Application of Neural Engineering in Sleep Research and Medicine
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: closed (31 August 2024) | Viewed by 2776
Special Issue Editors
Interests: processing and analysis of biomedical signals; brain imaging methodologies; EEG brain activity; computational/mathematical models; optimization algorithms
Special Issue Information
Dear Colleagues,
Sleep is essential for a multitude of biological processes including cognitive, immune, endocrine, metabolic, and cardiovascular functions. Uncovering the precise physiological mechanisms underlying these processes as well as their potential impairment under pathological conditions represents a fundamental step in the definition of novel risk factors, early diagnosis protocols, and strategies for maintaining, restoring, and improving our mental and physical health.
Studying and monitoring sleep requires the simultaneous acquisition of multiple bio-signals related to both the central and the peripheral nervous system. If this can limit the applicability in daily life conditions, it also implies a considerable effort in terms of signal preprocessing and advanced analysis. In the past, sleep medicine and research largely addressed this necessity using visual scoring, especially for sleep staging, and manual pattern identification.
Considering the latest achievements in the field of biomedical imaging, signal processing, and machine learning, this Special Issue aims to collect original research papers and comprehensive reviews focusing on the most recent applications and studies of neural engineering for sleep research and medicine. Topics of interest include, but are not limited to, the following:
- Signal processing for sleep data analysis.
- Machine learning based approaches for sleep data analysis and sleep staging.
- Automated methods for sleep staging, event detections and pattern recognition.
- Multimodal neuroimaging for sleep study.
- Non-invasive systems for sleep monitoring in both clinical and daily life settings.
- Techniques and technologies for influencing and manipulating sleep.
Dr. Monica Betta
Dr. Marco Laurino
Guest Editors
Manuscript Submission Information
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Keywords
- sleep
- signal processing
- computational neuroscience
- machine learning
- artificial intelligence
- PSG
- EEG
- neuroimaging
- wearable systems
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