title: Wearable pendant device monitoring using new wavelet-based methods shows daily life and laboratory gaits are different.
abstract: 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.
authors.affiliation: Falls and Balance Research Group, Neuroscience Research Australia, University of New South Wales, Barker Street, Randwick, Sydney, NSW, 2031, Australia. brodiephd@gmail.com.|Graduate School of Biomedical Engineering, University of New South Wales, Randwick, Sydney, NSW, Australia. brodiephd@gmail.com.
authors.forename: Matthew A D
authors.initials: MA
authors.lastname: Brodie
authors.affiliation: Falls and Balance Research Group, Neuroscience Research Australia, University of New South Wales, Barker Street, Randwick, Sydney, NSW, 2031, Australia.
authors.forename: Milou J M
authors.initials: MJ
authors.lastname: Coppens
authors.affiliation: Falls and Balance Research Group, Neuroscience Research Australia, University of New South Wales, Barker Street, Randwick, Sydney, NSW, 2031, Australia.
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Lord
authors.affiliation: Graduate School of Biomedical Engineering, University of New South Wales, Randwick, Sydney, NSW, Australia.
authors.forename: Nigel H
authors.initials: NH
authors.lastname: Lovell
authors.affiliation: Falls and Balance Research Group, Neuroscience Research Australia, University of New South Wales, Barker Street, Randwick, Sydney, NSW, 2031, Australia.
authors.forename: Yves J
authors.initials: YJ
authors.lastname: Gschwind
authors.affiliation: Graduate School of Biomedical Engineering, University of New South Wales, Randwick, Sydney, NSW, Australia.
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Redmond
authors.affiliation: Graduate School of Biomedical Engineering, University of New South Wales, Randwick, Sydney, NSW, Australia.
authors.forename: Michael Benjamin
authors.initials: MB
authors.lastname: Del Rosario
authors.affiliation: Graduate School of Biomedical Engineering, University of New South Wales, Randwick, Sydney, NSW, Australia.
authors.forename: Kejia
authors.initials: K
authors.lastname: Wang
authors.affiliation: Falls and Balance Research Group, Neuroscience Research Australia, University of New South Wales, Barker Street, Randwick, Sydney, NSW, 2031, Australia.
authors.forename: Daina L
authors.initials: DL
authors.lastname: Sturnieks
authors.affiliation: Falls and Balance Research Group, Neuroscience Research Australia, University of New South Wales, Barker Street, Randwick, Sydney, NSW, 2031, Australia.
authors.forename: Michela
authors.initials: M
authors.lastname: Persiani
authors.affiliation: Falls and Balance Research Group, Neuroscience Research Australia, University of New South Wales, Barker Street, Randwick, Sydney, NSW, 2031, Australia.
authors.forename: Kim
authors.initials: K
authors.lastname: Delbaere
mesh_terms: D000054:Acceleration; D000203:Activities of Daily Living; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003663:Decision Trees; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D008297:Male; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D058067:Wavelet Analysis
keywords: Falls; Gait analysis; Remote; Wavelet; Wearable devices