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Human Factors

Human Haptics

The behavior of the human haptic system has been the subject of far more systematic study than has machine haptics. There are several haptically important dimensions of object recognition, including texture, hardness, shape, and thermal conductivity (Klatzky, Lederman, & Reed, 1987). Most researchers report that subjects are able to discriminate textures and to a lesser extent shapes using the haptic sense only. For example, Ballesteros, Manga, and Reales (1997) reported a moderate level of accuracy for single-finger haptic detection of raised-line shapes, with asymmetric shapes being more readily discriminated. Hatwell (1995) found that recall of texture information coded haptically was successful when memorization was intentional, but not when it was incidental, indicating that haptic information processing may be effortful for subjects.

Available evidence indicates that haptic information processing in adults involves construal of a stimulus object, such as a texture sample, as coordinates on a set of underlying perceptual dimensions, like "hard-soft" or "rough-smooth." Developmental studies by Berger and Hatwell (1993, 1995) have shown that in discriminating texture samples varying with respect to the density and hardness dimensions, older subjects were less likely than younger ones to make global assessments of the stimuli and more likely to invoke the separate dimensions as judgment criteria. Hughes and Jansson (1994) note that texture gradients, like textures, can be multidimensional and suggest candidate dimensions such as variations in the size, height, and shape of elements. Hollins, Faldowski, Rao, and Young (1993) passed samples of 17 textures over the fingertips of subjects whose view of the samples was restricted. The subjects sorted the texture samples into categories based on similarity, and then rated the samples against a series of scales measuring well-established perceptual dimensions such as roughness and hardness, and several other less-well studied potential dimensions such as "slippery-sticky." Co-occurrence data from the sorting task were converted to dissimilarities and submitted to a multidimensional scaling analysis. The researchers reported that there were two clear, orthogonal perceptual dimensions, "rough-smooth" and "soft-hard," underlying the classification of samples and speculated about a possible third dimension, "springiness."

Hughes and Jansson (1994) lament the inadequacy of embossed maps and other devices intended to communicate information through the sense of touch, a puzzling state of affairs insomuch as perception by active touch (purposeful motion of the skin surface relative to the surface of some distal object) appears to be comparatively accurate, and even more accurate than vision in apprehending certain properties such as smoothness (Hughes & Jansson, p. 302). The authors note in their critical review of the literature on active-passive equivalence that active and passive touch (as when a texture is presented to the surface of the fingers, see Hollins et al., 1993) have repeatedly been demonstrated by Lederman and her colleagues (Lederman, 1985; Lederman, Thorne, & Jones, 1986; Loomis & Lederman, 1986) to be functionally equivalent, in that touch modality does not seem to account for a significant proportion of the variation in judgments of such basic dimensions as roughness, even though the two types of touch may lead to different sorts of attributions (respectively, about the texture object and about the cutaneous sensing surface) and motor information should clearly be useful in assessing the size and distribution of surface protrusions and retractions. Active and passive touch are more likely to be equivalent in certain types of perceptual tasks; active touch should be less relevant to judgments of "hardness" than it is to assessments of "springiness." Such findings should be of interest to those working with machine haptics, as most of the application development in this field involves using the displays under conditions of active rather than passive touch.

Some researchers have reported that shape and texture recognition improve with the addition of vision, although there is not uniform agreement as to the extent of the similarity between haptic and visual information processing. Balakrishnan, Klatzky, and Loomis (1989), although reporting that length-distortion effects (attributing greater distances between two points as a path between them becomes more winding) were less pronounced under visual path tracing than had been found in previous experiments using haptic exploration, nonetheless concluded that the encoding processes are similar in the two domains. Klatzky, Lederman, and Reed (1987), however, concluded after a series of experiments that the encoding pathways are fundamentally different in the haptic and visual systems, such that the visual system is more oriented to the discrimination of shape and the haptic system to substance. Heller's work (1982) suggests that the addition of visual information about "where the hand is" (as opposed to what the surface texture looks like) is the critical contributory factor in any improved performance arising from bimodal information acquisition. Work reported by Lederman, Thorne, and Jones (1986) indicates that the dominance of one system over the other in texture discrimination tasks is a function of the dimension of judgment being employed. In making judgments of density, the visual system tends to dominate, while the haptic system is most salient when subjects are asked to discriminate textures on the basis of roughness.

