基于SVM、K-NN和DA算法的神经肌肉疾病诊断分类第一部分

Hanife Küçük, Ilyas Eminoglu
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引用次数: 1

摘要

本研究包括一个由前三个阶段组成的分类结构,用于自动诊断肌萎缩性侧索硬化症(ALS)的神经肌肉疾病,肌病是一种肌肉疾病。在本研究中;EMG标记将被确定为最佳MUAP,以获得评论签名EMG的权利。将第一阶段原始肌电数据剔除噪声后,分离出分割阶段MUAP。在聚类阶段,采用混合结构优化聚类数量。在下一节中,MUAP的集群将允许使用小数据集进行事务处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neuromuscular disease diagnosis of SVM, K-NN and DA algorithm based classification part-I
This study includes a classification structure consisting of first three stages for the automatic diagnosis of the neuromuscular disease of ALS (Amyotrophic Lateral Sclerosis) and myopathy being a muscular disease. In this study; EMG mark representing best MUAP will be determined for the right to comment sign EMG. After the first stage of the raw EMG data eliminated by noise the segmentation stage MUAP were separated. In the clustering stage, a hybrid structure is used to optimize the number of clusters. MUAP's clustering will allow transactions to be made with small data sets in the next second section.
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