The integration of artificial intelligence (AI) and medical signal processing has revolutionized disease detection and prediction through intelligent analysis of biosignals such as ECG, glucose levels, and neural activity. This special session focuses on cutting-edge AI algorithms for processing biomedical signals and their applications in early diagnosis of cardiovascular, endocrine, and neurological disorders. Additionally, we explore challenges and innovations in deploying these technologies in wearable devices and brain-computer interfaces (BCIs). We invite contributions on AI model optimization, multimodal signal fusion, edge computing, and clinical validation to advance precision medicine and portable health monitoring solutions.

Track Committee
• Track Chair
Assoc. Prof. Peng Zhang, Huazhong University of Science and Technology
• Technical Committee
Assoc. Prof. Zhiwei Wang, Huazhong University of Science and Technology
Assistant Prof. Yu Cao, University of Leeds
Assistant Prof. Qiuxia Lai, Communication University of Chin
Fan Lin; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
Dr. Xiao Li, Hubei University of Technology
Dr. Hailong Huang, Zhongnan Hospital of Wuhan University
Dr. Luyao Chen, Beijing Academy of Artificial Intelligence
Liguo Yu, Wuhan Hospital of Traditional Chinese and Western Medicine

Topics
• AI Algorithms for Medical Signal Analysis
Deep learning approaches for ECG, EEG, EMG, and other biosignals
Dynamic modeling and anomaly detection in continuous glucose, blood pressure, and other physiological signals
• Disease Detection and Predictive Modeling
AI-assisted diagnosis of cardiovascular diseases, diabetes, and neurodegenerative disorders (e.g., Alzheimer’s)
Neural biomarkers for mental health conditions (e.g., depression, anxiety)
• Wearable Devices and Embedded AI
Low-power real-time signal processing
Privacy-aware and personalized health monitoring
• Brain-Computer Interfaces (BCIs) and Neurorehabilitation
Neural signal decoding for motor/cognitive rehabilitation
Signal optimization in closed-loop BCI systems
• Clinical Translation and Ethical Considerations
Interpretability and validation of AI models in clinical settings
Multi-center data collaboration and standardization

Publication