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基于模式识别的便携式、低功耗和低成本肌电图控制器中模拟前端的比较(2015年电磁生物控制会议)

Analog Front-Ends comparison in the way of a portable, low-power and low-cost EMG controller based on pattern recognition EMBC 2015.

作者信息

Mastinu Enzo, Ortiz-Catalan Max, Hakansson Bo

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:2111-4. doi: 10.1109/EMBC.2015.7318805.

Abstract

Compact and low-noise Analog Front-Ends (AFEs) are becoming increasingly important for the acquisition of bioelectric signals in portable system. In this work, we compare two popular AFEs available on the market, namely the ADS1299 (Texas Instruments) and the RHA2216 (Intan Technologies). This work develops towards the identification of suitable acquisition modules to design an affordable, reliable and portable device for electromyography (EMG) acquisition and prosthetic control. Device features such as Common Mode Rejection (CMR), Input Referred Noise (IRN) and Signal to Noise Ratio (SNR) were evaluated, as well as the resulting accuracy in myoelectric pattern recognition (MPR) for the decoding of motion intention. Results reported better noise performances and higher MPR accuracy for the ADS1299 and similar SNR values for both devices.

摘要

紧凑且低噪声的模拟前端(AFE)对于便携式系统中生物电信号的采集变得越来越重要。在这项工作中,我们比较了市场上两种流行的AFE,即ADS1299(德州仪器)和RHA2216(Intan Technologies)。这项工作旨在识别合适的采集模块,以设计一种经济实惠、可靠且便携的用于肌电图(EMG)采集和假肢控制的设备。评估了诸如共模抑制(CMR)、输入参考噪声(IRN)和信噪比(SNR)等设备特性,以及在运动意图解码的肌电模式识别(MPR)中所得到的准确性。结果表明,ADS1299具有更好的噪声性能和更高的MPR准确性,并且两种设备的SNR值相似。

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