Taiwan is currently undergoing an irreversible social transformation due to its aging population. According to recent statistics from the Ministry of Health and Welfare, there has been a rapid increase in the elderly demographic, particularly those over 65 years of age. This demographic shift poses critical challenges for public health and healthcare services, particularly in managing fall risks among the elderly. These risks significantly impact healthcare systems and affect the quality of life and autonomy of the elderly population. With the rapid progression of medical technology and information science, the application of artificial intelligence (AI) and deep learning in geriatric medicine is gaining prominence. These technologies are increasingly recognized for their effectiveness in analyzing the posture and gait of elderly people and identifying high-risk factors for falls. This research aims to integrate medical expertise with information technology by employing AI to assess the severity of sarcopenia and predict the risks of falls, thus improving health protection for the elderly. As age progresses, sarcopenia becomes prevalent among the elderly, characterized by decreased muscle mass and functional decline.