Development of a Fall Prevention Device for Older Persons

Abstract

Purpose The ever-increasing ageing population has raised awareness globally. The desire to live independently has resulted in consequences for them and society as well. The deterioration of health among older persons commonly leads to an increased risk of falling. Enabling environments for older persons can be created, easing the social challenge of preparing for an ageing society while improving their quality of life in their golden years. Technology solutions have been a game-changer in supporting families that have become caretakers for ageing relatives by default, bringing peace of mind. Fall detection systems represent one of the assistive technologies for older persons, as they are useful for offering immediate assistance in emergency events. Despite the fact that the usage of fall detection devices is statistically low in Malaysia, they have been known to save lives (Bourke et al., 2010). This study aims to improve such devices by incorporating a balance monitoring system, delivering better care for older persons. Rather than simply detecting falls, the proposed system will monitor balance instability, alerting the user to predict future falls and therefore serving as a fall prevention device. Method A fuzzy logic-based fall prevention algorithm has been developed to be integrated with fall detection devices, where two vital variables to balance are selected as the inputs for the system: Limit of Stability (LOS) and Degree of Sway (DOS). These two inputs will deliberate the balance instability of the user and analyse the category, whether it is low, medium, or high, signified as the fall risk level (Figure 1). Results and Discussion This study demonstrates a fall prevention algorithm to improve the accuracy of fall detection systems while monitoring balance instability. The system will notify the user if there are movement abnormalities to avoid falling or prolonged loss of balance. The results include simulations of the user’s movement with an indicator displaying their fall risk level alongside other health-related data. Analysing balance instability among older persons is an important aspect of their daily monitoring to be aware of their conditions periodically. This will help clinicians and physical therapists to provide proper rehabilitation if needed. The enhanced fall detection and balance monitoring can bridge the gap between family members’ concerns and one’s desire to stay independent. The proposed fall prevention system can increase safety in daily life; encouraging older persons to practise active ageing.

References

Bourke, A. K., Van de Ven, P., Gamble, M., O’connor, R., Murphy, K., Bogan, E., McQuade, E., Finucane, P., ÓLaighin, G. & Nelson, J. (2010). Evaluation of waist-mounted tri-axial accelerometer based fall-detection algorithms during scripted and continuous unscripted activities. Journal of Biomechanics, 43(15), 3051-3057.

https://doi.org/10.1016/j.jbiomech.2010.07.005

Keywords: fall detection, fall prevention, balance, assistive technology, older persons

Address: Malaysian Research Institute on Ageing, Universiti Putra Malaysia, Malaysia

Email: kawthar.ar@gmail.com

Acknowledgement This study was funded by the Matching Grant between Universiti Putra Malaysia-Kyushu Institute of Technology (UPM-KYUTECH), titled "Fall and Balance Monitoring for Older Persons" (Grant number: 9300464).