title: Virtual exertions: evoking the sense of exerting forces in virtual reality using gestures and muscle activity.
abstract: OBJECTIVE
  This study was a proof of concept for virtual exertions, a novel method that involves the use of body tracking and electromyography for grasping and moving projections of objects in virtual reality (VR). The user views objects in his or her hands during rehearsed co-contractions of the same agonist-antagonist muscles normally used for the desired activities to suggest exerting forces.
  
  
  BACKGROUND
  Unlike physical objects, virtual objects are images and lack mass. There is currently no practical physically demanding way to interact with virtual objects to simulate strenuous activities.
  
  
  METHODS
  Eleven participants grasped and lifted similar physical and virtual objects of various weights in an immersive 3-D Cave Automatic Virtual Environment. Muscle activity, localized muscle fatigue, ratings of perceived exertions, and NASA Task Load Index were measured. Additionally, the relationship between levels of immersion (2-D vs. 3-D) was studied.
  
  
  RESULTS
  Although the overall magnitude of biceps activity and workload were greater in VR, muscle activity trends and fatigue patterns for varying weights within VR and physical conditions were the same. Perceived exertions for varying weights were not significantly different between VR and physical conditions.
  
  
  CONCLUSIONS
  Perceived exertion levels and muscle activity patterns corresponded to the assigned virtual loads, which supported the hypothesis that the method evoked the perception of physical exertions and showed that the method was promising.
  
  
  CONCLUSIONS
  Ultimately this approach may offer opportunities for research and training individuals to perform strenuous activities under potentially safer conditions that mimic situations while seeing their own body and hands relative to the scene.
authors.affiliation: University of Wisconsin-Madison.
authors.forename: Karen B
authors.initials: KB
authors.lastname: Chen
authors.affiliation: University of Wisconsin-Madison.
authors.forename: Kevin
authors.initials: K
authors.lastname: Ponto
authors.affiliation: University of Wisconsin-Madison.
authors.forename: Ross D
authors.initials: RD
authors.lastname: Tredinnick
authors.affiliation: University of Wisconsin-Madison radwin@discovery.wisc.edu.
authors.forename: Robert G
authors.initials: RG
authors.lastname: Radwin
mesh_terms: D000328:Adult; D004576:Electromyography; D005260:Female; D005868:Gestures; D018737:Hand Strength / Q000502:physiology; D006801:Humans; D017770:Lifting; D008297:Male; D018763:Muscle Fatigue / Q000502:physiology; D018482:Muscle, Skeletal / Q000502:physiology*; D005082:Physical Exertion / Q000502:physiology*; D013647:Task Performance and Analysis; D014584:User-Computer Interface; D055815:Young Adult
keywords: computer interface; electromyography (EMG); forces and moments; simulation and virtual reality; virtual environments