Advances in Biomedical Signal Processing and Analysis

A special issue of Signals (ISSN 2624-6120).

Deadline for manuscript submissions: 31 January 2026 | Viewed by 60

Special Issue Editors


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Guest Editor
Department of Biomedical Engineering, Linköping University, Linköping, Sweden
Interests: biomedical signal processing; machine learning; statistical pattern recognition

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Guest Editor
1. Department of Information Science and Media Studies, University of Bergen, Bergen, Norway
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

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Keywords

  • cyclic biomedical signals
  • heart sound
  • lung sound
  • electroencephalogram (EEG)
  • electrocardiogram (ECG)

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Published Papers

This special issue is now open for submission.
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