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In this paper, we report on a proof-of-concept wearable prototype, called iSeiz, that can detect specific seizure activity, namely generalized tonic-clonic, in epilepsy patients. We first describe the high-level architecture of iSeiz, and then elaborate on its hardware and software features, including its robust and low-computational intensive real-time seizure detection algorithm (SDA), as well as...
This paper presents a novel wearable biomedical Network on Chip (NoC) concept development to monitor and predict irregular brain waves as advanced sensitive portable for an electroencephalogram (EEG) analysis device. The proposed device will monitor brain’s spontaneous electrical activity in normal and abnormal situations for specific patients suffering from different types of epilepsy...
Most current studies of epileptic seizure detection disclose that "Despite the design of new anti-epileptic drugs, drug resistant epilepsy still lacks an ultimate solution" [1]. The Internet of Things (IoT) provides a timely chance for a more personalised approach to the monitoring and management of epilepsy. This is by integrating smart devices deployed at home and personal patient data...
Epilepsy is a group of neurological diseases characterized by epileptic seizures. It affects millions of people worldwide, with 80% of cases occurring in developing countries. This can result in accidents and sudden, unexpected death. Seizures can happen undetectably in newborns, comatose, or motor impaired patients, especially due to the fact that many medical personnel are not qualified for EEG...
More than forty million people in the world are epilepsy sufferers. Epilepsy is a neurological disease. That is characterized by the presence of seizures in which the patient has convulsions, among other symptoms, that can cause damage, and even lead him to death. For this reason, it is important to develop systems for allowing early detections. Additionally, the cost of this kind of devices is usually...
To augment neural monitoring, a minimally intrusive multi-modal capture system was designed and implemented in the epilepsy clinic. This system provides RGB-D audio-video synchronized with patient electrocorticography (ECoG), which records neural activity across cortex. We propose an automated approach to studying the human brain in a naturalistic setting. We demonstrate coarse functional mapping...
Seizures affect each patient differently, so personalization is a vital part of developing a reliable nonEEG based seizure detection system. This personalization must be done while the patient is undergoing video EEG monitoring in an epilepsy monitoring unit (EMU) because seizure detection by EEG is considered to be the ground truth. We propose the use of confidence interval analysis for determining...
Many neurological diseases, such as Parkinson's disease and epilepsy, can significantly impair the motor function of the patients, often leading to a dramatic loss of their quality of life. Human motion analysis is regarded as fundamental towards an early diagnosis and enhanced follow-up in this type of diseases. In this contribution, we present NeuroKinect, a novel system designed for motion analysis...
For more than five decades progress in functional neurosurgery has been boosted at every time surgeons and physiologists have accepted the idea that the best way to restore a function, or to control a functional disorder, through a surgical operation, was to share their knowledge and to elaborate together new concepts as well as innovative procedures to the benefit of patients. The two most famous...
In this paper we present a three-tier service architecture to seizure detection and prediction based on cloud computing technology. This architecture is used for outdoor monitoring. We also propose a two-way security mechanism to protect user privacy for epilepsy patients.
Epilepsy is the disease of brain with more than 60 million (approx) cases worldwide. The cure for epilepsy is surgery and medication. Some patients are not cured with surgery and medicine. One third of the cases still remain with unrestrained epilepsy. There is an existing need of constant monitoring for epileptic seizures in this kind of cases. Treatment can be better provided by the doctors if seizure...
Epilepsy is a neurological disorder that affects a significant percentage of the population. Currently, electroencephalogram exams (EEG) are considered a valuable tool to support epilepsy diagnosis. In order to obtain a more trustworthy diagnosis, it is frequently necessary to submit patients to long monitoring periods. This fact, beyond causing discomfort to the patients and their relatives, implies...
Epilepsy is one of the commonest, serious and divesting brain disorders. Although it is still an incurable disorder in most cases its symptoms can be ameliorated by lifelong pharmaceutical treatment. Depending on the type of epilepsy and due to its multifactorial causes, different brain and body parameters need to be assessed continuously over a long period. This allows clinicians to have a better...
In this paper, the classification of epileptic and non-epileptic events from multi-channel EEG data is investigated using a large number of time and frequency domain features. In contrast to most of the evaluations found in the literature, in this paper the non-epileptic class consists of two types of paroxysmal episodes of loss of consciousness namely the psychogenic non epileptic seizure (PNES)...
Although refractory epileptic patients suffer from uncontrolled seizures, their quality of life (QoL) may be improved if the seizure can be predicted in advance. On the hypothesis that the excessive neuronal activity of epilepsy affects the autonomie nervous system and the fluctuation of the R-R interval (RRI) of an electrocardiogram (ECG), called heart rate variability (HRV), reflects the autonomie...
The surgical resection of the epileptogenic zone (EZ) is the only effective treatment for many drug-resistant epilepsy (DRE) patients, but the pre-surgical identification of the EZ is challenging. This study investigates whether the EZ exhibits a computationally identifiable signature during seizures. In particular, we compute statistics of the brain network from intracranial EEG (iEEG) recordings...
A video electroencephalogram (EEG) is the gold standard test for the monitoring of long term epilepsy, differentiating types of epilepsy and investigations of non-epileptic seizures. The use of video EEG in current practice is significantly limited by cost and non-availability of resources, causing delays for patients. This development addresses whether the limitations can be overcome by mobile technology...
Study of epilepsy in free moving animals provides the accurate information of this disease. While it has been proved that hemodynamic changes are greatly involved in epileptic seizures, methods for hemodynamic detection on free moving animals is limited. In this work, we integrated a photoacsoutic sensor and an EEG system into a small device that can be attached on the rat head, and for the first...
Detecting epileptic electroencephalography (EEG) signals, both automatically and accurately, is significant in ambulatory long-term monitoring patients with epilepsy. In this study, it is presented a novel epileptic-like event detection algorithm based on a mixture of amplitude, frequency and spatial analysis with rule-based decision. In this work, EEG signals from 6 different subjects were searched...
In the last years the introduction of Insertable Loop Recorders (ILRs) tried to tackle several unmet clinical needs, from unexplained syncope diagnosis to atrial fibrillation (AF) detection and management. While the use of a single vector EKG posed sensing and detection challenges, not faced with multi-lead therapy devices like implantable pacemakers or defibrillators, the possibility to apply established...
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