Motor Performance, Mental Workload and Self-Efficacy Dynamics during Learning of Reaching Movements throughout Multiple Practice Sessions

Isabelle M Shuggi; Hyuk Oh; Helena Wu; Maria J Ayoub; Arianna Moreno; Emma P Shaw; Patricia A Shewokis; Rodolphe J Gentili

doi:10.1016/j.neuroscience.2019.07.001

Motor Performance, Mental Workload and Self-Efficacy Dynamics during Learning of Reaching Movements throughout Multiple Practice Sessions

Neuroscience. 2019 Dec 15:423:232-248. doi: 10.1016/j.neuroscience.2019.07.001. Epub 2019 Jul 18.

Authors

Isabelle M Shuggi¹, Hyuk Oh¹, Helena Wu², Maria J Ayoub², Arianna Moreno², Emma P Shaw¹, Patricia A Shewokis³, Rodolphe J Gentili⁴

Affiliations

¹ Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA; Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA.
² Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA.
³ School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA, USA; Nutrition Sciences Department, College of Nursing and Health Professions, Drexel University, Philadelphia, PA, USA.
⁴ Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA; Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA; Maryland Robotics Center, University of Maryland, College Park, MD, USA. Electronic address: rodolphe@umd.edu.

PMID: 31325564
DOI: 10.1016/j.neuroscience.2019.07.001

Abstract

The human capability to learn new motor skills depends on the efficient engagement of cognitive-motor resources, as reflected by mental workload, and psychological mechanisms (e.g., self-efficacy). While numerous investigations have examined the relationship between motor behavior and mental workload or self-efficacy in a performance context, a fairly limited effort focused on the combined examination of these notions during learning. Thus, this study aimed to examine their concomitant dynamics during the learning of a novel reaching skill practiced throughout multiple sessions. Individuals had to learn to control a virtual robotic arm via a human-machine interface by using limited head motion throughout eight practice sessions while motor performance, mental workload, and self-efficacy were assessed. The results revealed that as individuals learned to control the robotic arm, performance improved at the fastest rate, followed by a more gradual reduction of mental workload and finally an increase in self-efficacy. These results suggest that once the performance improved, less cognitive-motor resources were recruited, leading to an attenuated mental workload. Considering that attention is a primary cognitive resource driving mental workload, it is suggested that during early learning, attentional resources are primarily allocated to address task demands and not enough are available to assess self-efficacy. However, as the performance becomes more automatic, a lower level of mental workload is attained driven by decreased recruitment of attentional resources. These available resources allow for a reliable assessment of self-efficacy resulting in a subsequent observable change. These results are also discussed in terms of the application to the training and design of assistive technologies.

Keywords: assistive technologies; human-robot interface; mental workload; reaching movements; self-efficacy; visuomotor learning.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Adolescent
Adult
Female
Healthy Volunteers / psychology*
Humans
Learning / physiology*
Male
Motor Skills / physiology
Movement / physiology*
Practice, Psychological*
Psychomotor Performance / physiology*
Self Efficacy*
User-Computer Interface
Workload / psychology*
Young Adult

Grants and funding

R25 HL092604/HL/NHLBI NIH HHS/United States