Instrumented shoes for activity classification in the elderly.
Quantifying daily physical activity in older adults can provide relevant monitoring and diagnostic information about risk of fall and frailty. In this study, we introduce instrumented shoes capable of recording movement and foot loading data unobtrusively throughout the day. Recorded data were used...
| Published in: | Gait & Posture Vol. 44; pp. 12 - 18 |
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| Main Authors: | , , , , , |
| Format: | research Journal Article |
| Published: |
Elsevier B.V.
Feb2016
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=113896709&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 113896709 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09666362 3L6 jtl: Gait & Posture issn: 09666362 maglogo: N pubinfo: dt: Feb2016 vid: 44 pid: 1004 pub: Elsevier B.V. artinfo: ui: 113896709 113896709 NLM27004626 113896709 10.1016/j.gaitpost.2015.10.016 NLM27004626 113896709 ppf: 12 ppct: 6 formats: tig: atl: Instrumented shoes for activity classification in the elderly. aug: au: Moufawad el Achkar, Christopher Lenoble-Hoskovec, Constanze Paraschiv-Ionescu, Anisoara Major, Kristof Büla, Christophe Aminian, Kamiar affil: Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland sug: subj: Motor Activity Shoes Monitoring, Physiologic Equipment and Supplies Activities of Daily Living Algorithms Female Male Human Aged Validation Studies Comparative Studies Evaluation Research Multicenter Studies Aged: 65+ years Female Male ab: Quantifying daily physical activity in older adults can provide relevant monitoring and diagnostic information about risk of fall and frailty. In this study, we introduce instrumented shoes capable of recording movement and foot loading data unobtrusively throughout the day. Recorded data were used to devise an activity classification algorithm. Ten elderly persons wore the instrumented shoe system consisting of insoles inside the shoes and inertial measurement units on the shoes, and performed a series of activities of daily life as part of a semi-structured protocol. We hypothesized that foot loading, orientation, and elevation can be used to classify postural transitions, locomotion, and walking type. Additional sensors worn at the right thigh and the trunk were used as reference, along with an event marker. An activity classification algorithm was built based on a decision tree that incorporates rules inspired from movement biomechanics. The algorithm revealed excellent performance with respect to the reference system with an overall accuracy of 97% across all activities. The algorithm was also capable of recognizing all postural transitions and locomotion periods with elevation changes. Furthermore, the algorithm proved to be robust against small changes of tuning parameters. This instrumented shoe system is suitable for daily activity monitoring in elderly persons and can additionally provide gait parameters, which, combined with activity parameters, can supply useful clinical information regarding the mobility of elderly persons. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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