Reviews on Applied Biomedical Signal Processing
A special issue of Signals (ISSN 2624-6120).
Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 633
Special Issue Editors
Interests: biomedical signal processing; machine learning; data science; sleep apnea; sleep
Special Issues, Collections and Topics in MDPI journals
2. Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), 28029 Madrid, Spain
Interests: biomedical signal processing; information theory; non-linear dynamics, entropy and complexity; machine learning; sleep disorders; pulmonary diseases
2. Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), 28029 Madrid, Spain
Interests: biomedical signal processing; computational neuroscience; network neuroscience; correlation networks; information theory; time-frequency analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are pleased to announce a new Special Issue on “Reviews on Applied Biomedical Signal Processing”. There are many signal processing techniques that have proven their usefulness when applied to solve medical and biological problems. Here, we offer a scientific forum to share interesting and rigorous reviews on these topics.
The purpose of this Special Issue is not only to gather classic bibliographic reviews, which are of course very welcome, but also any kind of systematic audit of methodological approaches over one or several subjects within a shared framework. Accordingly, reviews submitted to this Special Issue may include (but not be limited to):
- Bibliographic reviews on the signal processing methods applied to a medical or biological problem;
- Bibliographic reviews on the usefulness and interpretation of a signal processing method that has been applied to several medical or biological problems;
- Hands-on reviews where a set of methods are thoroughly and properly compared by applying them to the same dataset representative of a particular biomedical problem, thus providing original results and further discussion on the topic;
- Meta-analyses;
- Any combination of the above.
Similarly, ‘biomedical signal processing techniques’ should be interpreted in a wide sense, hence allowing not only feature extraction methods but also feature selection and machine-learning algorithms applied to both physiological signals and medical images.
Dr. Gonzalo C. Gutiérrez-Tobal
Dr. Daniel Álvarez
Dr. Javier Gomez-Pilar
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 papers will be 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. Review articles 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. Signals is an international peer-reviewed open access quarterly 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 1000 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.
Keywords
- applied biomedical signal processing
- electroencephalogram
- electrocardiogram
- respiratory signals
- spectral analysis
- nonlinear analysis
- machine learning
- deep learning
- explainable artificial intelligence
- automatic feature selection
- dementia
- sleep
- schizophrenia
- arrythmias
- (f)magnetic resonance imaging
- retinography
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