Haptic integration of planar size with hardness, texture, and planar contour

Three studies investigate the role of size information in haptic classification of custom-made planar objects when size covaries with hardness, texture, or planar contour. The haptic exploratory procedure (Lederman & Klatzky, 1987) associated with size extraction is also sufficient for encoding shape, which should promote their integration. Experiment 1 showed substantial facilitation of classification by redundant size and shape cues, indicating the coprocessing of size and shape. Experiments 2 and 3 used a withdrawal paradigm: Classification trials began with two redundant properties, and one was then held constant (withdrawn). Experiment 2 showed that when size and shape were redundant, withdrawal of either impaired responses, whereas when size was redundant with texture or hardness, only size withdrawal had an effect. Experiment 3 demonstrated that this size weighting was not restricted to a single procedure for exploration. Size appears to be highly weighted in haptic classification and potentially integrated with other properties having compatible methods of extraction.     

Face recognition by hand

We investigated participants’ ability to identify and represent faces by hand. In Experiment 1, participants proved surprisingly capable of identifying unfamiliar live human faces using only their sense of touch. To evaluate the contribution of geometric and material information more directly, we biased participants toward encoding faces more in terms of geometric than material properties, by varying the exploration condition. When participants explored the faces both visually and tactually, identification accuracy did not improve relative to touch alone. When participants explored masks of the faces, thereby eliminating material cues, matching accuracy declined substantially relative to tactual identification of live faces. In Experiment 2, we explored intersensory transfer of face information between vision and touch. The findings are discussed in terms of their relevance to haptic object processing and to the faceprocessing literature in general.     

Haptic recognition of static and dynamic expressions of emotion in the live face

If humans can detect the wealth of tactile and haptic information potentially available in live facial expressions of emotion (FEEs), they should be capable of haptically recognizing the six universal expressions of emotion (anger, disgust, fear, happiness, sadness, and surprise) at levels well above chance. We tested this hypothesis in the experiments reported here. With minimal training, subjects' overall mean accuracy was 51% for static FEEs (Experiment 1) and 74% for dynamic FEEs (Experiment 2). All FEEs except static fear were successfully recognized above the chance level of 16.7%. Complementing these findings, overall confidence and information transmission were higher for dynamic than for corresponding static faces. Our performance measures (accuracy and confidence ratings, plus response latency in Experiment 2 only) confirmed that happiness, sadness, and surprise were all highly recognizable, and anger, disgust, and fear less so.     

Watching a cursor distorts haptically guided reproduction of mouse movement

Participants moved a mouse along a force-feedback-defined linear path, either without vision or while watching a cursor set to 1 of 3 levels of visual:haptic gain (all >1:1). They attempted to haptically reproduce the movement without visual feedback. Errors increased with gain, reaching 70% overestimation at the highest gain. Forewarning participants about gain variability did not eliminate this effect. The gain level was potentially cued during the movement by the mismatch between visual feedback and kinesthetic feedback. Moreover, because participants did not achieve cursor-speed constancy across gain levels, visual speed was another cue to gain. Collectively, these cues failed to prevent visual distortion of movement reproduction.