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EMG Biometric Systems Based on Different Wrist-Hand Movements

机译：基于不同的手动运动的EMG生物识别系统

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摘要

Electromyogram (EMG) acquisition and analysis is growing in importance with human attempts to interact with and control equipment such as robots, prostheses or virtual environments. In some cases, only approved users should be permitted these capabilities. For these applications, securing EMG-based control is a major open question - to the best of the authors’ knowledge, no prior art exists which can identify individuals from a wide range of wrist-hand gestures EMG readings within the wearable device. This paper addresses this problem. Techniques are presented which allow EMG to be used as a biometric, allowing users to verify themselves. An EMG-sensing armband attached to the lower forearm is used to anonymously authenticate users as a member of an approved group, or to identify themselves uniquely. For the development of extensive biometric system, three EMG datasets with similar EMG sensing in different sessions were exploited. For verification, accuracy of up to 93% is achieved, with 92% achieved for identification. The system is also shown to operate in real-time on an ARM Cortex A-53 embedded processor suitable for housing in an EMG wearable device, incurring latencies of 1.06 ms and 1.61 ms for verification and identification respectively. These metrics are comfortably sufficient for use in real-time, battery-powered EMG authentication devices.
机译：电灰度（EMG）采集和分析的重要性与人类尝试与机器人，假体或虚拟环境等控制设备相互作用的重要性。在某些情况下，应仅允许批准的用户这些功能。对于这些应用，确保基于EMG的控制是一个主要的开放问题 - 据作者的知识，并且存在现有技术，其可以识别可穿戴设备内的各种手势手势EMG读数的个体。本文解决了这个问题。提出了允许EMG用作生物识别的技术，允许用户验证自己。连接到下前臂的EMG传感臂用于匿名验证用户作为批准组的成员，或者唯一地识别。对于广泛的生物识别系统的开发，利用不同会话中具有类似EMG感测的三个EMG数据集。为了验证，实现高达93％的准确性，达到92％的鉴定。该系统还示出了在ARM皮层A-53嵌入式处理器上实时运行，适用于EMG可穿戴装置的外壳，产生1.06ms和1.61 ms的延迟分别进行验证和识别。这些度量标准舒适地用于实时使用电池供电的EMG认证设备。

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