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A Study on a Recognition Method for Specific Motions by Processing Outputs of Artificial Neural Networks with Different Input Signals

机译:通过处理具有不同输入信号的人工神经网络的输出来识别特定运动的方法

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摘要

This paper studies improvement of the clinical practicality of the control command input method for motor disabled patients using the recognition of specific motions via an artificial neural network (ANN). Several good ANNs that had different combinations of input signals and/or different number of neurons in the hidden layer were selected for each subject. The final recognition was determined by the majority decision rule by three good ANNs. The AND operation of the outputs of selected ANNs was also used to reduce the number of misrecognitions. The results with neurologically intact subjects and a hemiplegic patient showed that the proposed method would be effective clinically compared to the method using a single ANN with a fixed combination of input signals for all patients. It was also shown that trained ANNs with the proposed method could be used on other days with good performance.
机译:本文研究了通过人工神经网络(ANN)识别特定运动来改善运动障碍患者控制命令输入方法的临床实用性的方法。为每个对象选择了几种具有不同输入信号组合和/或隐藏层中神经元数量的神经网络。最终的认可是由三个良好的人工神经网络根据多数决策规则确定的。所选ANN的输出的AND运算也用于减少误识别的次数。神经学完好的受试者和偏瘫患者的结果表明,与使用单个ANN和所有患者固定输入信号组合的方法相比,该方法在临床上将是有效的。还表明,采用该方法训练的人工神经网络可以在其他情况下以良好的性能使用。

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