Special Issue "Biomedical Signal Processing in Healthcare and Disease Diagnosis"
Deadline for manuscript submissions: 20 December 2022 | Viewed by 1617
Interests: neurophysiological signal processing; computer-aided diagnosis for diseases; brain–computer interface
Interests: biomedical signal processing; brain–computer interface; neural engineering
Interests: neuroimaging; cognitive neuroscience; functional connectivity analysis for brain diseases
The research topic of biomedical signal processing has been studied for more than two decades. However, with the rapid advancement of biosensing, IoT, AI, and embedded/edge/cloud computing technologies, it has been shown that there is a need to re-evaluate the effectiveness of conventional methods and/or to develop new biomedical signal processing methods with high validity and reliability for their application in healthcare and disease diagnosis. For example, telemedicine has recently proved its importance in healthcare, especially during the current COVID-19 pandemic. A critical and urgent concern is how to provide people with timely and accurate screening, diagnosis, and treatment. Real-time biomedical signal processing carried out from a remote location using portable devices or apps could represent a solution. In this context, designing biomedical signal processing methods with low computational complexity is crucial. As software as a medical device (SaMD) and digital medicine become increasingly common in clinical practice, a central question is how to improve the effectiveness (sensitivity, specificity, etc.) of a biomarker in the diagnosis of a specific disease, validate the robustness (e.g., reliability) of the marker across hospitals, and even examine the association between the biomarker and the pathological mechanism of the disease (i.e., interpretability).
This Special Issue aims to provide a cross-disciplinary forum for international researchers to share and exchange their research outcomes in biomedical signal processing, with a focus on medical signals and images in clinical practice. We invite researchers to submit original works focusing on the design and/or demonstration of advanced biomedical signal processing methods for healthcare and disease diagnosis, including preprocessing, feature extraction, classification, and prediction. We also solicit papers relating to the development of biomedical signal-actuated healthcare systems. Review articles comparing state-of-the-art biomedical signal processing methods in healthcare and disease diagnosis are also welcome.
Prof. Dr. Yi-Hung Liu
Dr. Tzyy-Ping Jung
Dr. Chien-Te Wu
Dr. Paul C.-P. Chao
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.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biosensors is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- biomedical signal
- disease diagnosis
- machine learning
- artificial intelligence