A Model Based Simulation Analysis For Evaluating Efficacy Of Surface Electromyographic Examination Of Neuromuscular Alternations

Neuromuscular disorders(NMDs)are important common diseases taking place in the nervous system.Patients with NMD often show similar clinical symptoms,like muscle atrophy,muscle weakness,spasm and abnormal movement coordination,so it is important to study the pathology of NMD towards improved diagnosis and therapy.Electromyography(EMG)signals can reflect the neural control and muscle function to a certain degree.EMG signal is regarded as summation of electrical potentials(i.e.,motor unit action potentials,MUAPs)at the detection electrode position,generated by a group of firing motor units(MUs).Surface EMG(sEMG)is measured by electrodes placed on the surface of the skin with easy to use,non-invasive advantages.With the development of surface EMG(sEMG)signals acquisition and signal processing technology,sEMG has been widely used in the diagnosis of NMDs.However,the performance of sEMG examination is limited due to collective effect of various superimposed neuromuscular alternations.Given macroscopic observations from the sEMG examination,possible causes to neuromuscular alternations can be inferred,without clear conclusion to specific MU properties.In addition,the diagnostic efficacy of single sEMG indicators is finite,and multiple indicator integration is the trend of NMD diagnosis and development.Therefore,exploring the sensitivity of the sEMG diagnostic indicators with respect to neuromuscular alternations is the prerequisite to diagnostic applications with multi-indicator integration.Based on this,a neuromuscular model is built to simulate sEMG signals from various potential types of neuromuscular alternations directly.Then the simulated signals is used to evaluate efficacy of sEMG indicators in examining neuromuscular alternations.These findings help to give more accurate interpretation to experimental results in NMD diagnosis,and to reveal underlying pathological mechanisms.The main contents and results of this study are summarized as follows:(1)A neuromuscular model was built.The parameters of First Dorsal Interosseous(FDI)are used as the default model parameters to simulate the sEMG signal of healthy subjects.Based on previous pathological study of NMD,signals derived from specific neuromuscular alternations with definite reasons were simulated by adjusting model parameters to abnormal levels and/or introducing additional model corrections.(2)The simulated sEMG signals are analyzed by a variety of sEMG interference pattern analysis.Under the same degree of neuromuscular alternations,the degree of the indicator changes is used to show the evaluating efficacy of the indicator for neuromuscular alternations.Taking the clustering index(CI)method as an example,the study found that the CI indicator is sensitive to neuromuscular alternations such as MU number decrease,enlarged MUAP duration,increased synchronization,and MUAP amplitude decrease,while its less sensitivity is found to neuromuscular alternations like MU firing rate decrease,change of MU recruitment range and large MU selective loss.(3)The sEMG signals recorded experimentally from healthy individuals and stroke patients are analyzed using the same methods for interference pattern analyses.All methods give macroscopic diagnostic decisions at the individual level.Taking the CI method as an example,the study found complicated neural or muscluar changes in hemiplegia muscles of stroke patients.Some of the hemiplegia muscles show abnormal increased CI indicators,the model simulation results suggest that hemiplegia muscles exhibit neuromuscular alternations such as MU number decrease,enlarged MUAP duration,or increased synchronization of MU;some of the hemiplegia muscles show abnormal decreased CI indicators,simulation results suggest that hemiplegia muscles show neuromuscular alternations like MUAP amplitude decrease(muscle fiber atrophy)and so on.This work will help to determine the specific pathology of neuromuscular alternations at the individual level,thus have important guiding significance for the diagnosis and personalized treatment of patients.