title: Disentangling the health benefits of walking from increased exposure to falls in older people using remote gait monitoring and multi-dimensional analysis.
abstract: Falls and physical deconditioning are two major health problems for older people. Recent advances in remote physiological monitoring provide new opportunities to investigate why walking exercise, with its many health benefits, can both increase and decrease fall rates in older people. In this paper we combine remote wearable device monitoring of daily gait with non-linear multi-dimensional pattern recognition analysis; to disentangle the complex associations between walking, health and fall rates. One week of activities of daily living (ADL) were recorded with a wearable device in 96 independent living older people prior to completing 6 months of exergaming interventions. Using the wearable device data; the quantity, intensity, variability and distribution of daily walking patterns were assessed. At baseline, clinical assessments of health, falls, sensorimotor and physiological fall risks were completed. At 6 months, fall rates, sensorimotor and physiological fall risks were re-assessed. A non-linear multi-dimensional analysis was conducted to identify risk-groups according to their daily walking patterns. Four distinct risk-groups were identified: The Impaired (93% fallers), Restrained (8% fallers), Active (50% fallers) and Athletic (4% fallers). Walking was strongly associated with multiple health benefits and protective of falls for the top performing Athletic risk-group. However, in the middle of the spectrum, the Active risk-group, who were more active, younger and healthier were 6.25 times more likely to be fallers than their Restrained counterparts. Remote monitoring of daily walking patterns may provide a new way to distinguish Impaired people at risk of falling because of frailty from Active people at risk of falling from greater exposure to situations were falls could occur, but further validation is required. Wearable device risk-profiling could help in developing more personalised interventions for older people seeking the health benefits of walking without increasing their risk of falls.
authors.affiliation: Neuroscience Research Australia, UNSW, Randwick, Sydney, Australia.
authors.forename: Matthew A
authors.initials: MA
authors.lastname: Brodie
authors.forename: Yoshiro
authors.initials: Y
authors.lastname: Okubo
authors.forename: Janneke
authors.initials: J
authors.lastname: Annegarn
authors.forename: Rainer
authors.initials: R
authors.lastname: Wieching
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Lord
authors.forename: Kim
authors.initials: K
authors.lastname: Delbaere
mesh_terms: D000058:Accidental Falls; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005684:Gait; D006801:Humans; D007342:Insurance Benefits; D008297:Male; D008991:Monitoring, Physiologic / Q000295:instrumentation / Q000379:methods*; D058998:Remote Sensing Technology / Q000295:instrumentation / Q000379:methods*; D018570:Risk Assessment; D000076251:Wearable Electronic Devices