Thirteen healthy subjects, 2 females age: All participants were right-handed based on their preferred hand for writing, eating and throwing [ 21 ]. Kinematic data were recorded from small IRED markers attached to the tips of thumb and index finger, and wrist at the center of the line running between the ulnar and radial styloid process. The virtual environment was calibrated so that the objects were located at the same distance as in the physical environment.
The objects used in the study physical and virtual were three different sized rectangular prisms with equal width W and height H of 2. Sizes S of the graspable dimension were: Large - 7. All objects were rotated along their vertical axis Z to 65 degrees measured from horizontal X axis to make them easier to grasp without excessive wrist extension see Fig. Schematic illustration of the experimental setup.
Subjects sat comfortably in front of a table. They placed their dominant right hand on the table in a comfortable pinch position lightly holding a wooden peg which maintained a starting distance between thumb and index of 1. The thumb was placed on the start switch next to the peg. Each trial began with an auditory signal, cuing the subject to reach, grasp, and lift the virtual or physical object see Fig. Subjects were instructed to reach naturally toward the object with the dominant upper limb, without leaning their trunk forward, at their preferred speed keeping their hand relatively parallel to the table to reduce vertical movements.
Contact with the virtual object was controlled by a collision detection algorithm which colored the virtual object red when the fingertip spheres reached the location of the object to make virtual objects easy to grasp the total collision error margin was set to 1. As the object was lifted from the table, the subject kept it in the vertical position before putting the object back down in VR, the object was held above the table until it disappeared and returning their hand to the starting position.
Overhead lights were turned on between trials to prevent dark adaptation. Therefore, visual information remained similar across the environments. Before data collection, subjects were familiarized with the setup and procedure, particularly to the VE environment.
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The experiment consisted of trials trials in the PE block, trials in the VE block. Three seconds were allowed for each trial. Trials were cropped from movement onset start switch to moment offset contact of both thumb and index finger with the object. In the physical environment, offset was defined as the moment when aperture stopped decreasing. In VR, offset was defined as the timestamp when the virtual object was successfully grasped thumb and index finger markers met the collision detection criteria. Based on the markers attached to fingertips thumb, index , the following kinematics were calculated.
Grasping components: movement time MT as the time between movement onset and offset, grip aperture as the 2D horizontal plane distance in time between thumb and index markers at each sample, peak aperture PA maximum value of grip aperture , and time to peak aperture TPA. The rationale for this normalization was two-fold. First, markers were attached to the dorsum of the digits on the nail in order to not create a barrier between the finger pads and the object that would interfere with grasping.
In the VE, the collision detection algorithm was dependent on the position of these markers. This created a discrepancy between PE and VE in the final grip aperture at the time of grasp roughly equal to the width of the finger from pad to nail. The described normalization accounts for this discrepancy. Second, normalization in this way permitted the direct comparison of aperture profiles and features, such as the size normalized peak aperture snPA , between different size objects.
To better understand motor planning, we also analyzed digit positions along the vertical object at movement offset object grasp. Specifically, we calculated the vertical distance between the thumb and index finger. This measure is analogous to the COP difference that has been commonly calculated in studies of digit force planning [ 22 , 23 ], though obviously lacks information about forces on the object. Based on the wrist marker, the following transport components were calculated: the 2D position of the transport component in the horizontal plane.
Transport velocity was calculated as the first derivative of wrist position. In order to account for variability in movement times between subjects and trial condition for, time to peak measures were time normalized as percentage of MT relative time to peak aperture - rTPA, and relative time to peak transport velocity - rTPV. Finally, hand distance to the object at peak aperture - hdPA the 2D distance from wrist marker to the object at peak aperture was used to determine whether the lack of haptic feedback affects the organization of aperture closure.
The Shapiro-Wilk test was used to verify the normality of data distribution; all variables met this assumption.
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To compare slopes between linear regressions and to assess the vertical distance between the thumb and index finger positions both for PE and VE t-test was used. All statistical analyses were performed using Statistica ver. All variables are presented as means with standard deviations. Correlational analyses examining differences in the relationship between aperture and transport velocity profiles between the physical PE and virtual hf-VE environment indicated largely invariant movement patterns see Fig.
Invariant movement patterns are also evident when the positions of individual markers are compared in the horizontal plane. Grip aperture left y axis, blue and grey and transport velocity right y axis, red during reach-to-grasp movement for all conditions. Presented data are time normalized, profiles showed means with standard deviations, solid lines PE, dashed lines VE. Trajectories of reaching wrist marker - W and grasping index finger marker — I, and thumb marker - T averaged across all subjects, for each condition.
Solid and dashed lines represent the mean trajectories, with shaded areas representing the standard deviation. On average, subjects needed more time to reach-to-grasp objects in VE PE Expectedly, the analysis also showed a main effect of factor Distance F 1. The differences in MT between Medium and Small object sizes across environments were not significant, see Fig.
