Haptic Discrimination of Distance

Abstract

While quite some research has focussed on the accuracy of haptic perception of distance, information on the precision of haptic perception of distance is still scarce, particularly regarding distances perceived by making arm movements. In this study, eight conditions were measured to answer four main questions, which are: what is the influence of reference distance, movement axis, perceptual mode (active or passive) and stimulus type on the precision of this kind of distance perception? A discrimination experiment was performed with twelve participants. The participants were presented with two distances, using either a haptic device or a real stimulus. Participants compared the distances by moving their hand from a start to an end position. They were then asked to judge which of the distances was the longer, from which the discrimination threshold was determined for each participant and condition. The precision was influenced by reference distance. No effect of movement axis was found. The precision was higher for active than for passive movements and it was a bit lower for real stimuli than for rendered stimuli, but it was not affected by adding cutaneous information. Overall, the Weber fraction for the active perception of a distance of 25 or 35 cm was about 11% for all cardinal axes. The recorded position data suggest that participants, in order to be able to judge which distance was the longer, tried to produce similar speed profiles in both movements. This knowledge could be useful in the design of haptic devices.

Radial trunk-centred reference frame in haptic perception

“…Cutaneous inputs, proprioceptive inputs, and movement information were all found to contribute to shape perception or the perception of angular relationships 20 . Movement 21 , 22 , motor 23 , or proprioceptive 24 , 25 information were also found to contribute to length and distance perception, and so did arm-hand configurations 11 , 26 and head positions 27 . Depending on the task, each of these inputs could be relevant or available, and could potentially explain the diversity of reference frames previously observed.…”

Evaluation of Direct Haptic 4D Volume Rendering of Partially Segmented Data for Liver Puncture Simulation

“…The used metrics ensure that our results can still be related to new JNDs published in the future. In light of the currently available JNDs for the hand-arm system from refs 25 , 27 , of 15–26% (0.12–0.21 N) and 11% (3 mm) for the force and distance magnitudes respectively, our mean errors are small (Figs 4 and 6 ). Also the high percentage of absolutely correctly rendered forces (88% of positions) underlines this statement, only 12% of all path positions are affected by errors.…”

“…In 12% of the path positions the detected errors are haptically irrelevant for the user experience. This is due to the fact that the puncture incident mismatch is mostly below JND-thresholds in terms of insertion depth 25 , 26 and very similar in force amplitude to the puncture event using gold-standard label data. The force errors are also below the force JND threshold adapted to our context 27 .…”

“…We use easily implementable objective force signal metrics and relate them to the currently published spatial and force JNDs 25 , 27 of the hand-arm system for haptic device usage. The JNDs are subject to ongoing research and therefore may change.…”

Enhancing general spatial skills of young visually impaired people with a programmable distance discrimination training: a case control study

“…Haptic distance estimation is influenced by task-specificity and response mode [15, 16]. For example, the relationship between physical length of a stimulus and its estimated size is linear with a slope ~ 1 when the estimation is performed using two index fingers, one at the beginning and one at the end of the stimulus [17], or with a single finger (or the whole hand) moved along the stimulus [18, 19].…”