Mechanism of Integrating Force and Vibrotactile Cues for 3D User Interaction within Virtual Environments

Proper integration of sensory cues facilitates 3D user interaction within virtual environments (VEs). Studies showed that the integration of visual and haptic cues follows maximum likelihood estimation (MLE). Little effort focuses however on the mechanism of integrating force and vibrotactile cues. We thus investigated MLE's suitability for integrating these cues. Within a VE, human users undertook 3D interaction of navigating a flying drone along a high-voltage transmission line for inspection. The users received individual force or vibrotactile cues, and their combinations in collocated and dislocated settings. The users' task performance including completion time and accuracy was assessed under each individual cue and setting. The presence of the vibrotactile cue promoted a better performance than the force cue alone. This agreed with the applicability of tactile cues for sensing 3D surfaces, herein setting a baseline for using MLE. The task performance under the collocated setting indicated a degree of combining the individual cues. In contrast, the performance under the dislocated setting was alike under the individual vibrotactile cue. These observations imply a possible role of MLE in integrating force and vibrotactile cues for 3D user interaction within VEs

Learning force patterns with a multimodal system using contextual cues

Previous studies on learning force patterns (fine motor skills) have focused on providing “punctual information”, which means users only receive information about their performance at the current time step. This work proposes a new approach based on “contextual information”, in which users receive information not only about the current time step, but also about the past (how the target force has changed over time) and the future (how the target force will change). A test was run to compare the performance of the contextual approach in relation to the punctual information, in which each participant had to memorize and then reproduce a pattern of force after training with a multimodal system. The findings suggest that the contextual approach is a useful strategy for force pattern learning. The advantage of the contextual information approach over the punctual information approach is that users receive information about the evolution of their performance (helping to correct the errors), and they also receive information about the next forces to be exerted (providing them with a better understanding of the target force profile). Finally, the contextual approach could be implemented in medical training platforms or surgical robots to extend the capabilities of these systems

Effects of Kinesthetic and Cutaneous Stimulation During the Learning of a Viscous Force Field

Haptic stimulation can help humans learn perceptual motor skills, but the precise way in which it influences the learning process has not yet been clarified. This study investigates the role of the kinesthetic and cutaneous components of haptic feedback during the learning of a viscous curl field, taking also into account the influence of visual feedback. We present the results of an experiment in which 17 subjects were asked to make reaching movements while grasping a joystick and wearing a pair of cutaneous devices. Each device was able to provide cutaneous contact forces through a moving platform. The subjects received visual feedback about joystick’s position. During the experiment, the system delivered a perturbation through (1) full haptic stimulation, (2) kinesthetic stimulation alone, (3) cutaneous stimulation alone, (4) altered visual feedback, or (5) altered visual feedback plus cutaneous stimulation. Conditions 1, 2, and 3 were also tested with the cancellation of the visual feedback of position error. Results indicate that kinesthetic stimuli played a primary role during motor adaptation to the viscous field, which is a fundamental premise to motor learning and rehabilitation. On the other hand, cutaneous stimulation alone appeared not to bring significant direct or adaptation effects, although it helped in reducing direct effects when used in addition to kinesthetic stimulation. The experimental conditions with visual cancellation of position error showed slower adaptation rates, indicating that visual feedback actively contributes to the formation of internal models. However, modest learning effects were detected when the visual information was used to render the viscous field

Effects of kinesthetic and cutaneous stimulation during the learning of a viscous force field

Haptic stimulation can help humans learn perceptual motor skills, but the precise way in which it influences the learning process has not yet been clarified. This study investigates the role of the kinesthetic and cutaneous components of haptic feedback during the learning of a viscous curl field, taking also into account the influence of visual feedback. We present the results of an experiment in which 17 subjects were asked to make reaching movements while grasping a joystick and wearing a pair of cutaneous devices. Each device was able to provide cutaneous contact forces through a moving platform. The subjects received visual feedback about joystick\u2019s position. During the experiment, the system delivered a perturbation through (1) full haptic stimulation, (2) kinesthetic stimulation alone, (3) cutaneous stimulation alone, (4) altered visual feedback or (5) altered visual feedback plus cutaneous stimulation. Conditions 1, 2 and 3 were also tested with the cancellation of the visual feedback of position error. Results indicate that kinesthetic stimuli played a primary role during motor adaptation to the viscous field, which is a fundamental premise to motor learning and rehabilitation. On the other hand, cutaneous stimulation alone appeared not to bring significant direct or adaptation effects, although it helped in reducing direct effects when used in addition to kinesthetic stimulation. The experimental conditions with visual cancellation of position error showed slower adaptation rates, indicating that visual feedback actively contributes to the formation of internal models. However, modest learning effects were detected when the visual information was used to render the viscous field