Advanced Sensors and Signal Processing for Psychophysiological Monitoring
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: 15 November 2025 | Viewed by 104
Special Issue Editor
Interests: biomedical signals; psychophysiology; injury; electroencephalography; heart rate variability; machine learning for rehabilitation medicine
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, advancements in wearable sensors, contactless monitoring technologies, and signal processing have enhanced our capability to track psychophysiological states more accurately in real-world settings. From heart rate variability and skin conductance to neural and ocular biomarkers, the integration of sophisticated sensing systems has unveiled new horizons in understanding cognitive load, stress, fatigue, and emotional regulation. These advancements present significant potential for applications in healthcare, human performance, and adaptability technologies.
This Special Issue explores the latest advancements in sensor technologies and signal processing methodologies that enhance psychophysiological monitoring.
Key areas of focus include the following:
- Innovations in wearable and contactless sensors, including miniaturised and flexible bioelectronic systems, multimodal wearables, and passive sensing technologies.
- Machine learning methods for feature extraction, such as deep learning models for interpreting physiological signals, automated noise reduction techniques, and personalised calibration strategies.
- Multimodal data integration to improve reliability and interpretation, including sensor fusion strategies combining physiological, behavioural, and contextual data.
- Advances in real-time processing and edge computing, enabling fast, low-latency analysis for continuous monitoring applications.
- Novel signal processing techniques, such as adaptive filtering, wavelet transforms, and graph-based methods for detecting subtle physiological changes.
- Validation studies in controlled and naturalistic settings, addressing challenges in terms of the accuracy, usability, and generalisability of psychophysiological sensors.
- Applications in mental health, cognitive workload assessment, human–computer interaction, and clinical interventions, showcasing how these technologies are reshaping research and practice.
This Special Issue, bridging engineering, neuroscience, and applied physiology, highlights emerging solutions that extend the boundaries of real-time and continuous monitoring. Wearable sensors in particular continue to enhance psychophysiological monitoring by offering continuous, unobtrusive, and high-resolution data streams that deepen our understanding of human physiology in dynamic settings.
We welcome contributions that advance the field via novel sensor designs, enhanced signal processing algorithms, and practical applications across various domains. By bringing together interdisciplinary perspectives, this Special Issue aims to define the state of the art and pave the way for future innovations in psychophysiological sensing.
Dr. Yvonne Tran
Guest Editor
Manuscript Submission Information
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Keywords
- innovations in wearable and contactless sensors, including miniaturised and flexible bioelectronic systems, multimodal wearables, and passive sensing technologies
- machine learning methods for feature extraction, such as deep learning models for interpreting physiological signals, automated noise reduction techniques, and personalised calibration strategies
- multimodal data integration to improve reliability and interpretation, including sensor fusion strategies combining physiological, behavioural, and contextual data
- advances in real-time processing and edge computing, enabling fast, low-latency analysis for continuous monitoring applications
- novel signal processing techniques, such as adaptive filtering, wavelet transforms, and graph-based methods for detecting subtle physiological changes
- validation studies in controlled and naturalistic settings, addressing challenges in terms of the accuracy, usability, and generalisability of psychophysiological sensors
- applications in mental health, cognitive workload assessment, human–computer interaction, and clinical interventions, showcasing how these technologies are reshaping research and practice
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