Biomedical Imaging and Sensing Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".
Deadline for manuscript submissions: 20 December 2026 | Viewed by 100
Special Issue Editors
Interests: biomedical sensing and imaging
Interests: medical image analysis visualization; computer anatomical model; pattern recognition; computer graphics and vision; virtual reality and development computer aided surgery/diagnosis systems
Special Issue Information
Dear Colleagues,
Biomedical imaging and sensing technologies are playing an increasingly important role in modern healthcare and health management. Recent advances in imaging sensors, multimodal sensing platforms, computer vision, and machine learning have enabled the objective and non-invasive assessment of human physiology, behavior, and disease-related signs in both clinical and daily life settings. Beyond conventional diagnostic imaging, growing attention is being paid to sensing human motion, gait, activity patterns, body composition, and fatigue status, as these observable signals may contain important indicators for neurological disorders, cognitive decline, chronic disease progression, and overall health conditions. At the same time, the integration of wearable sensors, camera-based systems, and intelligent image/signal processing is opening new opportunities for early screening, continuous monitoring, personalized intervention, and remote healthcare delivery. These developments make biomedical imaging and sensing a timely and highly interdisciplinary research area that is of great significance to both academia and real-world practice.
This Special Issue aims to present and disseminate the latest advances in biomedical imaging and sensing applications, with a particular focus on innovative sensing technologies, image/video analysis, and practical systems for medical diagnosis support, health assessment, and human-centered monitoring. We welcome contributions addressing the full pipeline from sensor design and data acquisition to image/signal processing, multimodal fusion, machine learning, and deployment in clinical, community, home, and surveillance-related healthcare contexts. Topics of interest include, but are not limited to, the following: camera-based biomedical sensing; medical and healthcare image analysis; gait and motion analysis for disease screening and cognitive assessment; behavioral sensing for health monitoring; multimodal sensing systems; wearable and remote sensing technologies; person detection, tracking, and trajectory analysis for healthcare applications; biometric analysis with healthcare relevance; AI and deep learning for biomedical image/signal understanding; and real-world diagnostic or health-management support systems. Original research articles, review papers, and application-oriented studies that demonstrate methodological novelty and practical value are particularly encouraged.
Topics of interest include, but are not limited to the following:
- Biomedical image and video sensing.
- Medical diagnosis support, using imaging and sensing.
- Gait, motion, and behavioral analysis for healthcare.
- Cognitive function estimation and neurological disorder screening.
- Health monitoring, fatigue estimation, and body-state assessment.
- Multimodal sensing and sensor fusion.
- Wearable, remote, and camera-based health sensing systems.
- AI, computer vision, and deep learning for biomedical imaging and sensing.
- Person detection, tracking, and trajectory analysis for healthcare-related applications.
- Real-world clinical and health-management deployment studies.
Dr. Jiaqing Liu
Prof. Dr. Tomoko Tateyama
Guest Editors
Manuscript Submission Information
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Keywords
- biomedical imaging
- sensing applications
- medical diagnosis support
- healthcare monitoring
- gait-based analysis
- human motion understanding
- cognitive assessment
- neurological disease screening
- multimodal biomedical sensing
- wearable and camera-based sensing
- image and video analysis
- deep learning for healthcare
- intelligent sensing systems
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