The aging physiological state of the elderly may lead to problems such as unstable gait, balance disorders, and falls. Previous research has confirmed that exercise training can help improve the physical function, quality of life, and reduce the risk of falls in the elderly. In order to achieve effective and continuous intervention training, somatosensory games have become a trend in recent years. Among them, the use of non-immersive virtual reality training methods not only provides training for the elderly, but also reduces the discomfort caused by the virtual environment; however, there are some limitations in clinical rehabilitation training methods, such as the lack of data-based evaluation and personalization. In order to solve the above problems, this research plan will use the inertial measurement unit as a tool for clinical monitoring and human movement assessment, and use artificial intelligence technology to evaluate and adjust the training plan according to its gait characteristics to achieve personalization Training and prevention strategies.
None
history of lower limb orthopedic surgery, ankylosing spondylitis, rheumatoid arthritis, osteoarthritis, and other medical joint diseases
Those who cannot communicate or follow instructions, and those with severe visual or hearing impairments
the neurological impairment or vestibular disorders, such as stroke, spinal cord injury, Meniere's syndrome.
Parallel
IMU-based balance training
Other interventionLeveraging AI technology to identify motion deficiencies, the experimental group will undergo IMU-based balance training
general health education or exercise training
Other interventiongeneral health education or exercise training
Static Standing Balance Test
Balance Assessments
Single Leg Standing Test
Balance Assessments
Five Times Sit to Stand Test
Functional Tests
Timed Up and Go Test
Functional Tests
Click on the lead sponsor to view all of their trials.
