An Electromyography-Based Constitutive Law for Force Generation in Skeletal Muscle—Part II: Model Validation on the Ankle Joint Complex

Author:

Knodel Nathan B.1,Calvert L. Brie1,Bywater Emily A.1,Lamia Joseph P.2,Patel Shiv N.2,Nauman Eric A.3

Affiliation:

1. Department of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47906

2. Department of Biomedical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47906

3. Department of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47906; Department of Biomedical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47906; Department of Basic Medical Sciences, Purdue University, 585 Purdue Mall, West Lafayette, IN 47906

Abstract

Abstract Part II of this study evaluates the predictive ability of the skeletal muscle force model derived in Part I within the ankle joint complex. The model is founded in dimensional analysis and uses electromyography and the muscle force–length, force–velocity, and force–frequency curves as inputs. Seventeen subjects (eight males, nine females) performed five different exercises geared toward activating the primary muscles crossing the ankle joint. Motion capture, force plate, and electromyography data were collected during these exercises for use in the analysis. A constant, Km, was calculated for each muscle of each subject using four of the five exercises. The fifth exercise was then used to validate the results by treating the moments due to muscle forces as known and all other components in Euler's second law as unknown. While muscle forces cannot be directly validated in vivo, methods can be developed to test these values with reasonable confidence. This study compared moments about the ankle joint due to the calculated muscle forces to the sum of the moments due to all other sources and the kinematic terms in the second Newton–Euler equation of rigid body motion. Average percent errors for each subject ranged from 4.2% to 15.5% with a total average percent error across all subjects of 8.2%, while maximum percent errors for each subject ranged from 33.3% to 78.0% with an overall average maximum of 52.4%. Future work will examine sensitivity analyses to identify any potential simplifications to the model and solution process, as well as validate the model on a more complex joint system to ensure it still performs at a satisfactory level.

Publisher

ASME International

Subject

Physiology (medical),Biomedical Engineering

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