手势
手势识别
计算机科学
人工智能
计算机视觉
语音识别
特征(语言学)
集合(抽象数据类型)
特征提取
模式识别(心理学)
哲学
语言学
程序设计语言
作者
Gang Ma,Haofeng Chen,Peng Wang,Shen Dong,Xiaojie Wang
出处
期刊:Mechatronics
[Elsevier]
日期:2023-10-01
卷期号:94: 103039-103039
标识
DOI:10.1016/j.mechatronics.2023.103039
摘要
In this paper, we proposed a novel two-electrode, frequency-scan gesture recognition system based on bio-impedance measurement. This method not only achieves a high accuracy in recognizing common gestures and pinch gestures, but also reduces the measurement complexity and the number of electrodes. We developed a bespoke circuit with two medical electrodes to collect data from the back of the hand and presented a frequency-scan method to increase the diversity of impedance data. Feature extraction method was adapted to explore the representative features for gesture recognition, and machine learning classification models with five-fold cross-validation were used to train and realize accurate gesture recognition. To verify the effectiveness of this system, we designed two groups of nine gestures in a hand-gesture recognition experiment. The results showed that the system achieved a recognition accuracy of 98.3% with a group of four common gestures and an accuracy of 98.5% with a group of six pinch gestures. The proposed method realized a higher accuracy in pinch gesture set while using fewer electrodes. Additionally, we designed two real-time proof-of-concept interactive scenarios to demonstrate the general applications of this system.
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