Literature DB >> 29214390

Changes in motor performance and mental workload during practice of reaching movements: a team dynamics perspective.

Isabelle M Shuggi1,2,3, Patricia A Shewokis4,5, Jeffrey W Herrmann6,7, Rodolphe J Gentili8,9,10.   

Abstract

Few investigations have examined mental workload during motor practice or learning in a context of team dynamics. This study examines the underlying cognitive-motor processes of motor practice by assessing the changes in motor performance and mental workload during practice of reaching movements. Individuals moved a robotic arm to reach targets as fast and as straight as possible while satisfying the task requirement of avoiding a collision between the end-effector and the workspace limits. Individuals practiced the task either alone (HA group) or with a synthetic teammate (HRT group), which regulated the effector velocity to help satisfy the task requirements. The findings revealed that the performance of both groups improved similarly throughout practice. However, when compared to the individuals of the HA group, those in the HRT group (1) had a lower risk of collisions, (2) exhibited higher performance consistency, and (3) revealed a higher level of mental workload while generally perceiving the robotic teammate as interfering with their performance. As the synthetic teammate changed the effector velocity in specific regions near the workspace boundaries, individuals may have been constrained to learn a piecewise visuomotor map. This piecewise map made the task more challenging, which increased mental workload and perception of the synthetic teammate as a burden. The examination of both motor performance and mental workload revealed a combination of both adaptive and maladaptive team dynamics. This work is a first step to examine the human cognitive-motor processes underlying motor practice in a context of team dynamics and contributes to inform human-robot applications.

Entities:  

Keywords:  Assistive technologies; Human–robot interactions; Mental workload; Reaching movements; Team dynamics; Visuomotor practice

Mesh:

Year:  2017        PMID: 29214390     DOI: 10.1007/s00221-017-5136-8

Source DB:  PubMed          Journal:  Exp Brain Res        ISSN: 0014-4819            Impact factor:   1.972


  74 in total

1.  Physical and observational practice afford unique learning opportunities.

Authors:  C H Shea; D L Wright; G Wulf; C Whitacre
Journal:  J Mot Behav       Date:  2000-03       Impact factor: 1.328

2.  Fitts' Law in two dimensions with hand and head movements.

Authors:  R J Jagacinski; D L Monk
Journal:  J Mot Behav       Date:  1985-03       Impact factor: 1.328

3.  Measurement of functional task difficulty during motor learning: What level of difficulty corresponds to the optimal challenge point?

Authors:  Kazunori Akizuki; Yukari Ohashi
Journal:  Hum Mov Sci       Date:  2015-08-04       Impact factor: 2.161

4.  Attractor and Lyapunov models for reach and grasp movements with application to robot-assisted therapy.

Authors:  Stephen J Guastello; Dominic E Nathan; Michelle J Johnson
Journal:  Nonlinear Dynamics Psychol Life Sci       Date:  2009-01

5.  A novel approach to the physiological measurement of mental workload.

Authors:  Matthew W Miller; Jeremy C Rietschel; Craig G McDonald; Bradley D Hatfield
Journal:  Int J Psychophysiol       Date:  2011-02-20       Impact factor: 2.997

6.  A method for evaluating head-controlled computer input devices using Fitts' law.

Authors:  R G Radwin; G C Vanderheiden; M L Lin
Journal:  Hum Factors       Date:  1990-08       Impact factor: 2.888

7.  Evolution of cerebral cortico-cortical communication during visuomotor adaptation to a cognitive-motor executive challenge.

Authors:  Rodolphe J Gentili; Trent J Bradberry; Hyuk Oh; Michelle E Costanzo; Scott E Kerick; José L Contreras-Vidal; Bradley D Hatfield
Journal:  Biol Psychol       Date:  2014-12-18       Impact factor: 3.251

8.  Measuring workload in collaborative contexts: trait versus state perspectives.

Authors:  William S Helton; Gregory J Funke; Benjamin A Knott
Journal:  Hum Factors       Date:  2014-03       Impact factor: 2.888

9.  Training with an upper-limb prosthetic simulator to enhance transfer of skill across limbs.

Authors:  Douglas L Weeks; Stephen A Wallace; David I Anderson
Journal:  Arch Phys Med Rehabil       Date:  2003-03       Impact factor: 3.966

10.  Too much of a good thing: random practice scheduling and self-control of feedback lead to unique but not additive learning benefits.

Authors:  Asif Ali; Bradley Fawver; Jingu Kim; Jeffrey Fairbrother; Christopher M Janelle
Journal:  Front Psychol       Date:  2012-12-10
View more
  2 in total

Review 1.  A tale of too many tasks: task fragmentation in motor learning and a call for model task paradigms.

Authors:  Rajiv Ranganathan; Aimee D Tomlinson; Rakshith Lokesh; Tzu-Hsiang Lin; Priya Patel
Journal:  Exp Brain Res       Date:  2020-11-10       Impact factor: 1.972

2.  Biomechanical and neurocognitive performance outcomes of walking with transtibial limb loss while challenged by a concurrent task.

Authors:  Alison L Pruziner; Emma P Shaw; Jeremy C Rietschel; Brad D Hendershot; Matthew W Miller; Erik J Wolf; Bradley D Hatfield; Christopher L Dearth; Rodolphe J Gentili
Journal:  Exp Brain Res       Date:  2018-11-20       Impact factor: 1.972

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.