About this trial
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.
Eligibility criteria
Qualifiers
None
Disqualifiers
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.
Trial design
Treatments tested in this trial
- IMU-based balance training
- general health education or exercise training