Sensitivity and false alarm rate of a fall sensor in long-term fall detection in the elderly

Document identifier: oai:DiVA.org:ltu-7740
Access full text here:10.1159/000362720
Keyword: Medical and Health Sciences, Health Sciences, Physiotherapy, Medicin och hälsovetenskap, Hälsovetenskaper, Sjukgymnastik, Accelerometer, Fall detector, Frequent faller, Older people, Specificity, Fysioterapi, Centre - eHealth Innovation Centre (EIC), Centrumbildning - Centrum för Innovation och eHälsa (EIC)
Publication year: 2015
Relevant Sustainable Development Goals (SDGs):
SDG 3 Good health and wellbeing
The SDG label(s) above have been assigned by OSDG.ai

Abstract:

Background: About a third of home-dwelling older people fall each year, and institutionalized older people even report a two- or threefold higher rate for falling. Automatic fall detection systems have been developed to support the independent and secure living of the elderly. Even though good fall detection sensitivity and specificity in laboratory settings have been reported, knowledge about the sensitivity and specificity of these systems in real-life conditions is still lacking. Objective: The aim of this study was to evaluate the long-term fall detection sensitivity and false alarm rate of a fall detection prototype in real-life use. Methods: A total of 15,500 h of real-life data from 16 older people, including both fallers and nonfallers, were monitored using an accelerometry-based sensor system with an implemented fall detection algorithm. Results: The fall detection system detected 12 out of 15 real-life falls, having a sensitivity of 80.0%, with a false alarm rate of 0.049 alarms per usage hour with the implemented real-time system. With minor modification of data analysis the false alarm rate was reduced to 0.025 false alarms per hour, equating to 1 false fall alarm per 40 usage hours. Conclusion: These data suggest that automatic accelerometric fall detection systems might offer a tool for improving safety among older people.

Authors

Maarit Kangas

Department of Medical Technology, Institute of Biomedicine, Oulu Deaconess Institute
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Raija Korpelainen

Department of Medical Technology, Institute of Biomedicine, Oulu Deaconess Institute
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Irene Vikman

Luleå tekniska universitet; Hälsa och rehabilitering
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Lars Nyberg

Luleå tekniska universitet; Hälsa och rehabilitering
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Timo Jämsä

Department of Medical Technology, Institute of Biomedicine, Oulu Deaconess Institute
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