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While mechanical vibration lessens discomfort associated with injection site pain (ISP), many local anesthetic injectors (LAIs) do not use vibratory anesthetic devices (VADs). Injector preference of vibration device is influenced by functional concerns, but qualitatively there is an element of adoption that is driven by visual feedback. We sought to capture operator preferences of vibration device design elements to further understand why injectors do not use these devices. We conducted a survey of image preferences among nurses and medical assistants employed at 8 dermatological clinics to investigate barriers to VAD use. Images were electronically modified with features distinct from the original device (a VAD commonly used in clinical practice). Participants rated their likelihood and comfort of use of each VAD represented in the images. Two-sample t-tests were used to compare the rating of the unmodified VAD to each modified VAD within participants. A response rate of 100% was achieved with 35 participants (average age, 38.5 years; 6 (17.1%) male, 29 (82.9%) female). Despite 28 (80%) participants knowing that mechanical vibration reduces ISP, only 16 (45.7%) endorsed ever using mechanical vibration as topical anesthetic. Images modified by pattern, color, and sterility covering were rated significantly lower than the original, unmodified VAD image (plain white VAD), confirming that visual feedback does impact adoption. Through independent comment categorization, aesthetics were found to be important to LAIs. Aesthetic preferences opposing functional concerns may factor into the lack of VAD use. Defining these visual preference barriers to adoption may help promote VAD use during dermatologic procedures.

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This study investigates the effects of two stimulation modalities (stretch and vibration) on natural touch sensation on the volar forearm. The skin-textile interaction was implemented by scanning three textures across the left forearm. The resulting skin displacements were recorded by the digital image correlation technique to capture the information imparted by the textures. The texture recordings were used to create three playback modes (stretch, vibration, and both), which were reproduced on the right forearm. Two psychophysical experiments compared the texture scans to rendered texture playbacks. The first experiment used a matching task and found that to maximize perceptual realism, i.e., similarity to a physical reference, subjects preferred the rendered texture to have a playback intensity of 1X - 2X higher on DC components (stretch), and 1X - 3.5X higher on AC components (vibration), varying across textures. The second experiment elicited similarity ratings between the texture scans and playbacks and showed that a combination of stretch and vibration was required to create differentiated texture sensations. However, the intensity amplification and use of two stimuli were still insufficient to create fully realistic texture sensations. We conclude that mechanisms beyond single-site uniaxial stimuli are needed to reproduce realistic textural sensations.

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PURPOSE: Successful implementation of precision education systems requires widespread adoption and seamless integration of new technologies with unique data streams that facilitate real-time performance feedback. This paper explores the use of sensor technology to quantify hands-on clinical skills. The goal is to shorten the learning curve through objective and actionable feedback. METHOD: A sensor-enabled clinical breast examination (CBE) simulator was used to capture force and video data from practicing clinicians (N = 152). Force-by-time markers from the sensor data and a machine learning algorithm were used to parse physicians' CBE performance into periods of search and palpation and then these were used to investigate distinguishing characteristics of successful versus unsuccessful attempts to identify masses in CBEs. RESULTS: Mastery performance from successful physicians showed stable levels of speed and force across the entire CBE and a 15% increase in force when in palpation mode compared with search mode. Unsuccessful physicians failed to search with sufficient force to detect deep masses ( F [5,146] = 4.24, P = .001). While similar proportions of male and female physicians reached the highest performance level, males used more force as noted by higher palpation to search force ratios ( t [63] = 2.52, P = .014). CONCLUSIONS: Sensor technology can serve as a useful pathway to assess hands-on clinical skills and provide data-driven feedback. When using a sensor-enabled simulator, the authors found specific haptic approaches that were associated with successful CBE outcomes. Given this study's findings, continued exploration of sensor technology in support of precision education for hands-on clinical skills is warranted.

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As the number of applications for tactile feedback technology rapidly increases, so too does the need for efficient, flexible, and extensible representations of virtual textures. The previously introduced Single-Pitch Texel rendering algorithm offers designers the ability to produce textures with perceptually wide-band spectral characteristics while requiring very few input parameters. This paper expands on the capabilities of the rendering algorithm. Diverse families of fine textures, with widely varied spectral characteristics, were shown to be rendered reliably using the Texel algorithm. Furthermore, by leveraging an assistive algorithm, subjects were shown to consistently navigate the Texel parameter space in a matching task. Finally, a psychophysical study was conducted to demonstrate the rendering algorithm's resilience to spectral quantization, further reducing the data required to represent a virtual texture.

