Toward modeling locomotion using electromyography‐informed 3D models: application to cerebral palsy. (21st December 2016)

• Record Type: Journal Article
• Authors: Sartori, M.; Fernandez, J. W.; Modenese, L.; Carty, C. P.; Barber, L. A.; Oberhofer, K.; Zhang, J.; Handsfield, G. G.; Stott, N. S.; Besier, T. F.; Farina, D.; Lloyd, D. G.
• Is Part Of: Wiley interdisciplinary reviews. Volume 9:Number 2(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-12-21
• Subjects: Systems biology -- Periodicals; Medicine -- Periodicals; 610
• DOI: 10.1002/wsbm.1368
• Languages: English
• ISSNs: 1939-5094

Abstract

Abstract : This position paper proposes a modeling pipeline to develop clinically relevant neuromusculoskeletal models to understand and treat complex neurological disorders. Although applicable to a variety of neurological conditions, we provide direct pipeline applicative examples in the context of cerebral palsy (CP). This paper highlights technologies in: (1) patient‐specific segmental rigid body models developed from magnetic resonance imaging for use in inverse kinematics and inverse dynamics pipelines; (2) efficient population‐based approaches to derive skeletal models and muscle origins/insertions that are useful for population statistics and consistent creation of continuum models; (3) continuum muscle descriptions to account for complex muscle architecture including spatially varying material properties with muscle wrapping; (4) muscle and tendon properties specific to CP; and (5) neural‐based electromyography‐informed methods for muscle force prediction. This represents a novel modeling pipeline that couples for the first time electromyography extracted features of disrupted neuromuscular behavior with advanced numerical methods for modeling CP‐specific musculoskeletal morphology and function. The translation of such pipeline to the clinical level will provide a new class of biomarkers that objectively describe the neuromusculoskeletal determinants of pathological locomotion and complement current clinical assessment techniques, which often rely on subjective judgment. WIREs Syst Biol Med 2017, 9:e1368. doi: 10.1002/wsbm.1368 This article is categorized under: Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Abstract : Modeling pipeline from neural function to rigid body mechanics, continuum muscle and model prediction.