Advances in Biomedical Signal Processing and Analysis
A special issue of Signals (ISSN 2624-6120).
Deadline for manuscript submissions: 31 January 2026 | Viewed by 761
Special Issue Editors
Interests: biomedical signal processing; machine learning; statistical pattern recognition
2. Department of Biomedical Engineering, Linköping University, Linköping, Sweden
Interests: medical informatics; data mining; classification; artificial intelligence; machine learning; pattern recognition; clustering
Special Issue Information
Dear Colleagues,
Biomedical signals are key indicators of physiological activity within the human body, providing vital information regarding the health and well-being of the individual. The presence of various sources of distortion unavoidably contaminates the signals, making it challenging to extract diagnostic information from the signal due to the nonstationary and non-ergodic behaviors of physiological signals. The integration of stochastic and ensemble processing of biomedical signals has led to significant advancements in signal understanding, complemented by sophisticated machine learning methodologies for classification and representation. The idea of cyclic stochastic processing of biomedical signals has significantly enriched the processing task by leveraging statistical processing methods. However, it should be noted that this topic is applicable only to the physiological signals in which the cyclic characteristics are intrinsically introduced. The heart sound signal (or alternatively phonocardiogram), lung sound signal, electrocardiogram, and sleep electroencephalogram are well-known signals with cyclic characteristics. The Special Issue welcomes papers addressing the advanced methods for processing biomedical signals. The scope of this issue is sufficiently broad, encompassing various study objectives, including denoising, representation, optimization, and classification of biomedical signals. The integration of advanced deep learning methods with processing techniques for cyclic biomedical signals, such as heart sound signals, is particularly encouraged.
Dr. Arash Gharehbaghi
Prof. Dr. Ankica Babic
Guest Editors
Manuscript Submission Information
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Keywords
- cyclic biomedical signals
- heart sound
- lung sound
- electroencephalogram (EEG)
- electrocardiogram (ECG)
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