Year><Month>05</Month><Day>20</Day></DateCreated><DateCompleted><Year>2015</Year><Month>08</Month><Day>21</Day></DateCompleted><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1879-2219</ISSN><JournalIssue CitedMedium="Internet"><Volume>40</Volume><Issue>1</Issue><PubDate><Year>2014</Year></PubDate></JournalIssue><Title>Gait & posture</Title><ISOAbbreviation>Gait Posture</ISOAbbreviation></Journal><ArticleTitle>Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention.</ArticleTitle><Pagination><MedlinePgn>11-9</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.gaitpost.2014.03.189</ELocationID><ELocationID EIdType="pii" ValidYN="Y">S0966-6362(14)00287-2</ELocationID><Abstract><AbstractText>The proliferation of miniaturized electronics has fueled a shift toward wearable sensors and feedback devices for the mass population. Quantified self and other similar movements involving wearable systems have gained recent interest. However, it is unclear what the clinical impact of these enabling technologies is on human gait. The purpose of this review is to assess clinical applications of wearable sensing and feedback for human gait and to identify areas of future research. Four electronic databases were searched to find articles employing wearable sensing or feedback for movements of the foot, ankle, shank, thigh, hip, pelvis, and trunk during gait. We retrieved 76 articles that met the inclusion criteria and identified four common clinical applications: (1) identifying movement disorders, (2) assessing surgical outcomes, (3) improving walking stability, and (4) reducing joint loading. Characteristics of knee and trunk motion were the most frequent gait parameters for both wearable sensing and wearable feedback. Most articles performed testing on healthy subjects, and the most prevalent patient populations were osteoarthritis, vestibular loss, Parkinson's disease, and post-stroke hemiplegia. The most widely used wearable sensors were inertial measurement units (accelerometer and gyroscope packaged together) and goniometers. Haptic (touch) and auditory were the most common feedback sensations. This review highlights the current state of the literature and demonstrates substantial potential clinical benefits of wearable sensing and feedback. Future research should focus on wearable sensing and feedback in patient populations, in natural human environments outside the laboratory such as at home or work, and on continuous, long-term monitoring and intervention.</AbstractText><CopyrightInformation>Copyright © 2014 Elsevier B.V. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Shull</LastName><ForeName>Pete B</ForeName><Initials>PB</Initials><AffiliationInfo><Affiliation>State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China. Electronic address: pshull@sjtu.edu.cn.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jirattigalachote</LastName><ForeName>Wisit</ForeName><Initials>W</Initials><AffiliationInfo><Affiliation>Department of Mechanical Engineering, Stanford University, Stanford, CA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hunt</LastName><ForeName>Michael A</ForeName><Initials>MA</Initials><AffiliationInfo><Affiliation>Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Cutkosky</LastName><ForeName>Mark R</ForeName><Initials>MR</Initials><AffiliationInfo><Affiliation>Department of Mechanical Engineering, Stanford University, Stanford, CA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Delp</LastName><ForeName>Scott L</ForeName><Initials>SL</Initials><AffiliationInfo><Affiliation>Department of Mechanical Engineering, Stanford University, Stanford, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType><PublicationType UI="D016454">Review</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2014</Year><Month>04</Month><Day>06</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Gait Posture</MedlineTA><NlmUniqueID>9416830</NlmUniqueID><ISSNLinking>0966-6362</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName MajorTopicYN="N" UI="D000328">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D000842">Ankle</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D001676">Biofeedback, Psychology</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000295">instrumentation</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D003020">Clothing</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D006259">Craniocerebral Trauma</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000503">physiopathology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D004867">Equipment Design</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D056228">Feedback, Sensory</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D005528">Foot</DescriptorName><QualifierName MajorTopicYN="N" 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UI="Q000295">instrumentation</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D009068">Movement</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D009069">Movement Disorders</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000503">physiopathology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D010003">Osteoarthritis</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000503">physiopathology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D010300">Parkinson Disease</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000503">physiopathology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D012016">Reference Values</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D058998">Remote Sensing Technology</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000295">instrumentation</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D014159">Transducers</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D016138">Walking</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D016474">Weight-Bearing</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D059015">Wireless Technology</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000295">instrumentation</QualifierName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Biofeedback</Keyword><Keyword MajorTopicYN="N">Gait retraining</Keyword><Keyword MajorTopicYN="N">Haptic</Keyword><Keyword MajorTopicYN="N">Motion analysis</Keyword><Keyword MajorTopicYN="N">Real-time feedback</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2013</Year><Month>10</Month><Day>28</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2014</Year><Month>3</Month><Day>10</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2014</Year><Month>3</Month><Day>30</Day></PubMedPubDate><PubMedPubDate PubStatus="aheadofprint"><Year>2014</Year><Month>4</Month><Day>6</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2014</Year><Month>4</Month><Day>29</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2014</Year><Month>4</Month><Day>29</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2015</Year><Month>8</Month><Day>22</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">24768525</ArticleId><ArticleId 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