Biological Signal Processing Technologies for Heart Disease Prediction and Diagnosis

Dear Colleagues,

This Special Issue, entitled “Biological Signal Processing Technologies for Heart Disease Prediction and Diagnosis”, highlights modern engineering solutions that advance the acquisition and interpretation of cardiovascular biosignals. In the era of wearable sensors, implanted electrotherapy devices, and AI-enhanced analytics, biological signal processing is becoming essential for early detection and precise management of heart disease. This issue focuses on approaches that merge biomedical engineering, data science, and clinical practice to improve diagnostic accuracy and support timely therapeutic decisions.

The aims of the issue include presenting innovative methods for processing ECG, PCG, PPG, and impedance signals; machine-learning models for predicting adverse cardiac events; and multimodal strategies for comprehensive assessment of cardiac function. Special emphasis is placed on technologies used in implanted electrotherapy devices—such as pacemakers and ICDs—including advanced algorithms capable of detecting arrhythmias or early signs of heart-failure decompensation based on intracardiac and physiological signals. Studies on telemedicine platforms, remote monitoring systems, and continuous home-based surveillance of cardiovascular status are also encouraged.

The scope welcomes interdisciplinary contributions that demonstrate practical applicability, clinical relevance, and the potential to shape next-generation tools for heart-disease prediction, diagnosis, and long-term management.

Prof. Dr. Maciej Sterliński
Dr. Ewa Świerżyńska-Wodarska
Guest Editors

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