The brain networks indices associated with the human perception of comfort in static force exertion tasks.

Introduction: The perception of physical comfort is one of the important workplace design parameters. Most comfort perception studies have mainly relied on subjective assessments and biomechanical techniques, with limited exploration of neural brain activity.

Methodology: The current study investigates this research gap by integrating the rating of perceiving physical comfort (RPPC) with brain network indices in an arm flexion task across different force levels. The applied arm forces, EEG-based neural responses, and the RPPC were measured, and the corresponding network theory indices were calculated. The following correlations were evaluated: (a) RPPC and applied forces, (b) network theory indices and applied forces, and (c) RPPC and network theory indices.

Results and discussion: Results for (a) revealed a significant negative correlation between RPPC and the applied force for the arm flexion task. This shows that as the exerted force difficulty increases to an extremely hard level, the perception of physical comfort decreases till it reaches no comfort level. Results for (b) showed a positive correlation between the applied forces and global efficiency for the alpha network coherence during an extremely hard task. In contrast, a negative correlation was found between applied forces and path length for beta coherence during a light task. Findings from (b) suggest that the brain is more efficient in transmitting information related to cognitive functioning during a highly demanding force exertion task than a light task. Results from (c) showed a negative correlation between RPPC and global efficiency for alpha coherence during an extremely hard force exertion task. Moreover, a positive correlation was observed between RPPC and local efficiency for beta coherence during a somewhat hard task. Findings from (c) also indicate that perceiving a low-comfort physical task might increase task alertness, with the corresponding neural network exhibiting a high level of internal brain organization.

Conclusions: The study results contribute valuable knowledge toward understanding the neural responses underlying the perception of physical comfort levels.