The invention belongs to the technical field of health monitoring, and particularly relates to a
senile dementia risk home monitoring method based on multi-
modal behavior analysis, which comprises the following specific steps: monitoring
human body postures in real time, analyzing repeated actions, synchronously early warning abnormal movement, and carrying out voice interaction operation through a built-in AI dialogue terminal; performing behavior, emotion and
physiology correlation modeling, executing
cognitive decline dynamic evaluation through cognitive function self-test, and judging a
risk level according to an analysis and
evaluation result; executing a multi-level early warning
mechanism based on the
risk level information, and automatically taking corresponding emergency measures; the threshold value is dynamically calibrated by integrating user
habit data, a closed-loop feedback mechanism is designed to realize
false alarm suppression, and a monthly health report is synchronously generated to assist a doctor in adjusting an intervention scheme. The problems that in a traditional monitoring mode, tiny behavior changes are difficult to capture, rescue is delayed due to subjective evaluation
hysteresis and passive response, the screening frequency is low, and the scene is limited can be solved.