ECG Sensors and Signal Processing
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: 25 October 2026 | Viewed by 121
Special Issue Editor
Interests: AI/machine learning; biomedical engineering; non-invasive biosensing; causal inference; computational physiology; health disparities
Special Issue Information
Dear Colleagues,
This Special Issue focuses on recent advances in ECG sensors and signal processing that enable next-generation cardiovascular monitoring, diagnosis, and personalized care. Electrocardiography remains one of the most widely used and accessible tools in clinical practice, yet emerging sensor technologies and intelligent signal processing methods are rapidly expanding diagnostic potential beyond traditional waveform interpretation.
We invite original research and review articles addressing innovative ECG sensing platforms, wearable and non-contact acquisition systems, and multimodal integration with complementary physiological signals. Particular emphasis is placed on advanced signal processing, machine learning, and artificial intelligence approaches that enhance feature extraction, noise suppression, arrhythmia detection, and risk stratification across diverse populations.
Topics of interest include novel electrode materials and hardware design, robust preprocessing and artifact removal, deep learning-based ECG analysis, large-scale data analytics, and the clinical translation of intelligent ECG systems. Applications spanning remote monitoring, point-of-care diagnostics, population health, and digital therapeutics are especially encouraged.
By bringing together interdisciplinary contributions from biomedical engineering, data science, and clinical research, this Special Issue aims to highlight emerging methodologies and practical implementations that advance ECG-based sensing and analytics toward scalable, accurate, and equitable cardiovascular care.
Dr. Jianwei Zheng
Guest Editor
Manuscript Submission Information
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Keywords
- electrocardiography (ECG)
- ECG sensors
- signal processing
- wearable biosensors
- machine learning
- artificial intelligence
- arrhythmia detection
- cardiovascular monitoring
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