A Novel Portable Seizure Detection Alarm System: Preliminary Results
A Novel Portable Seizure Detection Alarm System: Preliminary Results
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DOI：
10.1097/wnp.0b013e3182051320
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发表时间：
2011-02-01
影响因子：
2.4
通讯作者：
Kuzniecky, Ruben
中科院分区：
文献类型：
--
作者：
Kramer, Uri;Kipervasser, Svetlana;Kuzniecky, Ruben
癫痫发作的不可预测和随机发生是影响患者及其家人的最令人痛苦的问题。无人看管的癫痫发作可能会造成严重后果，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，并提醒患者和家属识别特定癫痫发作的运动活动。发作数据前瞻性地获得了连续的患者承认两个视频脑电图单位。本研究纳入了有运动性癫痫发作、阵挛性或强直性癫痫发作或强直-阵挛性癫痫发作病史的患者或伴有频繁继发全身化的复杂部分性癫痫发作的患者。安装在手镯上的“运动传感器”单元连接到一个手腕。“传感器”包含一个三轴加速度计和一个发射器。三轴运动的数据被传输到便携式计算机。专门为此开发的算法分析了记录的数据。将癫痫发作的警报与视频EEG数据进行比较。在31例招募患者中的15例中采集了发作数据。该算法正确识别了22次（91%）捕获的癫痫发作中的20次，并在17秒的中位时间内生成警报。所有事件持续>30秒（即，19起事件）。该系统未能识别22次癫痫发作中的2次（9%）。在1,692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/报警系统可以识别大多数运动癫痫发作，具有高灵敏度和低误报率。
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.