Authors (including presenting author) :
Choi YWR(1)(2), Ng TH(1)(2), Po YTA(1)(2), Kong SBB(1), Ku WNH(1)
Affiliation :
(1) Occupational Therapy department, Yan Chai Hospital (2) ICDS, Yan Chai Hospital
Keyword 1: :
AI technology
Keyword 2: :
Community rehabilitation
Keyword 3: :
Occupational Therapy
Keyword 4: :
Fall risk assessment
Keyword 5: :
Health Qigong
Keyword 6: :
LiFE program
Introduction :
Falls among older adults have long been a significant concern in occupational therapy, especially in community settings. Although there has been substantial research on fall prevention in the past, no service provision has utilized AI technology to manage fall risk in the community. By integrating and utilizing AI technology, Booguu, a belt with motion sensor, occupational therapists can provide real-time fall risk insights to patients, and provide accurate and personalized treatments including Booguu suggested balance and strength training program, BaDuanjin Health Qigong, and the LiFE program to improve overall balance, strength, and home safety. A pilot study was conducted from 1 October 2025 to 31 December 2025. Results indicated a significant enhancement in functional strength and overall balance, as well as a reduction in the fear of falling, thus increasing participation activities of daily living (ADL) and instrumental activities of daily living task (iADL).
Objectives :
To investigate the efficacy of using AI technology in fall prevention management in community patients.
Methodology :
A 12-week study period was conducted. Inclusion criteria were: i) older adults aged 65 and above who admitted to YCH due to fall, ii) able to ambulate 6 meters either with or without a walking aid; iii) able to communicate and understand instructions and procedures. Using the BooGuu, AI-based fall risk assessment and fall prediction, to assess three main areas: balance, strength, and home environment safety. Pre-and-post AI based assessment will be compared to conduct the improvement of risk factors. Outcome measure consists MBI, Fall Efficacy Scale (FES) and patient’s satisfactory questionnaire (SAQ) related to satisfaction of using AI technology.
Result & Outcome :
The study recruited 10 older adults (5 females and 5 males) with risk of falls from the ICDS group (8 orthopedics and 2 stroke patients) over the three months period. The statistics reveal a significant improvement in balance and lower limb strength, reflected by the ability to complete indoor and outdoor community functional mobility. The FES scores also improved significantly from high to moderate fears of falling (60–75/100) to low fear of falling (80–95/100), reflected by the increased confidence and participation in daily living and community living. This improvement not only indicated a reduction in the fear of falling but also suggested enhanced functional strength and overall balance. Additionally, results from SAQ showed that patients were more aware of their own weaknesses via AI based assessment system, thus fostering a proactive approach to training and compliance. Limitations include a small sample size and a wide range of health conditions. Future directions will involve a larger sample size and a focus on specific health conditions to improve the efficacy of application of AI technology.
