Visuo-Haptic Discrimination of Viscoelastic Materials

Representation of Social Determinants of Health terminology in medical subject headings: impact of added terms

OBJECTIVES

To enhance and evaluate the quality of PubMed search results for Social Determinants of Health (SDoH) through the addition of new SDoH terms to Medical Subject Headings (MeSH).

MATERIALS AND METHODS

High priority SDoH terms and definitions were collated from authoritative sources, curated based on publication frequencies, and refined by subject matter experts. Descriptive analyses were used to investigate how PubMed search details and best match results were affected by the addition of SDoH concepts to MeSH. Three information retrieval metrics (Precision, Recall, and F measure) were used to quantitatively assess the accuracy of PubMed search results. Pre- and post-update documents were clustered into topic areas using a Natural Language Processing pipeline, and SDoH relevancy assessed.

RESULTS

Addition of 35 SDoH terms to MeSH resulted in more accurate algorithmic translations of search terms and more reliable best match results. The Precision, Recall, and F measures of post-update results were significantly higher than those of pre-update results. The percentage of retrieved publications belonging to SDoH clusters was significantly greater in the post- than pre-update searches.

DISCUSSION

This evaluation confirms that inclusion of new SDoH terms in MeSH can lead to qualitative and quantitative enhancements in PubMed search retrievals. It demonstrates the methodology for and impact of suggesting new terms for MeSH indexing. It provides a foundation for future efforts across behavioral and social science research (BSSR) domains.

CONCLUSION

Improving the representation of BSSR terminology in MeSH can improve PubMed search results, thereby enhancing the ability of investigators and clinicians to build and utilize a cumulative BSSR knowledge base.

Perception of Soft Objects in Virtual Environments Under Conflicting Visual and Haptic Cues

In virtual/augmented/mixed reality (VR/AR/MR) applications, rendering soft virtual objects using a hand-held haptic device is challenging due to the anatomical restrictions of the hand and the ungrounded nature of the design, which affect the selection of actuators and sensors and hence limit the resolution and range of forces displayed by the device. We developed a cable-driven haptic device for rendering the net forces involved in grasping and squeezing 3D virtual compliant (soft) objects being held between the index finger and thumb only. Using the proposed device, we investigate the perception of soft objects in virtual environments. We show that the range of object stiffness that can be effectively conveyed to a user in virtual environments (VEs) can be significantly expanded by controlling the relationship between the visual and haptic cues. We propose that a single variable, named Apparent Stiffness Difference, can predict the pattern of human stiffness perception under manipulated conflict, which can be used for rendering a range of soft objects in VEs larger than what is achievable by a haptic device alone due to its physical limits.

Assessing the representational structure of softness activated by words

Softness is an important material property that can be judged directly, by interacting with an object, but also indirectly, by simply looking at an image of a material. The latter is likely possible by filling in relevant multisensory information from prior experiences with soft materials. Such experiences are thought to lead to associations that make up our representations about perceptual softness. Here, we investigate the structure of this representational space when activated by words, and compare it to haptic and visual perceptual spaces that we obtained in earlier work. To this end, we performed an online study where people rated different sensory aspects of soft materials, presented as written names. We compared the results with the previous studies where identical ratings were made on the basis of visual and haptic information. Correlation and Procrustes analyses show that, overall, the representational spaces of verbally presented materials were similar to those obtained from haptic and visual experiments. However, a classifier analysis showed that verbal representations could better be predicted from those obtained from visual than from haptic experiments. In a second study we rule out that these larger discrepancies in representations between verbal and haptic conditions could be due to difficulties in material identification in haptic experiments. We discuss the results with respect to the recent idea that at perceived softness is a multidimensional construct.

