Detection of nocturnal frontal lobe seizures in pediatric patients by means of accelerometers: A first study

Abstract

The monitoring of epileptic seizures is mainly done by means of video/EEG-monitoring. Although this method is considered as the golden standard, it is not comfortable for the patient as the EEG-electrodes have to be attached to the scalp which hampers the patient's movement. This makes long term home monitoring not feasible. A detection system with accelerometers attached to the wrists and ankles can solve this problem. Nocturnal frontal lobe seizures often include bicycle pedaling movements or uncontrolled movements with the arms which are clearly visible in the accelerometer signals. Data from three patients suffering from nocturnal frontal lobe seizures is used in this paper for the development of an automatic detection algorithm for this type of seizure. First movement epochs are detected as a preprocessing step by calculating the standard deviation of a sliding window. Afterwards a moving average filter is applied to the data and thresholds are set to the signals of the arms and legs to detect the seizures. This resulted in an algorithm with a sensitivity of 91.67% and a specificity of 83.92%.

Seizure onset detection based on a Uni- or Multi-modal Intelligent Seizure Acquisition (UISA/MISA) system

“…An alarm system, capable of detecting seizures, could alert relatives and caretakers and ensure help for the patient. Several groups [1], [2] have already tried to develop such a system based on motion data, but none of them is performing well enough to reach clinical use. We therefore propose a new automatic detection algorithm capable of capturing the seizures with motor manifestations, without too many false alarms.…”

Automatic video detection of body movement during sleep based on optical flow in pediatric patients with epilepsy

“…The algorithm detected all the motor events, and 43-89% of the detections was correct. Jallon et al [9] and Cuppens et al [6] also studied the detection of epileptic seizures with accelerometers and Conradsen et al [4] used a multi-modal approach. In our approach, we detect the movement contactless, which is more comfortable for the patient.…”

Multi-modal intelligent seizure acquisition (MISA) system — A new approach towards seizure detection based on full body motion measures

“…A new device for warning about seizures is therefore needed. Several groups have worked on detecting seizures based on ACM data [1], [6], [7]. Nijsen et al [ have shown that in a test on 18 patients it was possible to detect the seizures of 10 patients based on visual inspection of ACM data.…”