Recent years have seen increased interest in neuroergonomics, which investigates the brain activities of people engaged in diverse physical and cognitive activities at work and in everyday life. The present work extends upon prior assessments of the state of this art. However, here we narrow our focus specifically to studies that use electroencephalography (EEG) to measure brain activity, correlates, and effects during physical activity. The review uses systematically selected, openly published works derived from a guided search through peer-reviewed journals and conference proceedings. Identified studies were then categorized by the type of physical activity and evaluated considering methodological and chronological aspects via statistical and content-based analyses. From the identified works ( n = 110), a specific number ( n = 38) focused on less mobile muscular activities, while an additional group ( n = 22) featured both physical and cognitive tasks. The remainder ( n = 50) investigated various physical exercises and sporting activities and thus were here identified as a miscellaneous grouping. Most of the physical activities were isometric exertions, moving parts of upper and lower limbs, or walking and cycling. These primary categories were sub-categorized based on movement patterns, the use of the event-related potentials (ERP) technique, the use of recording methods along with EEG and considering mental effects. Further information on subjects' gender, EEG recording devices, data processing, and artifact correction methods and citations was extracted. Due to the heterogeneous nature of the findings from various studies, statistical analyses were not performed. These were thus included in a descriptive fashion. Finally, contemporary research gaps were pointed out, and future research prospects to address those gaps were discussed.
A variety of subjective measures have traditionally been used to assess the perception of physical exertion at work and related body responses. However, the current understanding of physical comfort experienced at work is very limited. The main objective of this study was first to investigate the magnitude of isometric arm forces exerted by females at different levels of physical comfort measured on a new comfort scale and, second, to assess their corresponding neural signatures expressed in terms of power spectral density (PSD). The study assessed PSDs of four major electroencephalography (EEG) frequency bands, focusing on the brain regions controlling motor and perceptual processing. The results showed statistically significant differences in exerted arm forces and the rate of perceived exertion at the various levels of comfort. Significant differences in power spectrum density at different physical comfort levels were found for the beta EEG band. Such knowledge can be useful in incorporating female users’ force requirements in the design of consumer products, including tablets, laptops, and other hand-held information technology devices, as well as various industrial processes and work systems.
The perception of physical exertion is the cognitive sensation of work demands associated with voluntary muscular actions. Measurements of exerted force are crucial for avoiding the risk of overexertion and understanding human physical capability. For this purpose, various physiological measures have been used; however, the state-of-the-art in-force exertion evaluation lacks assessments of underlying neurophysiological signals. The current study applied a graph theoretical approach to investigate the topological changes in the functional brain network induced by predefined force exertion levels for twelve female participants during an isometric arm task and rated their perceived physical comfort levels. The functional connectivity under predefined force exertion levels was assessed using the coherence method for 84 anatomical brain regions of interest at the electroencephalogram (EEG) source level. Then, graph measures were calculated to quantify the network topology for two frequency bands. The results showed that high-level force exertions are associated with brain networks characterized by more significant clustering coefficients (6%), greater modularity (5%), higher global efficiency (9%), and less distance synchronization (25%) under alpha coherence. This study on the neurophysiological basis of physical exertions with various force levels suggests that brain regions communicate and cooperate higher when muscle force exertions increase to meet the demands of physically challenging tasks.
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