排序方式: 共有79条查询结果,搜索用时 171 毫秒
71.
In this paper, a new control system based on forearm electromyogram (EMG) is proposed for computer peripheral control and artificial prosthesis control. This control system intends to realize the commands of six pre-defined hand poses: up, down, left, right, yes, and no. In order to research the possibility of using a unified amplifier for both electroencephalogram (EEG) and EMG, the surface forearm EMG data is acquired by a 4-channel EEG measurement system. The Bayesian classifier is used to classify the power spectral density (PSD) of the signal. The experiment result verifies that this control system can supply a high command recognition rate (average 48%) even the EMG data is collected with an EEG system just with single electrode measurement. 相似文献
72.
73.
74.
75.
76.
77.
人与计算机的交互技术是一种新型的计算机技术,且逐渐演变为一种主流技术和计算机领域的技术热点。为了能够更好的识别手势和跟踪手势的运动轨迹,提出了基于OPENCV的手势识别系统,系统引入了OPENCV计算机视觉库,OPENCV作为优秀的计算机视觉库,为设计的实现提供了便捷的代码,利用OPENCV技术中的图像处理算法,首现通过摄像头采集数据图像,并对采集到的图像进行一系列的缩放,去噪以及锐化等处理,然后对人体手势建立肤色模型,然后经过灰度阈值化来转换成二值图像,得到手轮廓的数据图像后,采用轮廓匹配方法识别出手型。最后通过10种基本的手势模型对比验证了本系统具有一定的实时性,并且识别率可以达到95%以上。 相似文献
78.
79.