The significant interaction in MT suggests that differences between environments are size-, but not distance-dependent. Since MT between environments exhibited significant differences, further analyses of temporal features were conducted using time-normalized data. There was a significant interaction between factors Environment and Size F 1. There were no significant interactions. Note that variability was also larger in VE, which might reflect uncertainty of grasping the virtual objects see Fig.
There were no other significant main effects nor interactions. Size normalized aperture. In general, subjects began closing their grip relatively earlier in VE 4. A significant main effect of factor Distance F 1. Panels a, c, d - significant interactions between Environment and Size factors, a - movement time, c - peak transport velocity, and d - hand distance to the object at peak aperture. Panel b - comparison of aperture overshooting between environments and object sizes.
Coordination of reach-to-grasp in physical and haptic-free virtual environments
A graphic representation of reach-to-grasp coupling is presented on Fig. First, temporal data were plotted of the reaching component against the grasping component both for PE and hf-VE. Then each of these data sets were fitted with linear regression models.
Panel a - linear regressions between times to peak aperture and peak transport velocity in physical PE and virtual environments VE. Panel b - linear regressions between relative times to peak aperture and peak transport velocity in PE and VE. Based on the observed significant main effect and interaction between environment and object size on movement time see Fig. To do so, we plotted transport velocity against size-normalized aperture. The resulting curves revealed three distinct phases of the reach-to-grasp movement which we labeled: Initiation I from movement onset to peak transport velocity, Shaping S from peak transport velocity to peak aperture, and Closure C from peak aperture to movement offset see Fig.
Relative time of three phases of reach-to-grasp movement averaged across all conditions. Panel a - grip aperture and transport velocity profiles with peak values. Panel b - three phases of reach to grasp movement: I - initiation phase, S - shaping phase, c - closure phase described in the text ; Panel c - relative time of individual phases between physical PE and virtual VE environments.
Post-hoc tests revealed that the proportion of movement dedicated to the initiation phase remained the same across environments. The analysis of vertical distance between the thumb and index at movement offset object grasp showed no significant differences between physical 0. Digit positions thumb and index fingertips along the vertical edges of the object gray area at the moment of object grasp averaged across all participants and conditions, PE — physical environment, VE — virtual environment.
The main goal of this study was to determine the potential of current VR systems as a platform for research and rehabilitation [ 4 , 11 , 24 ]. In order to assess the characteristics of movements produced in VR, we tested healthy participants in a comparable reach-to-grasp task in both the PE and the VE. Importantly, we decided not to include haptic feedback, as previous studies have, due to the relatively lower state of development of that technology which results in reduced accessibility and practicality [ 1 , 8 , 9 ].
While most of the previous work involving VE has provided haptic feedback to the participants [ 13 , 14 , 25 ], we were interested in determining whether visual feedback alone would support the production of properly coordinated reach-to-grasp movements. The characteristics of prehension movements observed in our study showed that even when haptic information is absent during reach-to-grasp actions in VE, the behavior across environments showed very similar kinematic patterns.
Similarly, as expected, grasp aperture was scaled to object size independently of the environment where the movement was carried out. These results coincide with previous studies comparing movement kinematics in PE and VE [ 13 , 14 , 26 ]. Many studies have postulated that in order to grasp any object successfully, the transport and grasp components must be coordinated [ 17 , 18 , 27 , 28 ].
Moreover, the temporal relationship between the components appears to depend on task goal, object properties, and experience [ 18 ]. In our setup we observed that even if there were some differences in movement kinematics, coordination between the reach and grasp components was preserved across environments see Fig. We suggest that coordination across environments is probably a more relevant measure of whether VE is useful for research and rehabilitation than any specific landmark.
Having said that, the differences we observed between environments as the participants deployed their grasping movements are important to understand for the possible improvement of this technology. Some of these results were not unexpected, as previous studies have found that in VE individuals move slower, particularly showing longer deceleration times both during reaching and grasping as well as in pointing tasks [ 13 , 14 , 25 , 26 , 29 ].
Similarly, the increase in peak aperture we observed in VE for small-sized objects, was previously reported by [ 13 ]. Larger grip aperture in VE especially during grasps to smaller objects have been reported in previous studies comparing physical and virtual environments [ 13 , 14 ]. The effects described suggest to us there was increased perceptual uncertainty during target acquisition in VE. Therefore, a strategy to increase the safety margin in terms of visibility of both the target and the hand during the movement is needed [ 30 ].
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Given the geometry of our setup, where the marker avatar representing the tip of the index finger is eclipsed by the distant edge of the virtual object near the time of peak aperture, it is possible that participants required more time and larger distance between the digits compared to PE, when acquiring the target object.
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