使用光电容积脉搏波进行简单的手势识别

Karthik Subramanian, Celal Savur, F. Sahin
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引用次数: 4

摘要

开发了一种新型可穿戴手环,该手环使用三个光电体积脉搏波(PPG)传感器来实现手势识别(HGR)。这些传感器通常用于心率估计和心血管疾病的检测。当手臂在运动时,由于人为因素,从这些传感器获得的心率估计将被忽略。这项研究表明,这些人工制品在本质上是可重复的,基于所做的手势。将开发的手环与使用表面肌电(s-EMG)进行手势识别的Myo臂环进行了比较研究。基于本文采用监督机器学习技术的结果,可以看出PPG可以作为手势识别应用的一种可行的替代模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Photoplethysmography for Simple Hand Gesture Recognition
A new wearable band is developed which uses three Photoplethysmography (PPG) sensors for the purpose of hand gesture recognition (HGR). These sensors are typically used for heart rate estimation and detection of cardiovascular diseases. Heart rate estimates obtained from these sensors are disregarded when the arm is in motion on account of artifacts. This research suggests and demonstrates that these artifacts are repeatable in nature based on the gestures performed. A comparative study is made between the developed band and the Myo Armband which uses surface-Electromyography (s-EMG) for gesture recognition. Based on the results of this paper which employs supervised machine learning techniques, it can be seen that PPG can be utilized as a viable alternative modality for gesture recognition applications.
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