北京林业大学学报2017，Vol.39Issue(2)：117-124,8.DOI:10.13332/j.1000--1522.20160290
面向整枝机控制的手势识别技术研究
Gesture control technology based on surface electromyography for automatic pruning machine
摘要
Abstract
To realize the gesture control for automatic pruning machine needs to complete two parts of work, gesture recognition and wireless remote control and therefore, the technology of hand gesture recognition based on the surface electromyography ( sEMG) signal was studied. Firstly, according to six working states of pruning machine, six corresponding gestures were defined, which comprised fist, palm lateral supination, palm lateral pronation, palm supination, palm pronation and finger spread. Secondly, collected sEMG signal was preprocessed, including noise elimination and motion segmentation. The motion signals were then analyzed in time domain and time-frequency domain, and three kinds of features were computed, which were mean absolute value, coefficient of autoregressive parameter model, and average energy of each subband after wavelet decomposition. Lastly, support vector machine classifier was constructed to conduct single-user and multi-user recognition experiments and the best parameters of the classifier were obtained by V-fold cross validation. The results of gesture recognition experiments showed that, the highest accuracy of single-user experiment reached 100% and the average accuracy of single-user experiment (98. 07%) was higher than that of multi-user experiment (91. 19%) . This study lays foundation for the implementation of the follow-up work of gesture control for pruning machine and provides an effective new way to promote the intelligent and human-computer interaction process of forestry machinery.关键词
表面肌电信号/手势识别/整枝机/手势控制Key words
surface electromyography/gesture recognition/pruning machine/gesture control分类
农业科技引用本文复制引用
胡昕卉,李文彬,阚江明..面向整枝机控制的手势识别技术研究[J].北京林业大学学报,2017,39(2):117-124,8.基金项目
国家林业局林业技术推广项目(2016-29). （2016-29）
