Dear Colleagues,

Biomedical signal processing involves the treatment and analysis of bio-signal measurements. It is done in order to provide useful information which clinicians can use to make decisions. Novel signal processing methods have assisted in revealing information that entirely altered the previous approaches taken in the diagnosis of different diseases. In order to analyze biomedical signals, biomedical engineers use different types of signal processing and machine learning techniques. By using intelligent biomedical analysis tools, the signals can be analyzed by software to help physicians gain greater insights and to make better decisions in clinical assessments.

Nowadays, there is a great deal of interest in machine learning applications in health, biomedicine, and biomedical engineering. The recent advances in biomedical signal processing and machine learning have brought forth incredible progress to different areas in signal analysis and processing, including biometrics, medical data processing, etc. The application-oriented and data-driven bio-signal analysis and processing applications, not only benefit from the machine learning algorithms, but also encourage the development of intelligent techniques.

The purpose of this Special Issue is to present recent advances in signal processing and machine learning for biomedical signal analysis. We are targeting original research works in this field, covering new theories, algorithms, implementations, and applications for signal and data analytics. Potential topics of interests are related to recent advances in machine learning in signal analysis and processing, but are not limited to them:

• Biomedical Signal Processing and Analysis
• Biomedical Image Processing and Analysis
• Brain Computer Interface
• Human Machine Interfaces
• Neural Rehabilitation Engineering
• Biomedical Data processing for Big Data
• Information forensics and security
• The Internet of Things and RFID
• Machine learning for signal/image processing
• Signal/Image Processing for Brain Machine Interface
• Time-frequency and Non-stationary Biosignal Analysis
• Machine learning for biomedical signal/image processing
• Machine Learning in Biomedical Applications
• Biometrics with biomedical signals

Prof. Dr. Abdulhamit Subasi
Prof. Dr. Humaira Nisar
Dr. Saeed M. Qaisar
Guest Editors

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