EMGTools, an Adaptive and Versatile Tool for Detailed EMG Analysis

Abstract

We have developed an electromyography (EMG) decomposition system called EMGTools that can extract the constituent MUAPs and firing patterns (FPs) for quantitative analysis from the EMG signal recorded at slight effort for clinical evaluation. The aim was to implement a robust system able to handle the challenges and variations in clinically recorded signals. The system extracts MUAPs recorded by concentric needle electrodes and resolves superimposed MUAPs to produce FPs. Thus, critical fixed thresholds/parameters are avoided and replaced with adaptive solutions. The decomposition algorithm consists of three stages: segmentation, clustering, and resolution of compound segments. The results are validated using three different methods, comparing mean MUAP duration with previous methods, comparing dual channel recordings, and assessing the residual signal after decomposition. The advantages and limitations of the system are discussed.