A heart source sudden death risk monitoring and early warning system and method based on multi-source signal collaborative analysis
By using multi-source signal collaborative processing and edge-cloud collaborative computing architecture, the problems of sudden drop in signal-to-noise ratio, missed detection and false alarm and insufficient battery life in wearable ECG monitoring are solved, and real-time, accurate and long-term early warning of sudden cardiac death is achieved.
Patent Information
- Authority / Receiving Office
- CN Β· China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHONGKE ZHIHE DIGITAL TECH (BEIJING) CO LTD
- Filing Date
- 2026-04-14
- Publication Date
- 2026-07-17
AI Technical Summary
Existing wearable ECG monitoring technologies have limitations in signal processing, system architecture, and early warning mechanisms, resulting in a sharp drop in signal-to-noise ratio, frequent missed detections and false alarms, insufficient battery life, and inadequate model generalization ability, making it impossible to achieve real-time, accurate, and long-term SCD early warning.
Employing multi-source signal collaborative processing technology, this system utilizes adaptive motion artifact filtering, power frequency notch filtering, and baseline drift correction for acceleration signals. Combined with a lightweight temporal neural network and a dynamic risk assessment engine, it constructs an edge-cloud collaborative computing architecture to achieve a closed-loop system for signal preprocessing, feature extraction, risk assessment, and model optimization.
It significantly improves the signal-to-noise ratio, reduces power consumption, extends battery life, enhances the accuracy and individual adaptability of early warnings, and forms a reliable and interpretable intelligent decision-making system, solving the problems of missed detections, false alarms, and insufficient battery life in existing technologies.
Smart Images
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