View clinical trials related to Epilepsy.
Filter by:Epilepsy is the 3rd neurological pathology after migraines and dementia syndromes with a high estimate of nearly 600,000 people affected in France. The disease is characterized by the repetition of epileptic seizures on the one hand, but also by the cognitive, behavioral, psychological and social consequences of this condition, especially when the epileptic disease is not stabilized. Epileptic patients feel a great deal of stress due to the unpredictability of the occurrence of seizures. Seizure detection is of great interest to bioinformatics researchers and to people with epilepsy and their caregivers. Recent advances in physiological sensor technologies and artificial intelligence have opened the possibility of developing systems capable of closely monitoring the frequency of epileptic seizures with a direct impact on therapeutic adaptations. This may eventually allow for seizure prediction and/or "seizure weather" (i.e., seizure forecasting) if there is a particular chronotype of seizure occurrence for a given individual. Currently, few devices have a sufficient level of evidence regarding their effectiveness to be recommended. Those that seem to be the most advanced are those that allow the identification of hypermotor seizures, including tonic-clonic generalized seizures and tonic-clonic secondary generalized focal seizures, mostly occurring at night. The latter represent only a small part of epileptic seizures. The objective of the present study is to build a real life database in order to develop a seizure detection algorithm. The recorded data will be heart rate via ECG and movement data via 9 variables measured on 3 axes x, y, z, with 3 sensors: accelerometer, gyroscope, magnetometer. These data will be collected using a connected patch available on the market (CE marking). At the same time, the patients will benefit from a long term video-EEG examination which will be annotated by the doctors and will be used as a gold standard for the identification of seizures in order to train the algorithm. This more complete base will be used to develop an algorithm previously developed from retrospective data.
Epilepsy is a chronic neurological disorder affecting millions of people all over the world. Epileptic seizures are caused by abnormal synchronized electrical neuronal discharges that could be either focal or widespread. Pathogenesis of epilepsy involves multiple processes including genetics, oxidative stress, ion channels, neuroinflammation, and cellular damage through autophagy and apoptosis. Neuroinflammation is considered one of the most important factors contributing critically to epileptogenesis.
After the general period of positive social adjustments, epilepsy is in a high life cycle to control seizures. During seizures in epilepsy, patients' quality of life and antiepileptic life span can be seen in daily life such as daily life and daily awakenings. Reiki, which has been proven by studies in health problems such as fatigue and pain; an energy that can be unblocked or applied in a non-applicable way can benefit from a therapy that can be applied by touch or remotely, without negative effects. In the literature, reiki applied to epilepsy patients has sleep and quality of life. This thesis is planned to do research on sleep and living areas of reiki applied to epilepsy patients.
Epilepsy is a disabling neurological disease that affects tens of millions of people worldwide. Despite therapeutic advances, about a third of these patients suffer from treatment-resistant forms of epilepsy and still experience regular seizures.All seizures can last and lead to status epilepticus, which is a major neurological emergency. Epilepsy can also be accompanied with cognitive or psychiatric comorbidities. Reliable seizures count is an essential indicator for estimating the care quality and for optimizing treatment. Several studies have highlighted the difficulty for patients to keep a reliable seizure diary due for example to memory loss or perception alterations during crisis. Whatever the reasons, it has been observed that at least 50% of seizures are on average missed by patients. Seizure detection has been widely developed in recent decades and are generally based on physiological signs monitoring associated with biomarkers search and coupled with detection algorithms. Multimodal approaches, i.e. combining several sensors at the same time, are considered the most promising. Mobile or wearable non invasive devices, allowing an objective seizures documentation in daily life activities, appear to be of major interest for patients and care givers, in detecting and anticipating seizures occurence. This single-arm exploratory, multicenter study aims at assessing whether the use of such a non-invasive, wearable device can be useful in a real life setting in detecting seizures occurence through multimodal analysis of various parameters (heart rate, respiratory and accelerometry).
The goal of this observational study is to learn more about phenotypic, genetic, biochemical, neurophysiological and radiological patterns in epilepsy. Participants will be asked to consent to use of clinical and paraclinical data (obtained during standard care) for research, and will be asked to donate blood samples at their routine clinic visits.
The purpose of this research is to search for reproducible changes in a wide range of physical signals, including heart rate, muscle tone and activity and EEG before and at the onset of seizures in patients with epilepsy.
The objective of this study is to assess the long-term safety, tolerability, and efficacy of adjunctive therapy of LP352 in subjects with developmental and epileptic encephalopathies who completed participation in Study LP352-201.
This project is a prospective, randomized, placebo-controlled, double-blind study that will evaluate the clinical efficacy of everolimus as an adjunctive treatment in adult patients diagnosed with refractory epilepsy.
Out of 30,000 new cases per year in France, 30% of epileptic patients are drug-resistant. Neurosurgery, which consists in resecting the epileptogenic zone, is the only chance of cure. In the case of temporal epilepsy of the language-dominant hemisphere (TLE), this procedure presents a high risk of increasing cognitive difficulties and may even be contraindicated for this reason alone. The difficulties found are impairments in lexical access (anomia) and verbal memory and affect more than 60% of patients . Preoperative cognitive rehabilitation could influence brain plasticity mechanisms but there are currently no recommendations on this topic. In this context, the investigators have developed a speech rehabilitation procedure specific to the needs of ELTPR patients. They rely on cognitive hypotheses explaining the disorders but also on models of rehabilitation-induced neural plasticity likely to improve cognitive reserve before surgery. The investigators hypothesize that preoperative cognitive language rehabilitation in ELTPR patients may decrease surgical risk and improve postoperative language prognosis. The primary objective is to demonstrate the protective efficacy of preoperative speech rehabilitation on language performance postoperatively.
In this study, participants will receive unilateral Deep Brain Stimulation (DBS) for treatment of epilepsy, with network-based stimulation targets specifically defined using a stereo-electro-encephalographic evaluation and chronic recordings using the Medtronic Percept™ primary cell (PC) Neurostimulator DBS System with BrainSense™ Technology. The hypothesis is that, compared to no stimulation or to standard duty cycle high frequency stimulation, epilepsy neuromodulation using low frequency stimulation and informed by network architecture in patients with epilepsy that arises in a hippocampus that also subserves memory - epilepsy in a precious hippocampus (EPH) - will result in a significant decrease in seizure frequency and severity, paralleled by a decrease in EEG spike counts and improved memory function.