Seizure Detection and Prediction Algorithms
ثبت نشده
چکیده
Research in automatic analysis of EEG for supporting the diagnosis of epileptic seizures took pace in the 1970s. Prior et al [45] suggested the use of a device called cerebral function monitor to demarcate generalized tonic-clonic seizures. These could be identified as a large increase in EEG amplitude followed by an observable decrease and by large EMG activity. Method described by Ives et al [46] involved filtering of 16 channel EEG and amplitude discrimination. Though, it could detect large seizure discharge it was not sensitive to smaller discharges. Babb et al [47] introduced an electronic circuit that could recognize a seizure through a rapid succession of large amplitude spikes.
منابع مشابه
EEG seizure detection and prediction algorithms: a survey
Epilepsy patients experience challenges in daily life due to precautions they have to take in order to cope with this condition. When a seizure occurs, it might cause injuries or endanger the life of the patients or others, especially when they are using heavy machinery, e.g., deriving cars. Studies of epilepsy often rely on electroencephalogram (EEG) signals in order to analyze the behavior of...
متن کاملA stochastic framework for evaluating seizure prediction algorithms using hidden Markov models.
Responsive, implantable stimulation devices to treat epilepsy are now in clinical trials. New evidence suggests that these devices may be more effective when they deliver therapy before seizure onset. Despite years of effort, prospective seizure prediction, which could improve device performance, remains elusive. In large part, this is explained by lack of agreement on a statistical framework f...
متن کاملInnovative Methodology A Stochastic Framework for Evaluating Seizure Prediction Algorithms Using Hidden Markov Models
Wong S, Gardner AB, Krieger AM, Litt B. A stochastic framework for evaluating seizure prediction algorithms using hidden Markov models. J Neurophysiol 97: 2525–2532, 2007. First published October 4, 2006; doi:10.1152/jn.00190.2006. Responsive, implantable stimulation devices to treat epilepsy are now in clinical trials. New evidence suggests that these devices may be more effective when they de...
متن کاملToward new paradigms of seizure detection.
Great effort has been made toward defining and characterizing the pre-ictal state. Many studies have pursued the idea that there are recognizable electrographic (EEG-based) features which occur before overt clinical seizure activity. However, development of reliable EEG-based seizure detection and prediction algorithms has been difficult. In this review, we discuss the concepts of seizure detec...
متن کاملSeizure detection, seizure prediction, and closed-loop warning systems in epilepsy
Nearly one-third of patients with epilepsy continue to have seizures despite optimal medication management. Systems employed to detect seizures may have the potential to improve outcomes in these patients by allowing more tailored therapies and might, additionally, have a role in accident and SUDEP prevention. Automated seizure detection and prediction require algorithms which employ feature co...
متن کاملIntelligent application for Heart disease detection using Hybrid Optimization algorithm
Prediction of heart disease is very important because it is one of the causes of death around the world. Moreover, heart disease prediction in the early stage plays a main role in the treatment and recovery disease and reduces costs of diagnosis disease and side effects it. Machine learning algorithms are able to identify an effective pattern for diagnosis and treatment of the disease and ident...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015