多种生理信号监测的可穿戴设备研发

发布时间：2018-05-31 17:45

本文选题：可穿戴设备 + 生理信号监测　；参考：《电子科技大学》2017年硕士论文

【摘要】：为了帮助人们在日常生活中更好地监测自身健康状况和满足人们消费升级的需求,可穿戴设备的研发愈发活跃。本文设计了一种可对多种生理信号进行监测的可穿戴设备。在硬件上,这款可穿戴设备由智能硬件和穿戴物两部分构成。其中,智能硬件由多种生理信号监测模块、核心处理平台和电源模块等构成,主要负责实现对多种生理信号的采集和信号处理。穿戴物由布料构成的本体、嵌入到本体中的导线和传感器接口构成,其使得整个可穿戴设备更加方便用户使用。在日常生活中,用户只需把智能硬件插入到穿戴物内,然后穿戴上该设备即可实现对自身多种生理信号的监测,例如心电信号、心阻抗信号、呼吸信号、人体运动信号和肌电信号。在软件上,本文所设计的设备应用程序通过调用设备驱动程序和多种信号预处理算法去控制整个可穿戴设备正常工作从而得到高质量生理信号数据。而本文所开发的终端设备应用程序则通过网络接收来自可穿戴设备的数据从而能够实时地显示各种生理信号的波形。为了验证本文所研发的可穿戴设备的性能和稳定性,笔者进行了大量的实验。在前期的性能测试实验中,不光验证了各个信号预处理算法的效果,还证明了本系统能够准确地采集生理信号。而在长时间的稳定性测试过程中,证明了整个系统不仅工作稳定、各种生理信号波形能够实时地显示,而且各种生理信号数据的质量符合预期效果。因此,本文所研发的可穿戴设备能够实现对用户的多种生理信号进行长时间的监测从而帮助用户更好地了解自身健康状况。
[Abstract]:In order to help people better monitor their health and meet the needs of consumption upgrading in their daily life, wearable devices are becoming more and more active. In this paper, a wearable device which can monitor many physiological signals is designed. In hardware, the wearable device consists of intelligent hardware and wearables. Among them, the intelligent hardware consists of a variety of physiological signal monitoring module, core processing platform and power module, mainly responsible for the collection and processing of a variety of physiological signals. The wearable object is made up of fabric body, wire and sensor interface embedded in body, which makes the wearable device more user-friendly. In daily life, users simply insert smart hardware into their wearables, and then wear the device to monitor their own physiological signals, such as ECG signals, heart impedance signals, respiratory signals, etc. Human motion signals and EMG signals. In software, the device application program designed in this paper can control the whole wearable device to work properly by calling device driver and signal preprocessing algorithm to get high quality physiological signal data. The terminal device application developed in this paper receives the data from wearable devices through the network so that the waveform of various physiological signals can be displayed in real time. In order to verify the performance and stability of wearable devices developed in this paper, a large number of experiments have been carried out. In the previous performance test experiments, not only the effect of each signal preprocessing algorithm is verified, but also the system can accurately collect physiological signals. During the long time stability test, it is proved that the whole system not only works stably, but also shows all kinds of physiological signal waveforms in real time, and the quality of all kinds of physiological signal data accords with the expected effect. Therefore, the wearable device developed in this paper can monitor a variety of physiological signals for a long time to help users understand their health better.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R318;TP368.33

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