title: A method for a categorized and probabilistic analysis of the surface electromyogram in dynamic contractions.
abstract: The human motor system permits a wide variety of complex movements. Thereby, the inter-individual variability as well as the biomechanical aspects of the performed movement itself contribute to the challenge of the interpretation of sEMG signals in dynamic contractions. A procedure for the systematic analysis of sEMG recordings during dynamic contraction was introduced, which includes categorization of the data in combination with the analysis of frequency distributions of the sEMG with a probabilistic approach. Using the example of elbow flexion and extension the procedure was evaluated with 10 healthy subjects. The recorded sEMG signals of brachioradialis were categorized into a combination of constant and variable movement factors, which originate from the performed movement. Subsequently, for each combination of movement factors cumulative frequency distributions were computed for each subject separately. Finally, the probability of the difference of muscular activation in varying movement conditions was assessed. The probabilistic approach was compared to a deterministic analysis of the same data. Both approaches observed a significant change of muscular activation of brachioradialis during concentric and eccentric contractions exclusively for flexion and extension angles exceeding 30°. However, with the probabilistic approach additional information on the likelihood that the tested effect occurs can be provided. Especially for movements under uncontrollable boundary conditions, this information to assess the confidence of the detected results is of high relevance. Thus, the procedure provides new insights into the quantification and interpretation of muscular activity.
authors.affiliation: Department of Rehabilitation & Prevention Engineering, Institute of Applied Medical Engineering, RWTH Aachen University Aachen, Germany.
authors.forename: Sylvie C F A
authors.initials: SC
authors.lastname: Von Werder
authors.affiliation: Department of Rehabilitation & Prevention Engineering, Institute of Applied Medical Engineering, RWTH Aachen University Aachen, Germany ; German Research School for Simulation Sciences, Joint Graduate School of RWTH Aachen University and Forschungszentrum Jülich Jülich, Germany.
authors.forename: Tim
authors.initials: T
authors.lastname: Kleiber
authors.affiliation: Department of Rehabilitation & Prevention Engineering, Institute of Applied Medical Engineering, RWTH Aachen University Aachen, Germany.
authors.forename: Catherine
authors.initials: C
authors.lastname: Disselhorst-Klug
keywords: categorization; contraction type; dynamic; joint angle; probabilistic; sEMG