穿戴式肌电采集设备的研究与应用

发布时间：2019-01-30 16:03

【摘要】：近年来,基于生物电信号的人机交互技术是人机交互的研究前沿和热点之一。表面肌电信号记录了肌肉在自主收缩时由肌纤维产生的电信号。它作为生物／机械人机接口的一种重要输入信号,因其采集方便、对身体无创伤的优点,得到了广泛重视。但是常规肌电采集设备具有体积笨重、价格较高、不便携带的局限性。本论文将基于穿戴式设备的上肢表面肌电采集与人机交互技术结合起来,设计出一款可穿戴肌电采集系统,从而使基于表面肌电的人机接口技术进入家庭成为可能。本论文主要内容包括以下两个方面：1.穿戴式肌电采集设备硬件设计本论文首先对表面肌电采集电路各功能单元进行设计和验证,在此基础对各电路模块的功能进行了细致分析,提出了常规表面肌电采集方式的不足。随后,对常用肌电采集电路滤波器的设计进行了优化,研究对比了模拟滤波和数字滤波在表面肌电采集中的功能。通过对模拟滤波、放大、数字滤波、蓝牙技术、FPC基板、低功耗小封装器件的巧妙运用设计了基于NRF51822蓝牙4.0和FPC穿戴式双通道肌电采集下位机设备。2.基于上肢表面肌电信号手势识别算法的设计利用SVM对传输到PC端的不同手势的上肢表面肌电信号进行离线分析,包含了预处理、特征值的提取、归一化和SVM核函数的选择等。在离线分析获得满意的分类结果后,将训练所得模板载入基于SVM分类器的在线控制系统,控制受试设备按照上肢运动产生的表面肌电信号完成任务。其准确率超过90%。在上述研究工作的基础上,本设计完成的穿戴式肌电采集设备集电极、电极导联线和表面肌电采集电路于一体,设备小巧、功耗较低、方便使用。本文最后验证了基于表面肌电信号的穿戴式设备在人机交互领域应用的可行性。
[Abstract]:In recent years, the technology of human-computer interaction based on bioelectric signal is one of the research frontiers and hot spots in human-computer interaction. Surface EMG signals record electrical signals generated by muscle fibers when they contract autonomously. As an important input signal of biological / mechanical man-machine interface, it has been paid more and more attention because of its convenient acquisition and non-invasive advantages. But the conventional EMG acquisition equipment has the limitation of bulky, high price and inconvenient to carry. In this paper, a wearable EMG acquisition system based on wearable device is designed by combining the EMG acquisition technology of the upper limb with human-computer interaction technology, which makes it possible for the interface technology based on SEMG to enter the home. The main contents of this paper include the following two aspects: 1. Hardware Design of wearable Electromyography acquisition device this paper first designs and verifies the functional units of the surface electromyography acquisition circuit. On this basis, the functions of each circuit module are analyzed in detail. The deficiency of conventional surface electromyography acquisition method is put forward. Then, the design of common EMG acquisition circuit filter is optimized, and the functions of analog filter and digital filter in surface EMG acquisition are studied and compared. By using analog filtering, amplifying, digital filtering, Bluetooth technology, FPC substrate and low-power small package device, the device based on NRF51822 Bluetooth 4.0 and FPC wearable dual-channel electromyography acquisition is designed. 2. Based on the design of upper limb EMG signal gesture recognition algorithm, SVM is used to analyze the upper limb surface EMG signal transmitted to PC, which includes pretreatment, extraction of eigenvalue, normalization and selection of SVM kernel function. After off-line analysis, the training template is loaded into the on-line control system based on SVM classifier to control the equipment to complete the task according to the surface EMG signal generated by the upper limb movement. The accuracy is more than 90. On the basis of the above research work, the wearable electromyoelectric collecting device is designed, which integrates the electrode, the electrode lead wire and the surface electromyography acquisition circuit. The device is compact, low power consumption and easy to use. Finally, the feasibility of the wearable device based on surface EMG signal in the field of human-computer interaction is verified.
【学位授予单位】：东南大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：R318;TN911.7

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