A wearable sensor system for neonatal seizure monitoring

2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks (BSN) Pub Date : 2017-05-09 DOI:10.1109/BSN.2017.7935999

Hongyu Chen, Xiao Gu, Zhenning Mei, Ke Xu, Kai Yan, Chunmei Lu, Laishuan Wang, Feng Shu, Qixin Xu, S. Oetomo, Wei Chen

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引用次数: 14

Abstract

A novel wearable sensor system for seizure monitoring of neonates comprised of smart clothing, video recording and cloud platform is presented. Textile electrodes and Inertial Measurement Unit (IMU) are embedded in the smart clothing to obtain ECG signal and motion signal whereby epileptic seizure detection algorithm is performed. Moreover, a video monitoring module provides real-time information about patients. The cloud platform receives the pre-processed data and enables remote monitoring, centralized signal processing and data management. Comparison with commercial instruments shows that the smart clothing is capable of acquiring high-quality signals. Pilot tests under disinfection operations at Children's Hospital of Fudan University confirm clinical feasibility of the proposed system. The scalability and modularity of the unobtrusive wearable front end and the design of system architecture based on cloud enable the whole system with great potential in clinical practice and home monitoring scenarios.

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用于新生儿癫痫监测的可穿戴传感器系统

提出了一种新型的可穿戴式新生儿癫痫监测传感器系统，该系统由智能服装、视频记录和云平台组成。在智能服装中嵌入纺织电极和惯性测量单元(IMU)，以获取心电信号和运动信号，从而执行癫痫发作检测算法。此外，视频监控模块提供患者的实时信息。云平台接收预处理后的数据，实现远程监控、集中信号处理和数据管理。与商用仪器的对比表明，该智能服装能够获得高质量的信号。复旦大学儿童医院消毒操作的试点测试证实了该系统的临床可行性。不显眼的可穿戴前端的可扩展性和模块化，以及基于云的系统架构设计，使整个系统在临床实践和家庭监控场景中具有巨大的潜力。

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2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks (BSN)

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