Seizure detection using wearable sensors and machine learning: Setting a benchmark
… Based on the analysis of a large clinical seizure dataset of wrist- and ankle-worn wearable
… evaluate seizure detection with wearable devices for a broad spectrum of epileptic seizures. …
… evaluate seizure detection with wearable devices for a broad spectrum of epileptic seizures. …
Wearable seizure detection devices in refractory epilepsy
J Verdru, W Van Paesschen - Acta Neurologica Belgica, 2020 - Springer
… This literature review provides an update on the available wearable seizure detection devices
… additional fields of research such as wearable seizure prediction devices and closed-loop …
… additional fields of research such as wearable seizure prediction devices and closed-loop …
EZcap: A novel wearable for real-time automated seizure detection from EEG signals
IL Olokodana, SP Mohanty… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
… compare well with other seizure detection models in the literature but their excellent seizure
detection latency surpasses the performance of most existing works in seizure detection. …
detection latency surpasses the performance of most existing works in seizure detection. …
Using wearable sensors for semiology-independent seizure detection-towards ambulatory monitoring of epilepsy
BE Heldberg, T Kautz, H Leutheuser… - 2015 37th Annual …, 2015 - ieeexplore.ieee.org
… In this study, wearable sensors measuring EDA and ACC were used to detect epileptic
seizures, … It was shown that both seizure types could be detected using EDA and ACC data. …
seizures, … It was shown that both seizure types could be detected using EDA and ACC data. …
Feasibility of cardiac‐based seizure detection and prediction: A systematic review of non‐invasive wearable sensor‐based studies
… seizure detection or prediction. This study aims to examine available studies on seizure
detection and prediction based on cardiac parameters using non-invasive wearable devices. …
detection and prediction based on cardiac parameters using non-invasive wearable devices. …
[HTML][HTML] Tonic-clonic seizure detection using accelerometry-based wearable sensors: a prospective, video-EEG controlled study
… -based wearable system to detect tonic-clonic seizures (TCSs) and to investigate the
accuracy of different seizure detection algorithms using separate training and test data sets. …
accuracy of different seizure detection algorithms using separate training and test data sets. …
Automated epileptic seizure detection based on wearable ECG and PPG in a hospital environment
… seizure detection algorithm performs better than chance. Here, using wearable ECG, we
obtained a comparable seizure detection … the reasons for missed seizures and false alarms. …
obtained a comparable seizure detection … the reasons for missed seizures and false alarms. …
[HTML][HTML] Towards a wearable multi-modal seizure detection system in epilepsy: A pilot study
JM Nielsen, IC Zibrandtsen, P Masulli… - Clinical …, 2022 - Elsevier
… wearable offline multi-modal seizure detection system for the long-term detection of focal
seizures, both … An SVM based automatic seizure detection algorithm using different multi-modal …
seizures, both … An SVM based automatic seizure detection algorithm using different multi-modal …
Seizure detection based on wearable devices: a review of device, mechanism, and algorithm
W Li, G Wang, X Lei, D Sheng, T Yu… - Acta Neurologica …, 2022 - Wiley Online Library
… to use a wearable device to detect seizure and inform … of seizure detection based on
wearable devices from three parts: devices, physiological activities, and algorithms. Firstly, seizure …
wearable devices from three parts: devices, physiological activities, and algorithms. Firstly, seizure …
A wearable sensor based multi-criteria-decision-system for real-time seizure detection
… two part wearable for real-time epileptic seizure detection. … The combination of a chest and
hand worn wearable … (LSTM) based anomaly detection algorithms and logistic classifiers …
hand worn wearable … (LSTM) based anomaly detection algorithms and logistic classifiers …
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