The invention relates to the technical field of health monitoring, in particular to a cardiovascular
disease high-risk group
health data monitoring method based on
the Internet of Things, which comprises the following steps: acquiring health
equipment state and activity records, analyzing health state trend, extracting abnormal fluctuation frequency and duration, collecting node environment parameters and
signal quality, screening nodes meeting conditions, and determining the
health data of cardiovascular
disease high-
risk groups. According to the invention, through continuous acquisition and
time sequence analysis of the multi-source
health data, dynamic mastering of multi-dimensional physiological indexes is realized, and the health monitoring
recovery path and the synchronization node configuration table are obtained. Abnormal fluctuation screens and focuses key risk parameters according to frequency and duration, monitoring nodes complete adaptive adjustment according to
signal and environment matching, monitoring paths are optimized according to
signal delay and fluctuation characteristics,
information transmission synchronization accuracy is guaranteed, the data
utilization rate and decision-making precision are improved, and the real-time performance and continuity of cardiovascular risk monitoring are enhanced.