Fall Detection and Prevention for the Elderly: A Review of Trends and Challenges
Open Access
- 1 January 2013
- journal article
- review article
- Published by Walter de Gruyter GmbH in International Journal on Smart Sensing and Intelligent Systems
- Vol. 6 (3), 1230-1266
- https://doi.org/10.21307/ijssis-2017-588
Abstract
It is of little surprise that falling is often accepted as a natural part of the aging process. In fact, it is the impact rather than the occurrence of falls in the elderly, which is of most concern. Aging people are typically frailer, more unsteady, and have slower reactions, thus are more likely to fall and be injured than younger individuals. Typically, research and industry presented various practical solutions for assisting the elderly and their caregivers against falls via detecting falls and triggering notification alarms calling for help as soon as falls occur in order to diminish fall consequences. Furthermore, fall likelihood prediction systems have been emerged lately based on the manipulation of the medical and behavioral history of elderly patients in order to predict the possibility of falls occurrence. Accordingly, response from caregivers may be triggered prior to most fall occurrences and accordingly prevent falls from taking place. This paper presents an extensive review for the state-of-the- art trends and technologies of fall detection and prevention systems assisting the elderly people and their caregivers. Furthermore, this paper discusses the main challenges, facing elderly fall prevention, along with suggestions for future research directions.Keywords
This publication has 33 references indexed in Scilit:
- Home geriatric physiological measurementsPhysiological Measurement, 2012
- Wireless Sensors Network Based Safe Home to Care Elderly People: Behaviour DetectionProcedia Engineering, 2011
- Evaluation of waist-mounted tri-axial accelerometer based fall-detection algorithms during scripted and continuous unscripted activitiesJournal of Biomechanics, 2010
- A Multisensor System for High Reliability People Fall Detection in Home EnvironmentLecture Notes in Electrical Engineering, 2009
- A comparison of automatic fall detection by the cross-product and magnitude of tri-axial accelerationPhysiological Measurement, 2009
- Comparison of low-complexity fall detection algorithms for body attached accelerometersGait & Posture, 2008
- A daily behavior enabled hidden Markov model for human behavior understandingPattern Recognition, 2008
- A new accelerometric method to assess the daily walking practiceInternational Journal of Obesity, 2002
- System architecture directions for networked sensorsACM SIGPLAN Notices, 2000
- Prevention of Falls among the ElderlyThe New England Journal of Medicine, 1989