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- Autorius: Manoj S. Nagmode, Ratnaprabha Ravindra Borhade, Ravindra Honaji Borhade, Vinayak K. Bairagi
- Leidėjas: Taylor & Francis Ltd
- Metai: 2026
- Puslapiai: 140
- ISBN-10: 103272594X
- ISBN-13: 9781032725949
- Kalba: Anglų
Epileptic Seizure Prediction Using Electroencephalogram Signals (el. knyga) (skaityta knyga) | knygos.lt
Atsiliepimai
Aprašymas
This book presents an innovative method of EEG-based feature extraction and classification of seizures using EEG signals. It describes the methodology required for EEG analysis, seizure detection, seizure prediction, and seizure classification. It contains a compilation of techniques described in the literature and emphasizes newly proposed techniques. The book includes a brief discussion of existing methods for epileptic seizure diagnosis and prediction and introduces new efficient methods specifically for seizure prediction.
- Focuses on the mathematical models and machine learning algorithms from a perspective of clinical deployment of EEG-based epileptic seizure prediction
- Discusses recent trends in seizure detection, prediction, and classification methodologies
- Provides engineering solutions to severity or risk analysis of detected seizures at remote places
- Presents wearable solutions to seizure prediction
- Includes details of the use of deep learning for epileptic seizure prediction using EEG
This book acts as a reference for academicians and professionals who are working in the field of computational biomedical engineering and are interested in the domain of EEG-based disease prediction.
- Autorius: Manoj S. Nagmode, Ratnaprabha Ravindra Borhade, Ravindra Honaji Borhade, Vinayak K. Bairagi
- Leidėjas: Taylor & Francis Ltd
- Metai: 2026
- Puslapiai: 140
- ISBN-10: 103272594X
- ISBN-13: 9781032725949
- Kalba: Anglų
This book presents an innovative method of EEG-based feature extraction and classification of seizures using EEG signals. It describes the methodology required for EEG analysis, seizure detection, seizure prediction, and seizure classification. It contains a compilation of techniques described in the literature and emphasizes newly proposed techniques. The book includes a brief discussion of existing methods for epileptic seizure diagnosis and prediction and introduces new efficient methods specifically for seizure prediction.
- Focuses on the mathematical models and machine learning algorithms from a perspective of clinical deployment of EEG-based epileptic seizure prediction
- Discusses recent trends in seizure detection, prediction, and classification methodologies
- Provides engineering solutions to severity or risk analysis of detected seizures at remote places
- Presents wearable solutions to seizure prediction
- Includes details of the use of deep learning for epileptic seizure prediction using EEG
This book acts as a reference for academicians and professionals who are working in the field of computational biomedical engineering and are interested in the domain of EEG-based disease prediction.
Atsiliepimai