Morley, J. | Search bioRxiv

bioRxiv2021

Unravelling the Physiological Correlates of Mental Workload Variations in Tracking and Collision Prediction Tasks: Implications for Air Traffic Controllers

ObjectiveWe have designed tracking and collision prediction tasks to elucidate the differences in the physiological response to the workload variations in basic ATC tasks to untangle the impact of workload variations experienced by operators working in a complex ATC environment. BackgroundEven though several factors influence the complexity of ATC tasks, keeping track of the aircraft and preventing collision are the most crucial. MethodsPhysiological measures, such as electroencephalogram (EEG), eye activity, and heart rate variability (HRV) data, were recorded from 24 participants performing tracking and collision prediction tasks with three levels of difficulty. ResultsThe neurometrics of workload variations in the tracking and collision prediction tasks were markedly distinct, indicating that neurometrics can provide insights on the type of mental workload. The pupil size, number of blinks and HRV metric, root mean square of successive difference (RMSSD), varied significantly with the mental workload in both these tasks in a similar manner. ConclusionOur findings indicate that variations in task load are sensitively reflected in physiological signals, such as EEG, eye activity and HRV, in these basic ATC-related tasks. ApplicationThese findings have applicability to the design of future mental workload adaptive systems that integrate neurometrics in deciding not just when but also what to adapt. Our study provides compelling evidence in the viability of developing intelligent closed-loop mental workload adaptive systems that ensure efficiency and safety in ATC and beyond. PrecisThis article identifies the physiological correlates of mental workload variation in basic ATC tasks. The findings assert that neurometrics can provide more information on the task that contributes to the workload, which can aid in the design of intelligent mental workload adaptive system.

neuroscience↗

bioRxiv2020

Characterizing the body morphology of the first metacarpal in the Homininae using 3D geometric morphometrics

ObjectivesThe morphological characteristics of the thumb are of particular interest due to its fundamental role in enhanced manipulation. Despite its possible importance regarding this issue, the body of the first metacarcapal (MC1) has not been fully characterized using morphometrics. This could provide further insights into its anatomy, as well as its relationship with manipulative capabilities. Hence, this study quantifies the shape of the MC1s body in the extant Homininae and some fossil hominins to provide a better characterization of its morphology. Materials and methodsThe sample includes MC1s of modern humans (n=42), gorillas (n=27) and chimpanzees (n=30), as well as Homo neanderthalensis, Homo naledi and Australopithecus sediba. 3D geometric morphometrics were used to quantify the shape of MC1s body. ResultsThe results show a clear distinction among the three extant genera. H. neanderthalensis mostly falls within the modern human range of variation. H. naledi varies slightly from modern humans, although also showing some unique trait combination, whereas A. sediba varies to an even greater extent. When classified using a discriminant analysis, the three fossils are categorized within the Homo group. Conclusion: The modern human MC1 is characterized by a distinct suite of traits, not present to the same extent in the great apes, that are consistent with an ability to use forceful precision grip. This morphology was also found to align very closely with that of H. neanderthalensis. H. naledi shows a number of human-like adaptations, whilst A. sediba presents a mix of both derived and more primitive traits.

paleontology↗