Cross-cohort evaluation of machine learning approaches to fall detection from accelerometer data

Aneta Lisowska, Alison O’Neil, Ian Poole

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Falls in seniors can lead to serious physical and psychological consequences. A fall detector can allow a fallen person to receive medical intervention promptly after the incident. The accelerometer data from smartphones or wearable devices can be used to detect falls without serious privacy intrusion. Common machine learning approaches to fall detection include supervised and novelty based methods. Previous studies have found that supervised methods have superior performance when tested on participants from the population cohort resembling the one they were trained on. In this study, we investigate if the performance remains superior when they are tested on a distinctly different population cohort. We train the supervised algorithms on data gathered using a wearable Silmee device (Cohort 1) and test on smartphone data from a publicly available data set (Cohort 2). We show that the performance of the supervised methods decreases when they are tested on distinctly different data, but that the decrease is not substantial. Novelty based fall detectors have better performance, suggesting that novelty based detectors might be better suited for real life applications.
Original languageEnglish
Title of host publicationHEALTHINF 2018 - 11th International Conference on Health Informatics, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018
EditorsR. Zwiggelaar, H. Gamboa, A. Fred, S. Bermudez i Badia
PublisherSciTePress
Pages77-82
ISBN (Electronic)9789897582813
DOIs
Publication statusPublished - 2018
Externally publishedYes
Event11th International Conference on Health Informatics, HEALTHINF 2018 - Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018 - Funchal, Madeira, Portugal
Duration: 19 Jan 201821 Jan 2018

Conference

Conference11th International Conference on Health Informatics, HEALTHINF 2018 - Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018
Country/TerritoryPortugal
CityFunchal, Madeira
Period19/01/1821/01/18

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