A machine learning based frame work for classification of neuromuscular disorders

G. Murthy, G. Phawahan Saii, T. Pavani, J. Lalith Mohan
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引用次数: 1

Abstract

Neuromuscular disorders, primarily due to either random mutation of genes or problems in the human immune system, cause muscular atrophy, weakness or balancing problems. With an estimated diabetic population of 578 million by 2030, the subsequent risk of being affected by diabetic neuropathy is also more. In particular Amyotrophic lateral sclerosis (ALS) is the non-curable disease caused by death or loss of neurons. Current work proposes a machine learning based frame work to demarcate between normal and myopathic subjects. Electromyography (EMG) signals taken from the biceps brachii muscle located on the upper arm are considered for the purpose.
基于机器学习的神经肌肉疾病分类框架
神经肌肉疾病,主要是由于基因的随机突变或人类免疫系统的问题,导致肌肉萎缩,无力或平衡问题。据估计,到2030年,糖尿病人口将达到5.78亿,糖尿病神经病变的后续风险也会更高。特别是肌萎缩性侧索硬化症(ALS)是由神经元死亡或丧失引起的不可治愈的疾病。目前的工作提出了一个基于机器学习的框架来区分正常和肌病受试者。肌电图(EMG)信号取自肱二头肌位于上臂的目的是考虑。
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