Development of AI assisted assessment and intervention system based on the culture contextualization for care of people with neurocognitive disoder.
Summary This project integrates clinical physical and mental medical practice, medical engineering, information engineering and social welfare units, adopts cross-fields and uses AI technology, and builds an innovative artificial intelligence auxiliary evaluation and treatment system for dementia care based on cultural context. Establish an early intervention mechanism for early detection of dementia, and establish measures to improve cognitive function, emotional state, social and daily behavioral functions.
The trajectory parameters of the gait behavior detection device and the MoCA classification result can get an accuracy rate of about 76.3%; using the BPNN model for emotion recognition of a small amount of physiological signals, the recognition rate can reach 91.33% and 84.62% respectively; using the BPNN model for a small amount of game data The recognition rate of cognitive function, combining nostalgic features and molester features, can reach 75.76%.
The progression of dementia is usually very slow, and the early symptoms are often considered to be a normal aging phenomenon and therefore ignored. As the course of the disease progresses, it will take 4 to 5 years to seek medical treatment for being unable to take care of daily life. The purpose of this system is to detect the dementia tendency of the elderly early. If the tendency to dementia can be detected as soon as possible and seek medical treatment as soon as possible, the cost of future care and medical resources can be greatly reduced.
Keyword Intelligent Information System Digital content and digital learning cosmetics and health care Interdisciplinary integration
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