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一种用于通过耦合麦克风 - 加速度计传感器对记录的肌动图(MMG)信号源分离的数学模型。

A mathematical model for source separation of MMG signals recorded with a coupled microphone-accelerometer sensor pair.

作者信息

Silva Jorge, Chau Tom

机构信息

Rehabilitation Engineering Department, Bloorview MacMillan Children's Centre, 150 Kilgour Road, Toronto, ON M4G 1R8, Canada.

出版信息

IEEE Trans Biomed Eng. 2005 Sep;52(9):1493-501. doi: 10.1109/TBME.2005.851531.

Abstract

Recent advances in sensor technology for muscle activity monitoring have resulted in the development of a coupled microphone-accelerometer sensor pair for physiological acousti signal recording. This sensor can be used to eliminate interfering sources in practical settings where the contamination of an acoustic signal by ambient noise confounds detection but cannot be easily removed [e.g., mechanomyography (MMG), swallowing sounds, respiration, and heart sounds]. This paper presents a mathematical model for the coupled microphone-accelerometer vibration sensor pair, specifically applied to muscle activity monitoring (i.e., MMG) and noise discrimination in externally powered prostheses for below-elbow amputees. While the model provides a simple and reliable source separation technique for MMG signals, it can also be easily adapted to other aplications where the recording of low-frequency (< 1 kHz) physiological vibration signals is required.

摘要

用于肌肉活动监测的传感器技术的最新进展促成了一种用于生理声学信号记录的耦合麦克风 - 加速度计传感器对的开发。这种传感器可用于在实际环境中消除干扰源,在这些环境中,声学信号被环境噪声污染会混淆检测且不易去除[例如,肌动电流图(MMG)、吞咽声音、呼吸和心音]。本文提出了一种用于耦合麦克风 - 加速度计振动传感器对的数学模型,特别适用于肌肉活动监测(即MMG)以及肘部以下截肢者的外部供电假肢中的噪声辨别。虽然该模型为MMG信号提供了一种简单可靠的源分离技术,但它也可以很容易地适用于其他需要记录低频(<1 kHz)生理振动信号的应用。

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