AI-Driven Human-Computer Interaction and Intelligent Systems for Digital Health and Rehabilitation
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 May 2027 | Viewed by 3
Special Issue Editors
Interests: artificial intelligence; knowledge discovery; AI-assisted decision making process
Interests: computational neuroscience; medical image processing; wearable sports health
Interests: wearable computing; human motion decoding; exoskeleton
Special Issue Information
Dear Colleagues,
The rapid development of AI-enabled digital health technologies offers significant opportunities for improving health monitoring, rehabilitation training and athletic performance, all of which are enabled by advanced human–computer interaction. Data from electroencephalography, electromyography and medical imaging are increasingly being used to understand human states and provide support for the design of intelligent interaction systems and the formulation of personalized intervention strategies. However, these data are often multimodal, dynamic and highly personalized, presenting challenges for signal processing, model generalization and real-time decision-making.
This Special Issue welcomes theoretical, methodological and applied research that can advance intelligent sensing, human-centered computing and adaptive intervention technologies in health monitoring, rehabilitation and sports science. Interested topics include, but are not limited to, the processing of multimodal physiological signals; brain–computer interfaces based on neuroimaging and physiological signals; emotion and cognitive state recognition driven by AI; wearable and portable health monitoring and intervention systems; rehabilitation robots; etc. The goal of this Special Issue is to promote the development of innovative electronic, computing and intelligent systems to enhance real-time assessment, interaction and intervention capabilities for human health and performance, while encouraging the adoption of repeatable methods, conduct of detailed experimental validation, and conduct of translational applications in clinical, occupational and sports settings.
Dr. Zhiyuan Chen
Prof. Dr. Chunzhi Yi
Dr. Baichun Wei
Dr. Haiqi Zhu
Guest Editors
Manuscript Submission Information
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Keywords
- human–computer interaction
- digital health
- multimodal physiological signal processing
- AI-enabled health monitoring and rehabilitation
- wearable robotics
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