Development of Artificial Intelligence Innovation for Assessing Fall Risk Using Clinical Neurological Studies With Transcranial Magnetic Stimulation and Quantitative Sensory Testing in the Thai Elderly
Development of Artificial Intelligence Innovation for Assessing Fall Risk Using Clinical Neurological Studies With Transcranial Magnetic Stimulation and Quantitative Sensory Testing in the Thai Elderly
The elderly are at high risk of falls due to neurophysiological changes, such as motor and sensory impairment, that occur with aging. The incidence of falls in older adults is high, with approximately 30% of adults over the age of 65 falling at least once per year. Falls can lead to serious consequences such as fractures, hospitalization, and loss of independence. The changes in neurophysiology have also been found to decrease balance control in aging people, leading to postural instability. It is well-known that postural balance is influenced by sensory inputs, including touch, proprioception, vision, and vestibular, as well as motor output such as motor controls. Impairments in these systems contribute to postural instability and an increased risk of falling in the elderly.
The data collection will be arranged in the same order. Practice trials will be provided before the start of the data collection. The entire data collection session will take approximately 90 minutes. Data collection will be conducted for both the baseline and the 3-month follow-up.
The data collection will include:
Inclusion Criteria:
1) Male and female individuals aged 65-80 years.
Exclusion Criteria: