An automated system for epilepsy detection using EEG brain signals based on deep learning approach
Epilepsy is a life-threatening and challenging neurological disorder, which is affecting a
large number of people all over the world. For its detection, encephalography (EEG) is a …
large number of people all over the world. For its detection, encephalography (EEG) is a …
EEG signal analysis for diagnosing neurological disorders using discrete wavelet transform and intelligent techniques
Analysis of electroencephalogram (EEG) signals is essential because it is an efficient
method to diagnose neurological brain disorders. In this work, a single system is developed …
method to diagnose neurological brain disorders. In this work, a single system is developed …
Automatic epileptic seizure detection using scalp EEG and advanced artificial intelligence techniques
The epilepsies are a heterogeneous group of neurological disorders and syndromes
characterised by recurrent, involuntary, paroxysmal seizure activity, which is often …
characterised by recurrent, involuntary, paroxysmal seizure activity, which is often …
[HTML][HTML] A machine learning system for automated whole-brain seizure detection
Epilepsy is a chronic neurological condition that affects approximately 70 million people
worldwide. Characterised by sudden bursts of excess electricity in the brain, manifesting as …
worldwide. Characterised by sudden bursts of excess electricity in the brain, manifesting as …
Energy-efficient low duty cycle MAC protocol for wireless body area networks
This paper presents an energy-efficient medium access control protocol suitable for
communication in a wireless body area network for remote monitoring of physiological …
communication in a wireless body area network for remote monitoring of physiological …
eSeiz: An edge-device for accurate seizure detection for smart healthcare
Epilepsy is one of the most common neurological disorders affecting a significant portion of
the world's population and approximately 2.5 million people in the United States. Important …
the world's population and approximately 2.5 million people in the United States. Important …
BrainFuseNet: Enhancing Wearable Seizure Detection through EEG-PPG-accelerometer Sensor Fusion and Efficient Edge Deployment
This paper introduces BrainFuseNet, a novel lightweight seizure detection network based on
the sensor fusion of electroencephalography (EEG) with photoplethysmography (PPG) and …
the sensor fusion of electroencephalography (EEG) with photoplethysmography (PPG) and …
Takagi–Sugeno–Kang transfer learning fuzzy logic system for the adaptive recognition of epileptic electroencephalogram signals
The intelligent recognition of electroencephalogram (EEG) signals has become an important
approach to the detection of epilepsy. Among existing intelligent identification methods …
approach to the detection of epilepsy. Among existing intelligent identification methods …
Integer convolutional neural network for seizure detection
Outstanding seizure detection algorithms have been developed over past two decades.
Despite this success, their implementations as part of implantable or wearable devices are …
Despite this success, their implementations as part of implantable or wearable devices are …
Miniaturized wireless ECG monitor for real-time detection of epileptic seizures
F Massé, MV Bussel, A Serteyn, J Arends… - ACM Transactions on …, 2013 - dl.acm.org
Recent advances in miniaturization of ultra-low power components allow for more intelligent
wearable health monitors. The development and evaluation of a wireless wearable …
wearable health monitors. The development and evaluation of a wireless wearable …