Material design of soft biological tissue replicas using viscoelastic micromechanical modelling

Anatomical models for research and education are often made of artificial materials that attempt to mimic biological tissues in terms of their mechanical properties. Recent developments in additive manufacturing allow tuning mechanical properties with microstructural designs. We propose a strategy for designing material microstructures to mimic soft tissue viscoelastic behaviour, based on a micromechanical Mori-Tanaka model. The model was applied to predict homogenised viscoelastic properties of materials, exhibiting a matrix-inclusion microstructure with varying inclusion volume fractions. The input properties were thereby obtained from compression relaxation tests on silicone elastomers. Validation of the model was done with experimental results for composite samples. Finally, different combinations of silicones were compared to mechanical properties of soft tissues (hepatic, myocardial, adipose, cervical, and prostate tissue), found in literature, in order to design microstructures for replicating these tissues in terms of viscoelasticity. The viscoelastic Mori-Tanaka model showed good agreement with the corresponding experimental results for low inclusion volume fractions, while high fractions lead to underestimation of the complex modulus by the model. Predictions for the loss tangent were reasonably accurate, even for higher inclusion volume fractions. Based on the model, designs for 3D printed microstructures can be extracted in order to replicate the viscoelastic properties of soft tissues.

Task and Material Properties Interactively Affect Softness Explorations Along Different Dimensions

Haptic research has frequently equated softness with the compliance of elastic objects. However, in a recent study we have suggested that compliance is not the only perceived material dimension underlying what is commonly called softness [1 ]. Here, we investigate, whether the different perceptual dimensions of softness affect how materials are haptically explored. Specifically, we tested whether also the task, i.e., the attribute that a material is being judged on, might affect how a material is explored. To this end we selected 15 adjectives and 19 materials that each associate with different softness dimensions for the study. In the experiment, while participants freely explored and rated the materials, we recorded their hand movements. These movements were subsequently categorized into distinct exploratory procedures (EPs) and analyzed in a multivariate analysis of variance (MANOVA). The results of this analysis suggest that the pattern of EPs depended not only on the material's softness dimension and the task (i.e., what attributes were rated), but also on an interaction between the two factors. Taken together, our findings support the notion of multiple perceptual dimensions of softness and suggest that participants actively adapt their EPs in a nuanced way when judging a particular softness dimensions for a given material.

An elasticity-curvature illusion decouples cutaneous and proprioceptive cues in active exploration of soft objects

Our sense of touch helps us encounter the richness of our natural world. Across a myriad of contexts and repetitions, we have learned to deploy certain exploratory movements in order to elicit perceptual cues that are salient and efficient. The task of identifying optimal exploration strategies and somatosensory cues that underlie our softness perception remains relevant and incomplete. Leveraging psychophysical evaluations combined with computational finite element modeling of skin contact mechanics, we investigate an illusion phenomenon in exploring softness; where small-compliant and large-stiff spheres are indiscriminable. By modulating contact interactions at the finger pad, we find this elasticity-curvature illusion is observable in passive touch, when the finger is constrained to be stationary and only cutaneous responses from mechanosensitive afferents are perceptible. However, these spheres become readily discriminable when explored volitionally with musculoskeletal proprioception available. We subsequently exploit this phenomenon to dissociate relative contributions from cutaneous and proprioceptive signals in encoding our percept of material softness. Our findings shed light on how we volitionally explore soft objects, i.e., by controlling surface contact force to optimally elicit and integrate proprioceptive inputs amidst indiscriminable cutaneous contact cues. Moreover, in passive touch, e.g., for touch-enabled displays grounded to the finger, we find those spheres are discriminable when rates of change in cutaneous contact are varied between the stimuli, to supplant proprioceptive feedback.

Tactile Exploration Strategies With Natural Compliant Objects Elicit Virtual Stiffness Cues

When interacting with deformable objects, tactile cues at the finger pad help inform our perception of material compliance. Nearly all prior studies have relied on highly homogenous, engineered materials such as silicone-elastomers and foams. In contrast, we employ soft plum fruit varying in ripeness; ecological substances associated with tasks of everyday life. In this article, we investigate volitional exploratory strategies and contact interactions, for comparison to engineered materials. New measurement techniques are introduced, including an ink-based method to capture finger pad to fruit contact interactions, and instrumented force and optical sensors to capture imposed force and displacement. Human-subjects experiments are conducted for both single finger touch and two finger grasp. The results indicate that terminal contact areas between soft and hard plums are indistinguishable, but the newly defined metric of virtual stiffness can differentiate between the fruits' ripeness, amidst their local variations in geometry, stiffness, and viscoelasticity. Moreover, it affords discrimination independent of one's touch force. This metric illustrates the tie between the deployment of active, exploratory strategies and the elicitation of optimal cues for perceptual discrimination. Compared to single finger touch, perceptual discrimination improves further in pinch grasp, which is indeed a more natural gesture for judging ripeness.