A Novel Multisensory-Rhythmic Intervention in Geriatric Rehabilitation

Linking From an Artificial-Intelligence Driven Assessment of Upper Extremity Motor Adaptation to a Novel Multisensory-Rhythmic Intervention in Geriatric Rehabilitation

Human performance takes shape from the dynamic interaction between person, environment, and task. Goal-directed action is a complex task, which requires the elderly to adapt their motor response according to the environment constraints and task requirements to accomplish the task goal. Among age-related problems, motor control deficits are often the main problems which restricts the frail elderly from maintaining independence for activities of daily living. Therefore, to preserve the quality of life, motor function of the elderly must be taken into consideration, including early detection of motor control problems and development of appropriate intervention strategy for persons with either healthy or pathological brain aging. Rhythmic skill training which is a new mode of dual tasks using rhythmic cueing as an external agent for facilitating an automatized motor task. During training, rhythmic skill training can provide multi-component of sensory stimulation, strengthen motor planning and optimize motor execution, therefore, it will improve the motor performance for the elderly or patients with mild cognitive impairment. In addition, the neuroplastic changes related to sensory processing, selective attention, or working memory demands through music rhythm training can facilitate the cognitive function for the elderly which is a current trend of geriatric rehabilitation. Moreover, the advantage of virtual reality is that it provides important information related to knowledge of result, which can induce better motor and cognitive training effects. Therefore, this research project will focus on assessing and intervening motor adaptation of upper extremity for the healthy elderly and patients with mild cognitive impairment. The first purpose of the project will analyze the difference in efficiency of responsive and predictive grasping motor adaptation among the healthy young adults, healthy elderly and patients with mild cognitive impairment through a test of perturbation-based of pinch-holding-up-activity, and use artificial intelligence for more accurate classification for the grasp pattern of healthy young adults, elderly and patients with mild cognitive impairment. The second one is to verify the effects of virtual-reality based rhythmic skill training system on the motor adaptation capability of upper limb and cognition for the elderly and patients with mild cognitive impairment.

Inclusion Criteria:

1. Montreal Cognitive Assessment (MoCA) score of 23 or higher,
2. Clinical Dementia Rating (CDR) of 0 (for normal subjects) or 1 (for mild cognitive impairment subjects),
3. Healthy young participants aged between 20-39 years, healthy older adults and mild cognitive impairment participants aged between 65-85 years,
4. No skeletal, muscular, or neurological problems in the upper limbs in the past year, and
5. Sufficient visual acuity to complete the tasks.

Exclusion Criteria:

• Any subjects with significant mental illness, central nervous system disorders, or medical history