Application of Biosignal Processing, Artificial Intelligence and Machine Learning on Healthcare

Dear Colleagues,

With the advancements of wearable devices, machine learning and real-time processing, biosignal processing has become one of the most exciting and promising areas in healthcare. From hospital monitors to wearable sensors, and from intensive care units to smart devices, biomedical signals have great potential in the field of healthcare.

The scope of biosignal processing covers the exploration of different sensors, the preprocessing of recorded data, the development of intelligent algorithms and machine learning models, the extraction of helpful clinical information, the development of wearable devices, etc. Some common sources of biosignals include cardiac rhythms, neural activity, eye movement, muscle signals, skin conductance, and physiological movements.

The aim of this Special Issue “Application of Biosignal Processing, Artificial Intelligence and Machine Learning in Healthcare” is to collect a compendium of articles about the recent trends and advances in biomedical signal processing and wearable devices, as well as the development of artificial intelligence systems for clinical applications. This collection will supplement the existing literature by publishing novel and recent trends in the field of biosignal processing, wearable devices, sensors, etc. to advance healthcare and improve patients’ quality of life. We look forward to your participation in this Special Issue.

Topics of interest include, but are not limited to, the following:

• New trends in physiological monitoring and vital sign recording;
• Processing and analysis of electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmogram (PPG), inertial measurement unit (IMU), electromyogram (EMG), and other technologies;
• Applications of machine learning and artificial intelligence in healthcare;
• Development of wearable devices and body sensor networks;
• Human activity recognition and tracking and remote monitoring;
• Digital health and mHealth for disease monitoring, detection, and prediction.

Dr. Syed Khairul Bashar
Guest Editor

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• biomedical signal processing
• biosensors
• wearable devices
• healthcare
• physiological monitoring
• vital sign
• body sensor network
• artificial intelligence
• machine learning
• deep learning
• digital health
• disease detection and prediction