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An open-source toolbox for enhancing the assessment of muscle activation patterns during cyclical movements

Gregorio Dotti, Marco Ghislieri, Cristina Castagneri, Valentina Agostini, Marco Knaflitz, Gabriella Balestra, Samanta Rosati

Year
2024
Citations
2

Abstract

Abstract Objective. The accurate temporal analysis of muscle activations is of great importance in several research areas spanning from the assessment of altered muscle activation patterns in orthopaedic and neurological patients to the monitoring of their motor rehabilitation. Several studies have highlighted the challenge of understanding and interpreting muscle activation patterns due to the high cycle-by-cycle variability of the sEMG data. This makes it difficult to interpret results and to use sEMG signals in clinical practice. To overcome this limitation, this study aims at presenting a toolbox to help scientists easily characterize and assess muscle activation patterns during cyclical movements. Approach. <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:mtext>CIMAP</mml:mtext> </mml:mrow> </mml:mrow> </mml:math> (Clustering for the Identification of Muscle Activation Patterns) is an open-source Python toolbox based on agglomerative hierarchical clustering that aims at characterizing muscle activation patterns during cyclical movements by grouping movement cycles showing similar muscle activity. Main results. From muscle activation intervals to the graphical representation of the agglomerative hierarchical clustering dendrograms, the proposed toolbox offers a complete analysis framework for enabling the assessment of muscle activation patterns. The toolbox can be flexibly modified to comply with the necessities of the scientist. <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:mtext>CIMAP</mml:mtext> </mml:mrow> </mml:mrow> </mml:math> is addressed to scientists of any programming skill level working in different research areas such as biomedical engineering, robotics, sports, clinics, biomechanics, and neuroscience. CIMAP is freely available on GitHub ( https://github.com/Biolab-PoliTO/CIMAP ). Significance. <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:mtext>CIMAP</mml:mtext> </mml:mrow> </mml:mrow> </mml:math> toolbox offers scientists a standardized method for analyzing muscle activation patterns during cyclical movements.

Keywords

ToolboxComputer sciencePython (programming language)Cluster analysisHierarchical clusteringElectromyographyArtificial intelligenceMovement (music)Human–computer interactionMachine learning

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