title: Getting nowhere fast: trade-off between speed and precision in training to execute image-guided hand-tool movements.
abstract: BACKGROUND
  The speed and precision with which objects are moved by hand or hand-tool interaction under image guidance depend on a specific type of visual and spatial sensorimotor learning. Novices have to learn to optimally control what their hands are doing in a real-world environment while looking at an image representation of the scene on a video monitor. Previous research has shown slower task execution times and lower performance scores under image-guidance compared with situations of direct action viewing. The cognitive processes for overcoming this drawback by training are not yet understood.
  
  
  METHODS
  We investigated the effects of training on the time and precision of direct view versus image guided object positioning on targets of a Real-world Action Field (RAF). Two men and two women had to learn to perform the task as swiftly and as precisely as possible with their dominant hand, using a tool or not and wearing a glove or not. Individuals were trained in sessions of mixed trial blocks with no feed-back.
  
  
  RESULTS
  As predicted, image-guidance produced significantly slower times and lesser precision in all trainees and sessions compared with direct viewing. With training, all trainees get faster in all conditions, but only one of them gets reliably more precise in the image-guided conditions. Speed-accuracy trade-offs in the individual performance data show that the highest precision scores and steepest learning curve, for time and precision, were produced by the slowest starter. Fast starters produced consistently poorer precision scores in all sessions. The fastest starter showed no sign of stable precision learning, even after extended training.
  
  
  CONCLUSIONS
  Performance evolution towards optimal precision is compromised when novices start by going as fast as they can. The findings have direct implications for individual skill monitoring in training programmes for image-guided technology applications with human operators.
authors.affiliation: Laboratoire ICube UMR 7357 CNRS-University of Strasbourg, 2, rue Boussingault, 67000, Strasbourg, France.
authors.forename: Anil Ufuk
authors.initials: AU
authors.lastname: Batmaz
authors.affiliation: Laboratoire ICube UMR 7357 CNRS-University of Strasbourg, 2, rue Boussingault, 67000, Strasbourg, France.
authors.forename: Michel
authors.initials: M
authors.lastname: de Mathelin
authors.affiliation: Laboratoire ICube UMR 7357 CNRS-University of Strasbourg, 2, rue Boussingault, 67000, Strasbourg, France. birgitta.dresp@unistra.fr.
authors.forename: Birgitta
authors.identifier: http://orcid.org/0000-0002-2860-6472
authors.initials: B
authors.lastname: Dresp-Langley
mesh_terms: D000328:Adult; D056228:Feedback, Sensory; D005260:Female; D006801:Humans; D059032:Learning Curve; D008297:Male; D008875:Middle Aged; D009048:Motor Skills; D011214:Practice, Psychological; D011597:Psychomotor Performance; D011930:Reaction Time; D053001:Tool Use Behavior; D014584:User-Computer Interface; D018910:Video Games
keywords: Human operator; Image-guided technology; Precision; Simulator training; Time; Tool-mediated object manipulation