Analogous adaptations in speed, impulse and endpoint stiffness when learning a real and virtual insertion task with haptic feedback - CEA - Commissariat à l’énergie atomique et aux énergies alternatives Accéder directement au contenu
Article Dans Une Revue Scientific Reports Année : 2020

Analogous adaptations in speed, impulse and endpoint stiffness when learning a real and virtual insertion task with haptic feedback

Résumé

Abstract Humans have the ability to use a diverse range of handheld tools. Owing to its versatility, a virtual environment with haptic feedback of the force is ideally suited to investigating motor learning during tool use. However, few simulators exist to recreate the dynamic interactions during real tool use, and no study has compared the correlates of motor learning between a real and virtual tooling task. To this end, we compared two groups of participants who either learned to insert a real or virtual tool into a fixture. The trial duration, the movement speed, the force impulse after insertion and the endpoint stiffness magnitude decreased as a function of trials, but they changed at comparable rates in both environments. A ballistic insertion strategy observed in both environments suggests some interdependence when controlling motion and controlling interaction, contradicting a prominent theory of these two control modalities being independent of one another. Our results suggest that the brain learns real and virtual insertion in a comparable manner, thereby supporting the use of a virtual tooling task with haptic feedback to investigate motor learning during tool use.
Fichier principal
Vignette du fichier
Analogous_adaptations_in_speed_impulse_and_endpoin.pdf (2.09 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Licence : CC BY - Paternité

Dates et versions

cea-04570368 , version 1 (07-05-2024)

Licence

Paternité

Identifiants

Citer

Atsushi Takagi, Giovanni de Magistris, Geyun Xiong, Alain Micaelli, Hiroyuki Kambara, et al.. Analogous adaptations in speed, impulse and endpoint stiffness when learning a real and virtual insertion task with haptic feedback. Scientific Reports, 2020, 10 (1), pp.22342. ⟨10.1038/s41598-020-79433-5⟩. ⟨cea-04570368⟩
0 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More