Key result
AI-driven multi-lead ECG accurately detects PVCs and estimates cuffless BP for early cardiovascular detection.
Why the study?
Does an AI-driven multi-lead ECG and PPG monitoring system accurately detect PVCs and estimate blood pressure for remote health management?
Does an AI-driven multi-lead ECG and PPG monitoring system accurately detect PVCs and estimate blood pressure for remote health management?
An AI-enhanced multi-lead ECG and PPG monitoring system deployed on an embedded platform demonstrates potential for real-time PVC detection and cuffless blood pressure estimation in remote healthcare.
Supports AI ECG-PPG development for remote monitoring; leaves open prospective validation before clinical use.
This study introduces an AI-driven multi-lead ECG real-time monitoring system designed for cardiovascular disease detection and blood pressure estimation, integrated within the framework of smart healthcare. By utilizing deep learning techniques, particularly Convolutional Neural Networks (CNNs), the system accurately detects Premature Ventricular Contractions (PVCs) from multi-lead ECG signals, significantly improving diagnostic precision. Additionally, it implements a cufftess blood pressure estimation method by combining ECG and photo-plethysmography (PPG) signals through Pulse Transit Time (PTT) features. The system is deployed on the Nvidia Jetson Nano embedded platform, offering real-time processing, low power consumption, and continuous monitoring, which is ideal for remote health management. Experimental results highlight its ability to enhance early detection of cardiovascular conditions, showcasing its integration within smart healthcare systems to support personalized health management and remote monitoring.
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Fang et al. (2025) studied Cardiovascular disease. AI-driven multi-lead ECG real-time monitoring system was evaluated on Detection of Premature Ventricular Contractions (PVCs) and cuffless blood pressure estimation. An AI-driven multi-lead ECG monitoring system using CNNs accurately detected Premature Ventricular Contractions and estimated cuffless blood pressure to enhance early cardiovascular disease detection.
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