Advanced Sensing and AI-Driven Technologies for Physiological Monitoring and Health Assessment
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: 1 December 2026 | Viewed by 217
Special Issue Editors
Interests: photoplethysmography (PPG) signal processing; electromyography (EMG) analysis; physiological sensing technologies; biomedical signal processing; wearable health monitoring; artificial intelligence in healthcare; cardiovascular disease detection
Special Issue Information
Dear Colleagues,
Recent advances in sensing technologies, wearable systems, and artificial intelligence are rapidly transforming physiological monitoring and digital healthcare. Modern biomedical sensors enable continuous and non-invasive monitoring of physiological signals such as photoplethysmography (PPG), electrocardiography (ECG), electroencephalography (EEG), and electromyography (EMG). These signals provide valuable insights into cardiovascular health, neurological activity, human motion, and overall physiological conditions.
Wearable sensing devices combined with advanced signal processing techniques allow real-time monitoring and early detection of health abnormalities. At the same time, machine learning and deep learning methods are increasingly being used to extract meaningful patterns from large-scale physiological datasets, improving diagnostic accuracy and enabling personalized healthcare solutions.
This Special Issue aims to bring together researchers working on innovative sensing technologies, wearable health monitoring systems, biomedical signal processing, and AI-driven health assessment methods. This Issue will focus on novel sensor designs, robust signal processing algorithms, multimodal physiological monitoring, and intelligent data analysis techniques.
We particularly encourage contributions related to wearable biosensors, physiological signal analysis, artifact reduction, feature extraction, and AI-based healthcare applications. The goal of this Special Issue is to highlight emerging technologies that enhance the reliability, scalability, and clinical applicability of modern physiological sensing systems.
Dr. Saad Abdullah
Dr. Syed Ghufran Khalid
Guest Editors
Manuscript Submission Information
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Keywords
- photoplethysmography (PPG) signal processing
- electromyography (EMG) analysis
- physiological sensing technologies
- biomedical signal processing
- wearable health monitoring
- artificial intelligence in healthcare
- cardiovascular disease detection
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