无孔不入的实时生物医学监测系统

Ajay M. Cheriyan, Albert O. Jarvi, Z. Kalbarczyk, R. Iyer, K. Watkin
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引用次数: 4

摘要

随着低成本、节能硬件的巨大进步,以及最近对生物医学嵌入式系统的兴趣,许多传统的生物医学系统可以被更小的嵌入式系统所取代,这些嵌入式系统可以进行实时分析,向用户提供生物反馈。本文介绍了一个嵌入式系统的原型,该系统能够实时采集数据,利用模拟和数字传感器和处理,计算生理变量和指标。这些指标反过来可以用来确定有关用户总体健康的信息。传感器提供运动、脑电波活动(EEG)和血氧(SpO2)信息。所提出的系统自动计算特定应用的度量,并将检测方案的结果指示给用户和监控基站。所使用的指标已经通过使用癫痫发作患者的原始数据和过去的研究进行了验证。本文还讨论了该系统的应用场景,并讨论了基于FPGA的实现架构。
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Pervasive real-time biomedical monitoring system
With the tremendous advancements in low cost, power efficient hardware and the recent interest in biomedical embedded systems, numerous traditional biomedical systems can be replaced with smaller embedded systems that do real-time analysis to provide bio-feedback to the users. This paper presents a prototype of an embedded system which is capable of real-time data collection, using analog and digital sensors and processing, to compute physiological variables and metrics. These metrics in turn can be used to determine information about the user's general well being. The sensors provide motion, brain wave activity (EEG) and blood oxygenation (SpO2) information. The system presented automatically computes the application specific metrics and indicates the results of the detection scheme to the user and to a monitoring base station. The metrics being used have been validated using raw data from patients suffering epileptic seizures and from past research. The paper also deals with application scenarios for such systems and architecture for an FPGA based implementation is discussed.
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