With the advancement in artificial intelligence (AI) and machine learning (ML) techniques,
researchers are striving towards employing these techniques for advancing clinical practice …

Nearly one-third of patients with epilepsy continue to have seizures despite optimal
medication management. Systems employed to detect seizures may have the potential to …

Epilepsy affects almost 1% of the population and most of the approximately 20–30% of
patients with refractory epilepsy have one or more seizures per month. Seizure detection …

Neurostimulation is now an established therapy for the treatment of movement disorders,
pain, and epilepsy. While most neurostimulation systems available today provide stimulation …

Electrocardiography has added value to automatically detect seizures in temporal lobe
epilepsy (TLE) patients. The wired hospital system is not suited for a long-term seizure …

Epilepsy is one of the most prevalent paroxystic neurological disorders. It is characterized by
the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant …

Studies with heart rate variability have revealed interictal autonomic alterations in patients
with epilepsy. In addition, epilepsy is frequently associated with ictal tachycardia or …

Epileptic seizures can lead to changes in autonomic function affecting the sympathetic,
parasympathetic, and enteric nervous systems. Changes in cardiac signals are potential …

Purpose This study investigates the performance of a cardiac-based seizure detection
algorithm (CBSDA) that automatically triggers VNS (NCT01325623). Methods Thirty-one …

Objective To develop and prospectively evaluate a method of epileptic seizure detection
combining heart rate and movement. Methods In this multicenter, in-home, prospective …