EMG-Based Validation of Musculoskeletal Models Considering Crosstalk

BACKGROUND: Validation and verification of multibody musculoskeletal models sEMG is a difficult process because of the reliability of sEMG data and the complex relationship of muscle force and sEMG. OBJECTIVE: This work aims at comparing experimentally recorded and simulated muscle activities considering a numerical model for crosstalk. METHODS: For providing an experimentally derived reference data set, subjects were performing elevations of the arm, where the activities of the contemplated muscle groups were measured by sEMG sensors. Computed muscle activities were further processed and transformed into an artificial electromyographical signal, which includes a numerical crosstalk model. In order to determine whether the crosstalk model provides a better agreement with the measured muscle activities, the Pearson correlation coefficient has been computed as a qualitative way of assessing the curve progression of the data sets. RESULTS: The results show an improvement in the correlation coefficient between the experimental data and the simulated muscle activities when taking crosstalk into account. CONCLUSIONS: Although the correlation coefficient increased when the crosstalk model was utilized, it is questionable if the discretization of both, the crosstalk and the musculoskeletal model, is accurate enough.

[1]  J. G. Dijk,et al.  A convenient method to reduce crosstalk in surface EMG , 2001, Clinical Neurophysiology.

[2]  Leonard E. Schwer,et al.  Validation metrics for response histories: perspectives and case studies , 2007, Engineering with Computers.

[3]  John Rasmussen,et al.  On validation of multibody musculoskeletal models , 2012, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[4]  Jaap H van Dieën,et al.  Methodological aspects of SEMG recordings for force estimation--a tutorial and review. , 2010, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[5]  O. A. Nikitin,et al.  Neither high-pass filtering nor mathematical differentiation of the EMG signals can considerably reduce cross-talk. , 2002, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[6]  C. D. De Luca,et al.  Surface myoelectric signal cross-talk among muscles of the leg. , 1988, Electroencephalography and clinical neurophysiology.

[7]  Michael A. Sprague,et al.  Spectral elements and field separation for an acoustic fluid subject to cavitation , 2003 .

[8]  L. Jones,et al.  Movement of the shoulder complex: the development of a measurement technique based on proposed ISB standards , 2006 .

[9]  J. A. Soules Precise calculation of the electrostatic force between charged spheres including induction effects , 1990 .

[10]  D. Winter,et al.  Crosstalk in surface electromyography: Theoretical and practical estimates. , 1994, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.