神经肌肉连接处的分类和神经肌肉疾病的肌腱记录的频谱图

2017 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT) Pub Date : 2017-04-01 DOI:10.1109/EBBT.2017.7956768

T. Artug, İ. Göker, O. Osman, B. Baslo

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引用次数: 0

摘要

本研究通过EMG模拟器v3.6构建正常、神经源性和肌病运动单元的神经肌肉连接处和肌腱记录的频谱图对鉴别诊断的影响进行了研究。选择多层感知器作为分类器。如果仅将神经肌肉接点记录应用于网络，则性能为73.33%。仅将跟腱记录应用于网络输入时，性能为94.67%。当神经肌肉连接和肌腱记录一起应用于网络时，性能为100%。

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Classification of neuromuscular junction and tendon recordings of neuromuscular diseases by their spectrogram

In this study, the effect of spectrograms from neuromuscular junction and tendon records for normal, neurogenic and myopathic motor units being constructed via EMG Simulator v3.6 on the differential diagnosis were investigated. Multi-layer perceptron is chosen as classifier. If only the neuromuscular junction records are applied to the network, the performance is 73.33%. If only tendon records are applied to the input of network, the performance is 94.67%. When neuromuscular junction and tendon records are applied together to the network, the performance is 100%.

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2017 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT)

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