Sensors for Neuroimaging and Cardiovascular Monitoring
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: 20 March 2026 | Viewed by 55
Special Issue Editors
Interests: neural control of movement; functional near-infrared spectroscopy (fNIRS); gait and balance in aging and neurological disorders; cardiovascular-cognitive interactions; wearable technologies for movement monitoring; rehabilitation and therapeutic interventions
Interests: eHealth; mobile health; signal processing; pattern recognition; biomechanical and physiological parameter extraction and analysis; statistical analysis; machine learning/artificial intelligence techniques for eHealth applications; ICT-based intelligent solutions for chronic disease (cardiovascular diseases); wearable devices (ECG sensors, accelerometer sensors, etc.)
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Special Issue Information
Dear Colleagues,
Advances in sensor technology have revolutionized our understanding of brain and cardiovascular function by enabling real-time, non-invasive, and high-resolution monitoring. These sensors play a crucial role in early diagnosis, disease management, and therapeutic interventions in neurological and cardiovascular disorders. As the demand for precision healthcare grows, there is a pressing need to develop innovative, sensitive, and wearable sensor systems capable of capturing complex physiological signals under both clinical and real-world conditions. This Special Issue welcomes original research and reviews on the latest developments in sensor technologies aimed at neuroimaging and cardiovascular monitoring, with a focus on their design, application, and translational potential.
This Special Issue, “Sensors for Neuroimaging and Cardiovascular Monitoring”, aligns closely with the core scope of the journal Sensors, which focuses on the design, development, characterization, and application of sensing technologies across various domains. This Special Issue contributes to the field by highlighting innovative sensor systems and methodologies used to detect, monitor, and interpret physiological signals from the brain and cardiovascular system [1−3].
Moreover, given the increasing demand for non-invasive, real-time, and wearable sensing solutions in healthcare, the development of advanced biosensors, imaging sensors, and multimodal platforms directly supports the journal’s emphasis on cutting-edge sensor applications in biomedical engineering and personalized medicine. Furthermore, this issue encourages interdisciplinary contributions, combining sensor hardware, signal processing algorithms, and translational applications, all of which are integral to the journal’s aim of advancing sensor-based technologies for real-world challenges.
References:
[1] Bishnoi, A., Hu, Y., & Hernandez, M. E. (2024). Perturbation walking effects on prefrontal cortical activation and walking performance in older women with and without osteoarthritis: a FNIRS study. Frontiers in Aging Neuroscience, 16, 1403185. https://doi.org/10.3389/fnagi.2024.1403185
[2] Dogan, A., Bishnoi, A., Sowers, R. B., & Hernandez, M. E. (2025). Continuous Heart Rate Recovery Monitoring With ECG Signals From Wearables: Identifying Risk Groups in the General Population. IEEE Journal of Biomedical and Health Informatics, 29(8), 5493–5502. https://doi.org/10.1109/JBHI.2025.3550092
[3] Holtzer, R., Izzetoglu, M., Chen, M., & Wang, C. (2019). Distinct fNIRS-Derived HbO2 Trajectories during the Course and over Repeated Walking Trials under Single-and Dual-Task Conditions: Implications for Within Session Learning and Prefrontal Cortex Efficiency in Older Adults. Journals of Gerontology - Series A Biological Sciences and Medical Sciences, 74(7), 1076–1083. https://doi.org/10.1093/gerona/gly181
Dr. Alka Bishnoi
Dr. Giovanna Sannino
Guest Editors
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Keywords
- neuroimaging sensors
- cardiovascular monitoring
- wearable biosensors
- functional near-infrared spectroscopy (fNIRS)
- electroencephalography (EEG)
- electrocardiography (ECG)
- multimodal sensing
- signal processing in biomedical sensors
- point-of-care diagnostics
- smart health technologies
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