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一种新型便携式癫痫检测报警系统:初步结果。

A novel portable seizure detection alarm system: preliminary results.

机构信息

Epilepsy Unit, Sourasky Medical Center, Tel Aviv University, Tel Aviv, Israel.

出版信息

J Clin Neurophysiol. 2011 Feb;28(1):36-8. doi: 10.1097/WNP.0b013e3182051320.

Abstract

The unpredictable and random occurrence of seizures is of the most distressful issue affecting patients and their families. Unattended seizures can have serious consequences including injury or death. The objective of this study is to develop a small, portable, wearable device capable of detecting seizures and alerting patients and families on recognition of specific seizures' motor activity. Ictal data were prospectively obtained in consecutive patients admitted to two video-EEG units. This study included patients with a history of motor seizures, clonic or tonic, or tonic-clonic seizures or patients with complex partial seizures with frequent secondary generalization. A "Motion Sensor" unit mounted on a bracelet was attached to one wrist. The "Sensor" contains a three-axis accelerometer and a transmitter. The three-axis movements' data were transmitted to a portable computer. Algorithm specially developed for this purpose analyzed the recorded data. Seizures' alerts were compared with the video-EEG data. Ictal data were acquired in 15 of the 31 recruited patients. The algorithm correctly identified 20 of 22 (91%) captured seizures and generated an alarm within a median period of 17 seconds. All events lasting >30 seconds (i.e., 19 events) were identified. The system failed to identify 2 of 22 seizures (9%). There were eight false alarms during 1,692 hours of monitoring. Preliminary data suggest that this motion detection device/alarm system can identify most motor seizures with high sensitivity and with a low false alarm rate.

摘要

癫痫发作的不可预测和随机性是影响患者及其家属的最痛苦的问题。未得到治疗的癫痫发作可能会产生严重后果,包括受伤或死亡。本研究的目的是开发一种小型、便携式、可穿戴设备,能够检测癫痫发作,并在识别特定癫痫发作的运动活动时向患者和家属发出警报。我们前瞻性地从两个视频脑电图(EEG)病房连续招募的患者中获得了癫痫发作数据。本研究包括有运动性癫痫发作史的患者,如强直阵挛性或强直-阵挛性癫痫发作,或复杂部分性癫痫发作频繁继发全面性发作的患者。一个安装在手链上的“运动传感器”单元连接到一只手腕上。“传感器”包含一个三轴加速度计和一个发射器。三轴运动数据被传输到一个便携式计算机。为此专门开发的算法分析了记录的数据。将癫痫发作警报与视频-EEG 数据进行比较。在招募的 31 名患者中,有 15 名患者获得了癫痫发作数据。该算法正确识别了 22 次捕获癫痫发作中的 20 次(91%),并在中位数为 17 秒的时间内发出警报。所有持续时间超过 30 秒的事件(即 19 个事件)均被识别。该系统未能识别出 22 次癫痫发作中的 2 次(9%)。在 1692 小时的监测中,有 8 次误报。初步数据表明,这种运动检测设备/报警系统可以以高灵敏度和低误报率识别大多数运动性癫痫发作。

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