Classifying sitting, standing, and walking using plantar force data.
Prolonged static weight-bearing at work may increase the risk of developing plantar fasciitis (PF). However, to establish a causal relationship between weight-bearing and PF, a low-cost objective measure of workplace behaviors is needed. This proof-of-concept study assesses the classification accura...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 59; no. 1; pp. 257 - 271 |
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| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jan2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=148139441&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 148139441 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jan2021 vid: 59 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 148139441 148008914 148139441 NLM33420617 10.1007/s11517-020-02297-4 NLM33420617 148139441 ppf: 257 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Classifying sitting, standing, and walking using plantar force data. aug: au: Merry, Kohle J. Macdonald, Evan MacPherson, Megan Aziz, Omar Park, Edward Ryan, Michael Sparrey, Carolyn J. affil: School of Mechatronic Systems Engineering, Simon Fraser University, 250-13450 102 Ave, V3T 0A3, Surrey, BC, Canada sug: subj: Walking Weight-Bearing Shoes Foot Scales ab: Prolonged static weight-bearing at work may increase the risk of developing plantar fasciitis (PF). However, to establish a causal relationship between weight-bearing and PF, a low-cost objective measure of workplace behaviors is needed. This proof-of-concept study assesses the classification accuracy and sensitivity of low-resolution plantar pressure measurements in distinguishing workplace postures. Plantar pressure was measured using an in-shoe measurement system in eight healthy participants while sitting, standing, and walking. Data was resampled to simulate on/off characteristics of 24 plantar force sensitive resistors. The top 10 sensors were evaluated using leave-one-out cross-validation with machine learning algorithms: support vector machines (SVMs), decision tree (DT), discriminant analysis (DA), and k-nearest neighbors (KNN). SVM and DT best classified sitting, standing, and walking. High classification accuracy was obtained with five sensors (98.6% and 99.1% accuracy, respectively) and even a single sensor (98.4% and 98.4%, respectively). The central forefoot and the medial and lateral midfoot were the most important classification sensor locations. On/off plantar pressure measurements in the midfoot and central forefoot can accurately classify workplace postures. These results provide the foundation for a low-cost objective tool to classify and quantify sedentary workplace postures. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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