Falls are a serious issue among Hong Kong's elderly. Approximately one in five community-dwelling elderly aged 65 or above has experienced a fall, placing a great strain on medical and healthcare systems. To proactively address health challenges brought by an ageing population, The Hong Kong Polytechnic University (PolyU) Department of Rehabilitation Sciences has, since January last year, partnered with multiple community groups to launch the "Better Ageing in Community Campaign", using the Department's artificial intelligence (AI) technology to conduct fall risk screening for the elderly. During the first phase, nearly 900 elderly residents on Hong Kong Island were assessed, with 26% identified as high-risk individuals. To date, over 100 attendants have received 12-week fall prevention training from the University. The PolyU team plans to expand the project to Kowloon district and establish a large-scale elderly health database, benefitting more people with the aid of an enhanced AI model.
A sharing session was held today, attended by Mr Chris SUN, Secretary for Labour and Welfare; The Hon. Tommy CHEUNG, Executive Council Member; The Hon. SHIU Ka-fai, Legislative Council Member, from the Government of the Hong Kong Special Administrative Region (HKSAR) of the People's Republic of China; Dr Roy CHUNG, Honorary Chairman of the PolyU Court; Prof. Christopher CHAO, Senior Vice President (Research and Innovation); Prof. Marco PANG, Head of the Department of Rehabilitation Sciences; and Prof. Amy FU, Associate Head of the Department, from PolyU. The session also included various district officers, district councillors, partner organisation representatives, students and elderly participants, to review the first-phase achievements and look ahead to future developments.
Mr Chris Sun stated, "Daily outings are often a challenge for elderly persons whose physical functions are gradually declining. The 'Better Ageing in Community Campaign' demonstrates admirable thoughtfulness by addressing the issue of fall prevention among elderly persons, thereby reducing the risks they face in daily life. The Government also places great emphasis on making good use of gerontechnology to enhance the quality of life for elderly persons. It is planning to launch a pilot scheme to install smart detection devices in 300 high-risk caregiver households, enabling caregivers and/or care recipients to receive timely and appropriate assistance in case of home accidents through the use of technology."
Prof. Christopher Chao remarked, "Artificial intelligence offers a crucial direction for global research development. PolyU is committed to applying AI technology in healthcare, rehabilitation therapy and primary healthcare in communities, while promoting interdisciplinary research and translating research outcomes into practical applications that benefit society. This project is not only a community healthcare initiative but also an exemplar of the University's research outcomes being put into practice. In the future, PolyU will continue to strengthen its research in AI, big data and smart healthcare, working with all sectors of society to promote more innovative projects, enhance citizens' quality of life and promote healthy ageing."
Since January last year, the faculty of the PolyU Department of Rehabilitation Sciences has led physiotherapy and occupational therapy students to conduct fall risk screening for 891 eligible elderly residents on Hong Kong Island, including the "walking speed test" and the "sit-to-stand test". The team successfully identified 235 elderly individuals with higher fall risk, representing approximately 26% of participants and arranged for them to attend 12-week fall prevention exercise training classes provided by the Department. The elderly participants responded enthusiastically, and generally agreed that appropriate exercise helps strengthen muscles and better enables them to cope with the demands of daily life.
The project team previously conducted telephone interviews with elderly participants of the fall risk screening and found that approximately 20% had fallen in the past year, with half of them requiring medical attention. Analysis also revealed that the "walking speed test" and the "sit-to-stand test" can effectively predict fall risk in elderly men, while fall risk in elderly women is not only related to the walking speed test results but also their weight-to-height ratio.
Prof. Marco Pang and Prof. Amy Fu, who led the project, stated that the research team plans to expand the project to Kowloon and establish a large-scale elderly health database, while further optimising AI model training and developing more personalised and effective fall prevention solutions. At the same time, the team will strengthen collaboration with community organisations, the social welfare sector and the healthcare sector to extend AI screening to more communities, with the aim of reducing pressure on the healthcare system in the long term and enhancing elderly health and support for community elderly care.
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The PolyU Department of Rehabilitation Sciences leverages AI technology to conduct fall risk screening for the elderly. |
The elderly who have participated in the fall prevention training by PolyU Department of Rehabilitation Sciences responded enthusiastically, and generally agreed that appropriate exercise helps strengthen muscles and better enables them to cope with the demands of daily life. |
