4.5 Article

A novel approach to automatic seizure detection using computer vision and independent component analysis

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Behavioral Sciences

Seizure detection devices: A survey of needs and preferences of patients and caregivers

Tamara Herrera-Fortin et al.

Summary: The study found that the majority of people with epilepsy and their caregivers in Canada are interested in seizure detection, with a preference for continuous use of the detectors with automated alarms. Smartwatches and bracelets/rings were considered the most acceptable devices. Users were most concerned about false negatives, comfort, and cost, and they believed that seizure detection could improve their quality of life and care, expressing confidence in their ability to use the technology.

EPILEPSY & BEHAVIOR (2021)

Article Computer Science, Information Systems

Video-Based Detection of Generalized Tonic-Clonic Seizures Using Deep Learning

Yonghua Yang et al.

Summary: Automated detection of generalized tonic-clonic seizures (GTCSs) from videos using deep learning has been proven feasible and effective, showing better performance and potential compared to traditional methods. Results demonstrate that deep learning networks based on video sequences outperform detection based on individual frames, with an average sensitivity of 88% and specificity of 92%, and a detection latency of approximately 22 seconds.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2021)

Article Clinical Neurology

Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit

Francesco Onorati et al.

Summary: Using machine learning to combine wrist accelerometer and electrodermal activity has shown effective performance in detecting convulsive seizures in epilepsy monitoring units. The study evaluated the performance of a CS-detection device on pediatric and adult patients, achieving high sensitivity and precision while facing potential challenges with higher false alarm rates in pediatric population. The Active mode of the detection algorithm reduced false alarms significantly during rest periods, showing potential benefits for daily life impact reduction. Future work will focus on examining the performance and usability outside of epilepsy monitoring units.

FRONTIERS IN NEUROLOGY (2021)

Article Clinical Neurology

Diagnostic challenges in epilepsy: seizure under-reporting and seizure detection

Christian E. Elger et al.

LANCET NEUROLOGY (2018)

Article Engineering, Biomedical

Convolutional neural networks for real-time epileptic seizure detection

Felix Achilles et al.

COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION (2018)

Proceedings Paper Neurosciences

The Biosignal CAOS: Reflections on the Usability of Physiological Sensing for Human-Computer Interaction Practitioners and Researchers

Hugo Placido da Silva

CONVERGING CLINICAL AND ENGINEERING RESEARCH ON NEUROREHABILITATION II, VOLS 1 AND 2 (2017)

Article Behavioral Sciences

Patient-centered design criteria for wearable seizure detection devicesl

Anup D. Patel et al.

EPILEPSY & BEHAVIOR (2016)

Review Multidisciplinary Sciences

Principal component analysis: a review and recent developments

Ian T. Jolliffe et al.

PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2016)

Review Clinical Neurology

Automated seizure detection systems and their effectiveness for each type of seizure

A. Ulate-Campos et al.

SEIZURE-EUROPEAN JOURNAL OF EPILEPSY (2016)

Article Clinical Neurology

Patient and caregiver view on seizure detection devices: A survey study

Diego F. Tovar Quiroga et al.

SEIZURE-EUROPEAN JOURNAL OF EPILEPSY (2016)

Article Behavioral Sciences

Novel techniques for automated seizure registration: Patients' wants and needs

Christian Hoppe et al.

EPILEPSY & BEHAVIOR (2015)

Article Behavioral Sciences

Assessment of a quasi-piezoelectric mattress monitor as a detection system for generalized convulsions

Aditi P. Narechania et al.

EPILEPSY & BEHAVIOR (2013)

Article Clinical Neurology

Prospective Study of the Emfit Movement Monitor

Kate Van Poppel et al.

JOURNAL OF CHILD NEUROLOGY (2013)

Article Computer Science, Interdisciplinary Applications

Wavelet-based sparse functional linear model with applications to EEGs seizure detection and epilepsy diagnosis

Shengkun Xie et al.

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING (2013)

Review Clinical Neurology

The impact of epilepsy on patients' lives

M. P. Kerr

ACTA NEUROLOGICA SCANDINAVICA (2012)

Review Computer Science, Interdisciplinary Applications

Vision-based motion detection, analysis and recognition of epileptic seizures-A systematic review

Matthew Pediaditis et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2012)

Article Computer Science, Artificial Intelligence

AUTOMATIC DETECTION OF EPILEPTIC EEG SIGNALS USING HIGHER ORDER CUMULANT FEATURES

U. Rajendra Acharya et al.

INTERNATIONAL JOURNAL OF NEURAL SYSTEMS (2011)

Article Clinical Neurology

Detecting nocturnal convulsions: Efficacy of the MP5 monitor

Chad Carlson et al.

SEIZURE-EUROPEAN JOURNAL OF EPILEPSY (2009)

Article Clinical Neurology

Automated detection of videotaped neonatal seizures based on motion segmentation methods

Nicolaos B. Karayiannis et al.

CLINICAL NEUROPHYSIOLOGY (2006)

Article Computer Science, Artificial Intelligence

Recognizing faces with PCA and ICA

BA Draper et al.

COMPUTER VISION AND IMAGE UNDERSTANDING (2003)

Article Clinical Neurology

The epidemiology of epilepsy revisited

JW Sander

CURRENT OPINION IN NEUROLOGY (2003)

Article Medicine, General & Internal

Early identification of refractory epilepsy.

P Kwan et al.

NEW ENGLAND JOURNAL OF MEDICINE (2000)