Wearable pendant device monitoring using new wavelet-based methods shows daily life and laboratory gaits are different.
Morbidity and falls are problematic for older people. Wearable devices are increasingly used to monitor daily activities. However, sensors often require rigid attachment to specific locations and shuffling or quiet standing may be confused with walking. Furthermore, it is unclear whether clinical ga...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 54; no. 4; pp. 663 - 675 |
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| Autores principales: | , , , , , , , , , , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2016
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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=113881205&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 113881205 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Apr2016 vid: 54 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 113881205 113881205 NLM26245255 113881205 10.1007/s11517-015-1357-9 NLM26245255 113881205 ppf: 663 ppct: 12 formats: fmt: @attributes: type: P tig: atl: Wearable pendant device monitoring using new wavelet-based methods shows daily life and laboratory gaits are different. aug: au: Brodie, Matthew Coppens, Milou Lord, Stephen Lovell, Nigel Gschwind, Yves Redmond, Stephen Del Rosario, Michael Wang, Kejia Sturnieks, Daina Persiani, Michela Delbaere, Kim Brodie, Matthew A D Coppens, Milou J M Lord, Stephen R Lovell, Nigel H Gschwind, Yves J Redmond, Stephen J Del Rosario, Michael Benjamin Sturnieks, Daina L affil: Falls and Balance Research Group, Neuroscience Research Australia, University of New South Wales, Barker Street Randwick, Sydney 2031 Australia sug: subj: Signal Processing, Computer Assisted Gait Physiology Monitoring, Physiologic Equipment and Supplies Activities of Daily Living Aged, 80 and Over Algorithms Motion Female Aged Decision Trees Male Human Validation Studies Comparative Studies Evaluation Research Multicenter Studies Aged, 80 & over Aged: 65+ years Female Male ab: Morbidity and falls are problematic for older people. Wearable devices are increasingly used to monitor daily activities. However, sensors often require rigid attachment to specific locations and shuffling or quiet standing may be confused with walking. Furthermore, it is unclear whether clinical gait assessments are correlated with how older people usually walk during daily life. Wavelet transformations of accelerometer and barometer data from a pendant device worn inside or outside clothing were used to identify walking (excluding shuffling or standing) by 51 older people (83 ± 4 years) during 25 min of 'free-living' activities. Accuracy was validated against annotated video. Training and testing were separated. Activities were only loosely structured including noisy data preceding pendant wearing. An electronic walkway was used for laboratory comparisons. Walking was classified (accuracy ≥97 %) with low false-positive errors (≤1.9%, κ ≥ 0.90). Median free-living cadence was lower than laboratory-assessed cadence (101 vs. 110 steps/min, p < 0.001) but correlated (r = 0.69). Free-living step time variability was significantly higher and uncorrelated with laboratory-assessed variability unless detrended. Remote gait impairment monitoring using wearable devices is feasible providing new ways to investigate morbidity and falls risk. Laboratory-assessed gait performances are correlated with free-living walks, but likely reflect the individual's 'best' performance. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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