A Self-Powered Heart Rate Monitoring System for Intelligent Diagnosis of Cardiovascular Diseases

To address the limitations of traditional heart rate monitoring systems in energy supply, continuous monitoring, and integration with intelligent diagnostics, this paper proposes a self-powered heart rate monitoring system for intelligent cardiovascular disease diagnosis. The system employs a piezoelectric energy harvester to convert mechanical energy generated by human pressing into electrical energy, which, through an energy management module, powers a low-power ECG acquisition and transmission unit, enabling continuous heart rate monitoring without reliance on external batteries. Hardware design utilizes fast-response, low-power components to minimize overall energy consumption. On the signal processing side, an intermittent sampling approach combined with backend data processing achieves efficient data compression and intelligent analysis. Both theoretical simulations and practical experiments validate the system’s monitoring performance under ambient energy supply conditions. This system provides a feasible pathway for future integration of physiological signal acquisition with artificial intelligence algorithms to enable intelligent early diagnosis of cardiovascular diseases, holding significant clinical and application prospects.