Azin Zargham1, Maarten Afschrift2, Joris De Schutter3, Ilse Jonkers4, Friedl De Groote5. 1. Department of Movement Sciences, KU Leuven, Leuven, Belgium. Electronic address: azin.zargham@kuleuven.be. 2. Department of Movement Sciences, KU Leuven, Leuven, Belgium. Electronic address: maarten.afschrift@kuleuven.be. 3. Department of Mechanical Engineering, KU Leuven, Robotics Core Lab of Flanders Make, Belgium. Electronic address: joris.deschutter@kuleuven.be. 4. Department of Movement Sciences, KU Leuven, Leuven, Belgium. Electronic address: ilse.jonkers@kuleuven.be. 5. Department of Movement Sciences, KU Leuven, Leuven, Belgium. Electronic address: friedl.degroote@kuleuven.be.
Abstract
BACKGROUND: Assessment of contact forces is essential for a better understanding of mechanical factors affecting progression of osteoarthritis. Since contact forces cannot be measured non-invasively, computer simulations are often used to assess joint loading. Contact forces are to a large extent determined by muscle forces. These muscle forces are computed using optimization techniques that solve the muscle redundancy problem by assuming that muscles are coordinated in a way that optimizes performance (e.g., minimizes muscle activity or metabolic energy). However, it is unclear which of the many proposed performance criteria best describes muscle coordination. RESEARCH QUESTION: Which performance criterion best describes muscle recruitment patterns and knee contact forces recorded using electromyography (EMG) and load cell instrumented prostheses?. METHODS: We solved the muscle redundancy problem based on six different groups of performance criteria: muscle activations, volume-scaled activations, forces, stresses, metabolic energy, and joint contact forces. Computed muscle excitations and knee contact forces during over-ground walking were validated against recorded EMG signals and measured contact forces for four subjects with instrumented knee prostheses in the "Grand Challenge Competition to Predict in Vivo Knee Loads" dataset. RESULTS: Performance criteria based on either stress or muscle activation (either unscaled or scaled by muscle volume), both to a power of 3 or 4, resulted in the best agreement between measured and simulated values. These performance criteria outperformed all other criteria in terms of agreement between simulated muscle excitations and EMG, whereas good agreement between measured and predicted contact forces was also observed for minimization of contact forces and metabolic energy. SIGNIFICANCE: Given the large differences in accuracy obtained with different performance criteria (e.g., root mean square errors of contact forces differed up to 0.45 body weight), the results of our study are important to improve the validity of in silico assessment of joint loading.
BACKGROUND: Assessment of contact forces is essential for a better understanding of mechanical factors affecting progression of osteoarthritis. Since contact forces cannot be measured non-invasively, computer simulations are often used to assess joint loading. Contact forces are to a large extent determined by muscle forces. These muscle forces are computed using optimization techniques that solve the muscle redundancy problem by assuming that muscles are coordinated in a way that optimizes performance (e.g., minimizes muscle activity or metabolic energy). However, it is unclear which of the many proposed performance criteria best describes muscle coordination. RESEARCH QUESTION: Which performance criterion best describes muscle recruitment patterns and knee contact forces recorded using electromyography (EMG) and load cell instrumented prostheses?. METHODS: We solved the muscle redundancy problem based on six different groups of performance criteria: muscle activations, volume-scaled activations, forces, stresses, metabolic energy, and joint contact forces. Computed muscle excitations and knee contact forces during over-ground walking were validated against recorded EMG signals and measured contact forces for four subjects with instrumented knee prostheses in the "Grand Challenge Competition to Predict in Vivo Knee Loads" dataset. RESULTS: Performance criteria based on either stress or muscle activation (either unscaled or scaled by muscle volume), both to a power of 3 or 4, resulted in the best agreement between measured and simulated values. These performance criteria outperformed all other criteria in terms of agreement between simulated muscle excitations and EMG, whereas good agreement between measured and predicted contact forces was also observed for minimization of contact forces and metabolic energy. SIGNIFICANCE: Given the large differences in accuracy obtained with different performance criteria (e.g., root mean square errors of contact forces differed up to 0.45 body weight), the results of our study are important to improve the validity of in silico assessment of joint loading.
Authors: Peter J Bishop; Krijn B Michel; Antoine Falisse; Andrew R Cuff; Vivian R Allen; Friedl De Groote; John R Hutchinson Journal: PLoS Comput Biol Date: 2021-04-01 Impact factor: 4.475
Authors: Arne De Brabandere; Jill Emmerzaal; Annick Timmermans; Ilse Jonkers; Benedicte Vanwanseele; Jesse Davis Journal: Front Bioeng Biotechnol Date: 2020-04-15