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Design and implementation of wireless point-of-care health monitoring systems: Diagnosis for sleep disorder and cardiovascular diseases.

机译：无线即时医疗保健监视系统的设计和实现：睡眠障碍和心血管疾病的诊断。

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摘要

Chronic sleep disorders are present in 40 million people in the United States. More than 25 million people remain undiagnosed and untreated, which accounts for over ;In this dissertation, several remote POC systems are reported to diagnose sleep disorders and cardiovascular diseases to overcome the drawbacks of the current systems. First, two types of remote POC systems were developed for sleep disorders. One was designed with ZigBee and Wi-Fi network, which provides increase/decrease the number of physiological channels flexibly by using ZigBee star network. It also supports the remote real-time monitoring by extending WPAN to WLAN with combination of two wireless communication topologies, ZigBee and Wi-Fi. The other system was designed with GSM/WCDMA network, which removes the restriction of testing places and provides remote real-time monitoring in the true sense of the word. Second, a fully wearable textile integrated real-time ECG acquisition system for football players was developed to prevent sudden cardiac death. To reduce power consumption, adaptive RF output power control was implemented based on RSSI and the power consumption was reduced up to 20%. Third, as an application of measuring physiological signals, a wireless brain machine interface by using the extracted features of EOG and EEG was implemented to control the movement of a robot. The acceleration/deceleration of the robot is controlled based on the attention level from EEG. The left/right motion of eyeballs of EOG is used to control the direction of the robot. The accuracy rate was about 95%.;These kinds of health monitoring systems can reduce the exponentially increasing healthcare costs and cater the most important healthcare needs of the society.
机译：在美国，有4000万人患有慢性睡眠障碍。超过2500万人仍未得到诊断和治疗，占了超过200万人；在本文中，据报道，一些远程POC系统可以诊断睡眠障碍和心血管疾病，以克服现有系统的缺点。首先，针对睡眠障碍开发了两种类型的远程POC系统。一种是使用ZigBee和Wi-Fi网络设计的，它可以通过使用ZigBee星形网络灵活地增加/减少生理通道的数量。它还将WPAN扩展到WLAN，并结合了ZigBee和Wi-Fi这两种无线通信拓扑，从而支持远程实时监视。另一个系统是使用GSM / WCDMA网络设计的，它消除了测试地点的限制，并提供了真正意义上的远程实时监控。其次，开发了用于足球运动员的完全可穿戴的纺织品集成实时心电图采集系统，以防止心源性猝死。为了降低功耗，基于RSSI实施了自适应RF输出功率控制，功耗降低了20％。第三，作为测量生理信号的应用，通过利用EOG和EEG的提取特征实现了无线脑机接口来控制机器人的运动。机器人的加/减速基于来自EEG的注意力水平进行控制。 EOG眼球的左/右运动用于控制机器人的方向。准确率约为95％。；这些类型的健康监控系统可以降低呈指数增长的医疗保健成本，并满足社会最重要的医疗保健需求。

著录项

  • 作者

    Oh, Se Chang.;

  • 作者单位

    University of Arkansas.;

  • 授予单位 University of Arkansas.;
  • 学科 Engineering Biomedical.;Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 144 p.
  • 总页数 144
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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