Electrophysiological Signal Processing in Neurological Diseases
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 743
Special Issue Editor
Interests: innovative sensing; wearable system development and clinical translation of electrophysiological signals (EEG and EMG); mathematical algorithms and deep learning models for electrophysiological signal processing in early diagnosis of neurological diseases
Special Issue Information
Dear Colleagues,
Neurological diseases, such as epilepsy, Alzheimer’s disease, Parkinson’s disease, and stroke, present significant challenges to global healthcare. Electrophysiological signals—including electroencephalography (EEG), electromyography (EMG), magnetoencephalography (MEG), and local field potentials (LFP)—serve as critical windows into neural function and dysfunction. Recent advances in signal processing, coupled with the rapid development of artificial intelligence and wearable technology, have opened new avenues for the early detection, precise diagnosis, and continuous monitoring of these disorders.
This Special Issue aims to gather the latest research on advanced signal processing techniques applied to electrophysiological data in the context of neurological health. We invite researchers to submit original research papers, reviews, and short communications that address challenges in signal acquisition, artifact removal, feature extraction, and classification. Contributions focusing on multimodal fusion, real-time monitoring systems, and explainable AI for clinical decision support are particularly encouraged.
Topics of interest include, but are not limited to, the following:
- Advanced signal processing algorithms for EEG, MEG, EMG, and EOG;
- Machine learning and deep learning applications in neurological diagnosis;
- Wearable sensors and systems for long-term neurological monitoring;
- Brain–computer interfaces (BCIs) for rehabilitation and assistance;
- Multimodal data fusion (e.g., EEG-fMRI, EEG-Speech) for disease profiling;
- Biomarker discovery for neurodegenerative diseases (Alzheimer’s, Parkinson’s);
- Seizure detection, prediction, and localization;
- Connectivity analysis and brain network modeling;
- Real-time processing and low-power embedded systems for neuro-applications.
Prof. Dr. Shixiong Chen
Guest Editor
Manuscript Submission Information
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Keywords
- neurologic diseases
- signal processing
- EEG
- EMG
- neuroimaging
- wearable devices
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