The impact of anatomical uncertainties on the predictions of a musculoskeletal hand model – a sensitivity study. Issue 2 (3rd February 2022)

• Record Type: Journal Article
• Authors: Melzner, Maximilian; Süß, Franz; Dendorfer, Sebastian
• Is Part Of: Computer methods in biomechanics and biomedical engineering. Volume 25:Issue 2(2022)
• Page Start: 156
• Page End: 164
• Publication Date: 2022-02-03
• Subjects: Musculoskeletal -- hand -- AnyBody -- Latin hypercube sampling -- sensitivity analysis; Biomechanics -- Data processing -- Periodicals; Biomedical engineering -- Periodicals; Biomechanics -- Periodicals; Biomedical Engineering -- methods -- Periodicals; Computing Methodologies -- Periodicals; 612.7
• DOI: 10.1080/10255842.2021.1940974
• Languages: English
• ISSNs: 1025-5842

Abstract

Abstract: Outputs of musculoskeletal models should be considered probabilistic rather than deterministic as they are affected by inaccuracies and estimations associated with the development of the model. One of these uncertainties being critical for modeling arises from the determination of the muscles' line of action and the physiological cross-sectional area. Therefore, the aim of this study was to evaluate the outcome sensitivity of model predictions from a musculoskeletal hand model in comparison to the uncertainty of these input parameters. For this purpose, the kinematics and muscle activities of different hand movements (abduction of the fingers, abduction of the thumb, and flexion of the thumb) were recorded. One thousand simulations were calculated for each movement using the Latin hypercube sampling method with a corresponding variation of the muscle origin/insertion points and the cross-sectional area. Comparing the standard hand to simulations incorporating uncertainties of input parameters shows no major deviations in on- and off-set time point of muscle activities. About 60% of simulations are located within a ± 30% interval around the standard model concerning joint reaction forces. The comparison with the variation of the input data leads to the conclusion that the standard hand model is able to provide not over-scattered outcomes and, therefore, can be considered relatively stable. These results are of practical importance to the personalization of a musculoskeletal model with subject-specific bone geometries and hence changed muscle line of action.