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A method of recognizing finger-flexing motion using muscle action potential waveforms

机译:一种利用肌肉动作电位波形识别手指屈伸运动的方法

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For the bedridden person's lives, not only the movement but also the communication have been restricted. Regarding our support of a daily life, the construction of the human interface system that substitutes the movement means and the means of communication becomes an important problem. Regarding the human interface system, the system device that can be easily used for many bedridden people is needed. Hence, we will propose the electromyogram interface system that have finger-flexing motion and can be easily moved even in the state of bedridden. The prototype model is actually constructed with an electromyograph of the telemeter type and a computer. The finger-flexing motion is identified by the discrimination analysis method in the data analysis. In this report, the prototype system is actually produced In the system, the finger-flexing motion can be recognizes more than 90% on average. It means that the reproduction of the means of communication can be used by this technique.
机译:对于卧床不起的人的生活,不仅行动受限,而且沟通也受到限制。关于我们对日常生活的支持,替代移动手段和通信手段的人机界面系统的构建成为一个重要的问题。关于人机接口系统,需要可以容易地用于许多卧床不起的人的系统设备。因此,我们将提出一种具有手指弯曲动作并且即使在卧床不起的状态也能够容易移动的肌电图接口系统。原型模型实际上是由遥测型肌电图仪和计算机构成的。在数据分析中,通过辨别分析方法来识别手指弯曲动作。在此报告中,实际生产了原型系统。在该系统中,平均可以识别手指弯曲动作的90%以上。这意味着可以通过该技术来使用通信手段的再现。

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