This project integrates clinical physicalmental medical practice, medical engineering, information engineeringsocial welfare units, adopts cross-fieldsuses AI technology,builds an innovative artificial intelligence auxiliary evaluationtreatment system for dementia care based on cultural context. Establish an early intervention mechanism for early detection of dementia,establish measures to improve cognitive function, emotional state, socialdaily behavioral functions.

The trajectory parameters of the gait behavior detection devicethe 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 91.3384.62 respectively using the BPNN model for a small amount of game data The recognition rate of cognitive function, combining nostalgic featuresmolester features, can reach 75.76.

The progression of dementia is usually very slow,the early symptoms are often considered to be a normal aging phenomenontherefore 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 possibleseek medical treatment as soon as possible, the cost of future caremedical resources can be greatly reduced.

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