A multifactorial fall risk assessment system for older people utilizing a low-cost, markerless Microsoft Kinect

Abstract

Falls among older people are a major health concern. This study aims to develop a multifactorial fall risk assessment system for older people using a low-cost, markerless Microsoft Kinect. A Kinect-based test battery was designed to comprehensively assess major fall risk factors. A follow-up experiment was conducted with 102 older participants to assess their fall risks. Participants were divided into high and low fall risk groups based on their prospective falls over a 6-month period. Results showed that the high fall risk group performed significantly worse on the Kinect-based test battery. The developed random forest classification model achieved an average classification accuracy of 84.7%. In addition, the individual’s performance was computed as the percentile value of a normative database to visualise deficiencies and targets for intervention. These findings indicate that the developed system can not only screen out ‘at risk’ older individuals with good accuracy, but also identify potential fall risk factors for effective fall intervention.

Practitioner summary: Falls are the leading cause of injuries in older people. We newly developed a multifactorial fall risk assessment system for older people utilising a low-cost, markerless Kinect. Results showed that the developed system can screen out ‘at risk’ individuals and identify potential risk factors for effective fall intervention.

Keywords:

• Ageing
• fall risk
• multifactorial assessment
• Kinect sensor
• machine learning
• women

Acknowledgments

Authors would like to thank ‘Milmaru welfare town’ and ‘Chung-cheong bukdo sliver welfare center’ for helping recruit older participant and providing space for experimentation. We also thank all volunteer participants for their active participation and cooperation in this experiment.

Ethical approval

The study was ethically approved by KAIST Institutional Review Board (IRB No: KH2020-015).

Informed consent

Each participant gave written informed consent prior to participation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

This work was supported by the ICT R&D innovative voucher support program supervised by the Institute for Information & communications Technology Promotion [IITP20210019800012003] and the Basic Science Research Program through the National Research Foundation of Korea [NRF2017R1C1B2006811; NRF2022R1F1A1061045].