Lederman, Klatzky, Hamilton, and Ramsay (1999) studied the psychophysical effects of haptic exploration speed and mode of touch on the perceived roughness of metal objects when subjects used a rigid probe, not unlike the PHANToM stylus (see also Klatzky and Lederman, Chapter 10, this volume). In earlier work, Klatzky and Lederman found that subjects wielding rigid stick-like probes were less effective at discriminating surface textures than with the bare finger. In a finding that points to the importance of tactile arrays to haptic perception, the authors noted that when a subject is actively exploring an object with the bare finger, speed appears to have very little impact on roughness judgments, because subjects may have used kinesthetic feedback about their hand movements; however, when a rigid probe is used, people should become more reliant on vibrotactile feedback, since the degree of displacement of fingertip skin no longer is commensurate with the geometry of the surface texture.

Machine Haptics

Psychophysical studies of machine haptics are now beginning to accumulate. Experiments performed by von der Heyde and Hager-Ross (1998) have produced classic perceptual errors in the haptic domain: For instance, subjects who haptically sorted cylinders by weight made systematic errors consistent with the classical size-weight illusion. Experiments by Jansson, Faenger, Konig, and Billberger (1998) on shape sensing with blindfolded sighted observers were described above. Ernst and Banks (2001) reported that although vision usually "captures" haptics, in certain circumstances information communicated haptically (via two PHANToMs) assumes greater importance. They found that when noise is added to visual data, the haptic sense is invoked to a greater degree. Ernst and Banks concluded that the extent of capture by a particular sense modality is a function of the statistical reliability of the corresponding sensory input.

Kirkpatrick and Douglas (1999) argue that if the haptic interface does not support certain exploratory procedures, such as enclosing an object in the case of the single-point PHANToM tip, then the quick grasping of shape that enclosure provides will have to be done by techniques that the interface does support, such as tracing the contour of the virtual object. Obviously, this is slower than enclosing. The extent to which the haptic interface supports or fails to support exploratory processes contributes to its usability. Kirkpatrick and Douglas evaluated the PHANToM interface's support for the task of shape determining, comparing and contrasting its usability in three modes: vision only; haptics only; and haptics and vision combined, in a non-stereoscopic display. When broad exploration is required for quick object recognition, haptics alone is not likely to be very useful when the user is limited to a single finger whose explorations must be recalled and integrated to form an overall impression of shape. Vision alone may fail to provide adequate depth cues (e.g., the curved shape of a teapot). Kirkpatrick and Douglas assert that the effect of haptics and vision is not additive and that the combination of them would provide a result exceeding what an additive model might predict.

Kirkpatrick and Douglas (1999) also report that among the factors that influence the speed of haptic recognition of objects are the number of different object attributes that can be perceived simultaneously and the number of fingers that are employed. This work suggests that object exploration with devices like the PHANToM, which offer kinesthetic but not cutaneous feedback, will yield suboptimal results with respect both to exploration speed and accuracy when compared to the bare hand. It further suggests that speed and accuracy may improve with additional finger receptors.

With the advent of handheld devices and the possibility of the incorporation of haptics into such devices, it is becoming increasingly important to determine just how small a haptic effect can be perceived. Dosher, Lee, and Hannaford (Chapter 12, this volume) report that users can detect haptic effects whose maximum force is about half the measured Coulomb friction level of the device and about one-third the measured static friction level. They note that their results can be expected to vary by device and that it remains to be seen whether or not a measurable effect is necessarily one that can help users accomplish their tasks.

Srinivasan and Basdogan (1997) note the importance of other modalities in haptic perception (e.g., sounds of collision with objects, etc.). They report that with respect to object deformation, visual sensing dominates over proprioception and leads to severe misjudgments of object stiffness if the graphic display is intentionally skewed (Srinavasan, Beauregard, & Brock, 1996). Sound appears to be a less important perceptual mediator than vision. In an unpublished study by Hou and Srinivasan, reported in Srinivasan and Basdogan (1997), subjects navigating through a maze were found to prefer large visual-haptic ratios and small haptic workspaces. Best results were achieved in the dual-modality condition, followed by haptic only and then vision only. It is apparent that the relative contribution of visual and haptic perception will vary as a function of task, but it is also apparent, as Srinivasan and Basdogan conclude, that the inadequacies of force-feedback display (e.g., limitations of stiffness) can be overcome with appropriate use of other modalities. In Chapter 11 Jeong and Jacobson consider the question of how effective haptic and auditory displays are when combined, whether or not they interfere with one another, and how a user's previous experience with a modality affects the success of the integration and the efficacy of the multimodal display.

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