Investigating the Effect of Object Edges on Identification During Haptic Exploration

Abstract Body : Introduction & Objective
The cognitive ability to manipulate mental representations of environmental objects and orientations, perceived primarily through vision, are termed spatial abilities (SA). These abilities are correlated to learning anatomy and technical skills in health care. Haptic abilities (HA) are the integration of tactile information from the proximal environment to create mental representations. Haptics are involved in handling specimens in anatomy and performing any technical skill. During haptic exploration, object edges are thought to aid shape identification, but many natural objects, like anatomical specimens, lack prominent edges. Therefore, the objective was to determine if the intensity of object edges affects identification during haptic exploration, and to examine if performance is dependent on SA.

Materials and Methods
The redrawn Vandenberg and Kuse Mental Rotations Test (MRT) was used to quantify SA in students. To quantify HA, the MRT was adapted into the Edged Haptic Abilities Test (EHAT), a three-dimensional (3D) test that required participants to compare 3D-printed handheld MRT-styled objects. Unlike the MRT, the EHAT objects had three different edge intensities: hard edge (HE), with 90˚ edges; soft edge (SE), with rounded edges; and no edge (NE), cylindrical shaped. The goal of the EHAT was to match an exemplar object to one of three option objects, visually in a sighted condition (S-EHAT) and through blind touch in a haptic condition (H-EHAT). Performance was evaluated based on number of correct responses (maximum 15 per edge type) and response time within a 10 second (s) (S-EHAT) and 40s (H-EHAT) limit. The sample size was further divided into two groups based on SA. Video recordings were taken during the H-EHAT for future post-hoc identification and analysis of haptic strategies. Statistical tests included Spearman’s correlation coefficient (r) and paired t-test. A p< 0.05 was deemed statistically significant.

Results
An initial sample size of six (5F, 19-30yrs) was analyzed. MRT score was strongly correlated to S-EHAT score (r=0.64) but weakly correlated to H-EHAT score (r=0.20). Scores in the H-EHAT differed between NE and SE [mean 9.8±3.4 (SD) vs 12.3±2.3; p=0.029]. Response times within H-EHAT differed between edge type; NE vs HE (30.4±7.2 vs 26.8±8.0s; p=0.004) and NE vs SE (30.4±7.2 vs 27.9±8.3s; p=0.043). Further, a median split of the overall MRT scores (9.6±3.9) separated the group into high (n=3, 14.3±2.5) and low (n=3, 6.7±2.3) SA individuals (H/LSA) (p=0.006). No significant differences in performance across edge type or sensory condition existed for HSA; LSA had a difference in response time between NE and HE (34.1±8.6 vs 30.9±10.4s; p< 0.05) during the H-EHAT.

Conclusion
Preliminary results suggested that the intensity of object edges did influence the accuracy and speed of haptic object identification. Further, LSA relied more on edges for haptic identification than HSA based on response time.

Significance
This research guides philosophies of pedagogical approaches. Both HA and SA are involved in performance in anatomy and technical skills in health care. Ascertaining if edge intensity affects haptic object identification reveals gaps in anatomical and technical skills learning. Future analysis of haptic strategies in H-EHAT may point to optimal techniques and conditions for object identification based on object properties and SA, with the goal to implement findings into evidence-based practice.