An electromyography-assisted biomechanical cervical spine model: Model development and validation. (December 2020)

• Record Type: Journal Article
• Authors: Alizadeh, Mina; Aurand, Alexander; Knapik, Gregory G.; Dufour, Jonathan S.; Mendel, Ehud; Bourekas, Eric; Marras, William S.
• Is Part Of: Clinical biomechanics. Volume 80(2020)
• Publication Date: 2020-12
• Subjects: Computational model -- Neck model -- Multi-body dynamics -- Curved muscle model -- Occupational neck injury; Biomechanics -- Periodicals; Osteopathic medicine -- Periodicals; Biomechanics -- Periodicals; Osteopathic Medicine -- Periodicals; 612.76
• DOI: 10.1016/j.clinbiomech.2020.105169
• Languages: English
• ISSNs: 0268-0033

Abstract

Abstract: Background: In spite of the prevalence of occupational neck disorders as a result of work force fluctuating from industry to sedentary office work, most cervical spine computational models are not capable of simulating occupational and daily living activities whereas majority of cervical spine models specialized to simulate crash and impact scenarios. Therefore, estimating spine tissue loads accurately to quantify the risk of neck disorders in occupational environments within those models is not possible due to the lack of muscle models, dynamic simulation and passive spine structures. Methods: In this effort the structure, logic, and validation process of an electromyography-assisted cervical biomechanical model that is capable of estimating neck loading under three-dimensional complex motions is described. The developed model was designed to simulate complex dynamic motions similar to work place exposure. Curved muscle geometry, personalized muscle force parameters, and separate passive and (electromyography-driven) active muscle force components are implemented in this model. Findings: Calibration algorithms were able to reverse-engineer personalized muscle properties to calculate active and passive muscle forces of each individual. Interpretation: This electromyography-assisted cervical spine model with curved muscle model is capable to accurately predict spinal tissue loads during isometric and dynamic head and neck activities. Personalized active and passive muscle force algorithms will help to more robustly investigate person-specific muscle forces and spinal tissue loads. Highlights: Biomechanical models had developed to address work related cervical spine injury. Previous models are insufficient due to lack of accurate muscle force estimation. In this study an electromyography-assisted cervical spine model was developed. The model performance during isometric and dynamic exertions has been examined. The model estimated 3D spinal loads well as a function of various neck motions.