1# Library to Find Best eBook for Read
Author : Sharon Chiang
Release : 2022-03-31
Genre : Medical
Kind : eBook
Book Rating : 723/5 ( reviews)
Book Synopsis Seizure Forecasting and Detection: Computational Models, Machine Learning, and Translation into Devices by : Sharon Chiang
Download or read book Seizure Forecasting and Detection: Computational Models, Machine Learning, and Translation into Devices written by Sharon Chiang. This book was released on 2022-03-31. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Steven Baldassano
Release : 2017
Genre :
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Translational Machine Learning for Epilepsy Therapy by : Steven Baldassano
Download or read book Translational Machine Learning for Epilepsy Therapy written by Steven Baldassano. This book was released on 2017. Available in PDF, EPUB and Kindle. Book excerpt: Continuous medical data monitoring is playing an increasingly important role in patient care, both in and out the hospital. Diagnosing and treating patients with epilepsy is especially reliant on continuous EEG monitoring to identify and respond to seizures. However, as use of continuous EEG becomes more common, both for long-term inpatient monitoring and in ambulatory or implanted devices, the burden of study interpretation is rapidly outpacing available physician resources. In particular, the advent of implanted neuroresponsive devices for treating medically-refractory epilepsy is generating large, streaming datasets potentially lasting for several years and containing hundreds of seizures. The current need for manual review of long-term, continuous EEG data introduces tremendous health care costs and can result in significant delays in seizure diagnosis and treatment. Automated data processing is essential to improve data usage, accurately and rapidly detect seizures, and provide scalability in clinical practice. This thesis aims to develop platforms for automated data analysis and event detection using custom machine learning algorithms for application in the intensive care unit and in implanted neural devices. The work presented in this thesis progresses through the development of each component of an automated data analysis platform. The first section describes a system for real-time data analysis and caretaker notification in the ICU, with a focus on the process necessary to harness multi-modal data from clinical recording sources. The next section details the process of developing machine learning algorithms for seizure detection. In this section, I present novel seizure detection strategies as well as a competition designed to crowdsource algorithm development. This work produced several highly-accurate, open-source seizure detection methods, validated in extended human implanted device data, along with pipelines to facilitate algorithm application and benchmarking in new datasets. The last section covers the integration of data management and seizure detection for implementation in next-generation medical devices. I present a novel paradigm to leverage cloud computing resources for seizure detection in an implanted device. This system is then implemented in vivo using a canine epilepsy model, with real-time seizure detection on streaming data from Medtronic's RC+S neurostimulating device. These algorithms and flexible analysis platforms are a step toward automating analysis of EEG data for epilepsy therapy. It is my hope that such systems will improve medical data usage, reshape caretaker workflow, and increase the clinical power of continuous medical monitoring.
Author : Jamie Michael Koerner
Release : 2020
Genre :
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Machine Learning-driven Patient-specific Early Seizure Detection for Neuromodulation Devices by : Jamie Michael Koerner
Download or read book Machine Learning-driven Patient-specific Early Seizure Detection for Neuromodulation Devices written by Jamie Michael Koerner. This book was released on 2020. Available in PDF, EPUB and Kindle. Book excerpt: Epilepsy is a chronic disorder of the brain that predisposes individuals to experiencing recurrent and unprovoked seizures affecting 50 million people worldwide. Recent advances in fundamental neuroscience and implantable electronics have enabled the development of neuromodulation devices for the treatment of epilepsy. Modern neuromodulation devices detect abnormal electrical activity in the brain associated with seizures and activate electrical stimulation to prevent seizures from occurring. Today, there is a growing trend towards integrating machine learning for seizure detection on such devices to improve their efficacy. This thesis assesses the suitability of current machine learning models for neuromodulation devices by evaluating their seizure detection performance and efficiency in resource-constrained environments. Particular emphasis is placed on comparing traditional machine learning to modern deep learning models. This thesis will show that, in the seizure detection context, deep learning models can be implemented in a compact and resource-efficient way despite their computational complexity.
Author : Ratnaprabha Ravindra Borhade
Release : 2024-12-19
Genre : Computers
Kind : eBook
Book Rating : 394/5 ( reviews)
Book Synopsis Epileptic Seizure Prediction Using Electroencephalogram Signals by : Ratnaprabha Ravindra Borhade
Download or read book Epileptic Seizure Prediction Using Electroencephalogram Signals written by Ratnaprabha Ravindra Borhade. This book was released on 2024-12-19. Available in PDF, EPUB and Kindle. Book excerpt: 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 all techniques used in the literature and emphasises on newly proposed techniques. The book concentrates on 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.
Author : Ronald Tetzlaff
Release : 2013-08-28
Genre : Medical
Kind : eBook
Book Rating : 367/5 ( reviews)
Book Synopsis Recent Advances In Predicting And Preventing Epileptic Seizures - Proceedings Of The 5th International Workshop On Seizure Prediction by : Ronald Tetzlaff
Download or read book Recent Advances In Predicting And Preventing Epileptic Seizures - Proceedings Of The 5th International Workshop On Seizure Prediction written by Ronald Tetzlaff. This book was released on 2013-08-28. Available in PDF, EPUB and Kindle. Book excerpt: This book is to improve our understanding of mechanisms leading to seizures in humans and in developing new therapeutic options. The book covers topics such as recent approaches to seizure control, recent developments in signal processing of interest for seizure prediction, ictogenesis in complex epileptic brain networks, active probing of the pre-seizure state, non-EEG based approaches to the transition to seizures, microseizures and their role in the generation of clinical seizures, the impact of sleep and long-biological cycles on seizure prediction, as well as animal and computational models of seizures and epilepsy. Furthermore the book covers recent developments of international databases and of parallel computing structures based on Cellular Nonlinear Networks that can play an important role in the realization of a portable seizure warning device.
