Complex network properties analysis of upper trunk muscle fatigue in firefighters carrying self-contained breathing apparatus

Abstract

Muscle fatigue is a significant risk factor for injuries among firefighters in the workplace, particularly when wearing self-contained breathing apparatus (SCBA) for prolonged periods. However, the mechanisms of muscle function in both non-fatigue and post-fatigue states remain unclear. The purpose of this article is to assess the effect of SCBA on muscle fatigue and compensation in firefighters using surface electromyography (sEMG) from the upper trunk muscles. Thirty volunteer firefighters were recruited to perform a running task on a treadmill, and sEMG signals were recorded from the upper trunk muscles during the initial and final phases of the task. Then, the coherence features of the beta segment (14–30 Hz) were extracted to construct the muscle functional network. Finally, differences in muscle function between the two fatigue states were assessed quantitatively by extracting muscle network parameters. The results showed that fatigue increases the functional connectivity and coupling strength between muscles during firefighters’ running with the SCBA. Compared to the non-fatigued state, muscle functional network parameters—such as clustering coefficients, global efficiencies, and small-world properties—were significantly reduced in the post-fatigued state, with decreases of approximately 36.3 %, 14.63 %, and 43.44 %, respectively. Meanwhile, the main active muscles shifted from the waist to the abdominal muscles. These findings provide a scientific basis for the development of training programmes for specific muscle groups and the optimal design of SCBA.