Biosignals Processing and Analysis in Biomedicine

Dear colleagues,

Biosignals are physiological and physical measures of the human body’s functions. They provide useful information about one’s physiological, pathophysiological, and emotional states, playing a key role in health monitoring and clinical diagnosis. The processing and analysis of biosignals is an interdisciplinary and dynamic area of specialization, covering biology, physics, medicine, engineering, and computer science. Recent advances in signal computational methods enables the proper signal preprocessing/noise removal, the improvement of analysis algorithms, and the extraction of representative features for effective utilization of biosignals in clinical environments.

Multimodal biosignals analysis provide a more complete image integrating the specific information from each modality. Fusion approaches aim at integrating data analyses establishing synergic relationships for improved diagnostic accuracy. Recent advances in machine learning (ML) and artificial intelligence (AI) analyze the dataset and provide a computational model for automatic classification or decision making for the problem under investigation. The data analysis interpretation and the connection with the underlying physiological mechanisms may lead to a deeper understanding of the pathophysiological states.

The Special Issue “Biosignals Processing and Analysis in Biomedicine” aims to provide a collection of contributions showing new advancements and applications of advanced biosignals analysis for biomedical applications. Topics relevant to biosignals processing and analysis for biomedical applications and affective computing are invited for this Special Issue. Topics of interest include, but are not limited to, the following:

• Biomedical Signal Processing and Analysis
• Biomedical Image Processing and Analysis
• Electroencephalogram (EEG), Electrocardiogram (ECG), Heart Rate Variability (HRV), Electromyogram (EMG), Electrodermal Activity (EDA), Thermal Infrared Imaging (TII), Photoplethysmography (PPG)
• Medical Imaging (MRI, PET, CT, SPECT)
• Video Analysis
• Speech analysis
• Computational Neuroscience
• Biomedical/Human body sensing
• Signal Analysis for Neurological disorders
• Signal Analysis for Affective Computing
• Application of machine learning and artificial intelligence in medicine
• Deep learning for biosignal analysis

Dr. Giorgos Giannakakis
Guest Editor

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