load sharing

Submaximal Normalizing Methods to Evaluate Load Sharing Changes in Repetitive Upper Extremity Work

The relationship between EMG and muscle force changes with muscle fatigue, making interpretation of load sharing between muscles over time challenging. The purpose of this investigation was to evaluate the efficacy of normalizing EMG data to repeated, static, submaximal exertions to mitigate the fatigue artifact in EMG amplitude. Participants completed simulated repetitive work tasks, in 60-second work cycles, until exhaustion and surface EMG was recorded from 11 muscles. Every 12 minutes, participants completed a series of 4 submaximal reference exertions. Reference exertion EMG data were used in 6 normalizing methods including 1 standard (normalized to initial reference exertion) and 5 novel methods: (i) Fatigue Only, (ii) Linear Model, (iii) Cubic Model, (iv) Points Forward, and (v) Points Forward/Backward. EMG data were normalized to each novel methods and results were compared to the Standard Method. The significant differences between the novel methods and the Standard Method were dependent on the muscle and the number of time points in the analysis. Correlation analysis showed that the predicted cubic model points correlated better to the actual data points than the linear predicted values. This novel method to create “fatigue debiased” ratios may better reflect the changing muscular loads during repetitive work. This method was evaluated with a novel data set examining the effects of repetitive shoulder exertions, in multiple axes, on load sharing in the shoulder over time. The normalizing method was effective at distinguishing between the effects of fatigue artifact on EMG amplitude and load sharing between muscles over time.
Listed In: Biomechanics