title: Comparison of real-life accidental falls in older people with experimental falls in middle-aged test subjects.
abstract: Falling is a common accident among older people. Automatic fall detectors are one method of improving security. However, in most cases, fall detectors are designed and tested with data from experimental falls in younger people. This study is one of the first to provide fall-related acceleration data obtained from real-life falls. Wireless sensors were used to collect acceleration data during a six-month test period in older people. Data from five events representing forward falls, a sideways fall, a backwards fall, and a fall out of bed were collected and compared with experimental falls performed by middle-aged test subjects. The signals from real-life falls had similar features to those from intentional falls. Real-life forward, sideways and backward falls all showed a pre impact phase and an impact phase that were in keeping with the model that was based on experimental falls. In addition, the fall out of bed had a similar acceleration profile as the experimental falls of the same type. However, there were differences in the parameters that were used for the detection of the fall phases. The beginning of the fall was detected in all of the real-life falls starting from a standing posture, whereas the high pre impact velocity was not. In some real-life falls, multiple impacts suggested protective actions. In conclusion, this study demonstrated similarities between real-life falls of older people and experimental falls of middle-aged subjects. However, some fall characteristics detected from experimental falls were not detectable in acceleration signals from corresponding heterogeneous real-life falls.
authors.affiliation: Department of Medical Technology, Institute of Biomedicine, University of Oulu, Oulu, Finland. maarit.kangas@oulu.fi
authors.forename: M
authors.initials: M
authors.lastname: Kangas
authors.forename: I
authors.initials: I
authors.lastname: Vikman
authors.forename: L
authors.initials: L
authors.lastname: Nyberg
authors.forename: R
authors.initials: R
authors.lastname: Korpelainen
authors.forename: J
authors.initials: J
authors.lastname: Lindblom
authors.forename: T
authors.initials: T
authors.lastname: Jämsä
mesh_terms: D000054:Acceleration; D000058:Accidental Falls / Q000517:prevention & control / Q000706:statistics & numerical data*; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology; D000465:Algorithms; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D018670:Monitoring, Ambulatory / Q000379:methods*; D004856:Postural Balance / Q000502:physiology*; D011187:Posture / Q000502:physiology; D011930:Reaction Time; D012016:Reference Values; D018570:Risk Assessment