Date of Award

2013

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Systems Engineering

First Advisor

Jiang, Dr. Zongliang

Abstract

Musculoskeletal disorders (MSDs) constitute one of the most important occupational health issues in healthcare workers who are susceptible to upper extremity disorders. Yet MSDs in the healthcare professions have not been studied extensively beyond the lower back. The focus population for this research is the field of dentistry where neck and shoulder disorders have been documented to have a high prevalence. Though quantitative data has been collected, many prior studies have focused on self-reported information. The goal of this research is to provide insight into the inter-relationship of muscles in the upper extremities. One way to accomplish this is to understand the muscle coactivation patterns in the neck and shoulders. A comprehensive profile of eleven superficial muscles is developed using electromyography (EMG): two in the neck (the sternocleidomastoid and upper trapezius), five that cross the shoulder joint (latissimus dorsi, infraspinatus, supraspinatus, anterior, lateral, and posterior deltoid, the pectoralis major), and two that stabilize the shoulder joint (triceps and biceps); providing objective and quantitative data. Multivariate multiple regression, correlation, the muscle coactivation indicator (MCI), and stochastic modeling, using conditional histograms, are used to better understand muscle coactivation patterns and muscle responses to independent variables. While the MCI showed relative coactivation level and correlation disclosed a dependency among dependent variables, regression was inconsistent in predicting muscle activity. Conditional histograms provided a means of coactivation assessment. Data gathered and knowledge gained is essential for the development of interventions to minimize MSDs and to understand muscle coactivation patterns in workers who maintain static postures.

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