Abstract
Current methods for evaluating fatigue separately assess intramuscular changes in individual muscles from corresponding alterations in movement output. The purpose of this study is to investigate if a system-based monitoring paradigm, which quantifies how the dynamic relationship between the activity from multiple muscles and force changes over time, produces a viable metric for assessing fatigue. Improvements made to the paradigm to facilitate online fatigue assessment are also discussed. Eight participants performed a static elbow extension task until exhaustion, while surface electromyography (sEMG) and force data were recorded. A dynamic time-series model mapped instantaneous features extracted from sEMG signals of multiple synergistic muscles to extension force. A metric, called the Freshness Similarity Index (FSI), was calculated using statistical analysis of modeling errors to reveal time-dependent changes in the dynamic model indicative of performance degradation. The FSI revealed strong, significant within-individual associations with two well-accepted measures of fatigue, maximum voluntary contraction (MVC) force () and ratings of perceived exertion (RPE) (), substantiating the viability of a system-based monitoring paradigm for assessing fatigue. These findings provide the first direct and quantitative link between a system-based performance degradation metric and traditional measures of fatigue.
Highlights
During the second half of the endurance task, all muscles showed a steady increase in ai (t) and decrease in f im (t), with the long and lateral heads of the triceps brachii showing the greatest mean changes. These results show that the endurance task, whose target force was only 30% maximum voluntary contraction (MVC), started as a low effort task but progressed to a moderate-to-high effort task that required increased recruitment of all muscles
We verified that participants developed fatigue during the endurance task by observing significant reductions in MVC force and increases in Ratings of perceived exertion (RPE)
This paper presented and validated a framework for continuously assessing fatigue using a system-based monitoring paradigm
Summary
Neuromuscular fatigue presents a major obstacle for achieving desired performance in a variety of circumstances. For healthy individuals in physically demanding professions (e.g., astronauts, soldiers, athletes, etc.), prolonged periods of training and operations are known to adversely affect task efficiency [4], movement accuracy [5], and performance [4], while increasing susceptibility to overuse injuries [4]. For patients with neurological or cerebrovascular diseases, such as stroke, multiple sclerosis, and Parkinson’s disease, fatigue is a typical and potentially debilitating symptom [6,7]. Assessing fatigue has important implications for preventing neuromuscular injury [8], optimizing training loads [9], and guiding effective, individualized treatment strategies for rehabilitation [7]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
