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Biomedical signals based computer-aided diagnosis for neurological disorders

URI
https://hdl.handle.net/10497/24604
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Type
Book
Citation
Murugappan, M., & Yuvaraj Rajamanickam. (Eds.). (2022). Biomedical signals based computer-aided diagnosis for neurological disorders. Springer. https://doi.org/10.1007/978-3-030-97845-7
Author
Murugappan, M.
•
Yuvaraj Rajamanickam 
Abstract
Biomedical signals provide unprecedented insight into abnormal or anomalous neurological conditions. The computer-aided diagnosis (CAD) system plays a key role in detecting neurological abnormalities and improving diagnosis and treatment consistency in medicine. This book covers different aspects of biomedical signals-based systems used in the automatic detection/identification of neurological disorders. Several biomedical signals are introduced and analyzed, including electroencephalogram (EEG), electrocardiogram (ECG), heart rate (HR), magnetoencephalogram (MEG), and electromyogram (EMG). It explains the role of the CAD system in processing biomedical signals and the application to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders.
Date Issued
2022
ISBN
978303097845-7
Publisher
Springer
DOI
10.1007/978-3-030-97845-7
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