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We present PixeLite, a novel haptic device that produces distributed lateral forces on the fingerpad. PixeLite is 0.15 mm thick, weighs 1.00 g, and consists of a 4×4 array of electroadhesive brakes ("pucks") that are each 1.5 mm in diameter and spaced 2.5 mm apart. The array is worn on the fingertip and slid across an electrically grounded countersurface. It can produce perceivable excitation up to 500 Hz. When a puck is activated at 150 V at 5 Hz, friction variation against the countersurface causes displacements of 627 ± 59 µm. The displacement amplitude decreases as frequency increases, and at 150 Hz is 47 ± 6 µm. The stiffness of the finger, however, causes a substantial amount of mechanical puck-to-puck coupling, which limits the ability of the array to create spatially localized and distributed effects. A first psychophysical experiment showed that PixeLite's sensations can be localized to an area of about 30% of the total array area. A second experiment, however, showed that exciting neighboring pucks out of phase with one another in a checkerboard pattern did not generate perceived relative motion. Instead, mechanical coupling dominates the motion, resulting in a single frequency felt by the bulk of the finger.

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Human manual dexterity relies critically on touch. Robotic and prosthetic hands are much less dexterous and make little use of the many tactile sensors available. We propose a framework modeled on the hierarchical sensorimotor controllers of the nervous system to link sensing to action in human-in-the-loop, haptically enabled, artificial hands.

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Multiple human sensory systems exhibit sensitivity to spatial and temporal variations of physical stimuli. Vision has evolved to offer high spatial acuity with limited temporal sensitivity, while audition has developed complementary characteristics. Neural coding in touch has been believed to transition from a spatial to a temporal domain in relation to surface scale, such that coarse features (e.g., a braille cell or corduroy texture) are coded as spatially distributed signals, while fine textures (e.g., fine-grit sandpaper) are encoded by temporal variation. However, the interplay between the two domains is not well understood. We studied tactile encoding with a custom-designed pin array apparatus capable of deforming the fingerpad at 5 to 80 Hz in each of 14 individual locations spaced 2.5 mm apart. Spatial variation of skin indentation was controlled by moving each of the pins at the same frequency and amplitude, but with phase delays distributed across the array. Results indicate that such stimuli enable rendering of shape features at actuation frequencies up to 20 Hz. Even at frequencies > 20 Hz, however, spatial variation of skin indentation continues to play a vital role. In particular, perceived roughness is affected by spatial variation within the fingerpad even at 80 Hz. We provide evidence that perceived roughness is encoded via a summary measure of skin displacement. Relative displacements in neighboring pins of less than 10 µm generate skin stretch, which regulates the roughness percept.

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Objective. Electrical stimulation of the retina can elicit flashes of light called phosphenes, which can be used to restore rudimentary vision for people with blindness. Functional sight requires stimulation of multiple electrodes to create patterned vision, but phosphenes tend to merge together in an uninterpretable way. Sequentially stimulating electrodes in human visual cortex has recently demonstrated that shapes could be 'drawn' with better perceptual resolution relative to simultaneous stimulation. The goal of this study was to evaluate if sequential stimulation would also form clearer shapes when the retina is the neural target.Approach. Two human participants with retinitis pigmentosa who had Argus®II epiretinal prostheses participated in this study. We evaluated different temporal parameters for sequential stimulation and performed phosphene shape mapping and forced choice discrimination tasks. For the discrimination tasks, performance was compared between stimulating electrodes simultaneously versus sequentially.Main results. Phosphenes elicited by different electrodes were reported as vastly different shapes. For sequential stimulation, the optimal pulse train duration was 200 ms when stimulating at 20 Hz and the optimal gap interval was tied between 0 and 50 ms. Sequential electrode stimulation outperformed simultaneous stimulation in simple discrimination tasks, in which shapes were created by stimulating 3-4 electrodes, but not in more complex discrimination tasks involving ≥5 electrodes. The efficacy of sequential stimulation depended strongly on selecting electrodes that elicited phosphenes with similar shapes and sizes.Significance. An epiretinal prosthesis can produce coherent simple shapes with a sequential stimulation paradigm, which can be used as rudimentary visual feedback. However, success in creating more complex shapes, such as letters of the alphabet, is still limited. Sequential stimulation may be most beneficial for epiretinal prostheses in simple tasks, such as basic navigation, rather than complex tasks such as novel object identification.

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We used broadband electroadhesion to reproduce the friction force profile measured as a finger slid across a textured surface. In doing so, we were also able to reproduce with high fidelity the skin vibrations characteristic of that texture; however, we found that this did not reproduce the original perception. To begin, the reproduction felt weak. In order to maximize perceptual similarity between a real texture and its friction force playback, the vibratory magnitude of the latter must be scaled up on average ≈ 3X for fine texture and ≈ 5X for coarse texture samples. This additional gain appears to correlate with perceived texture roughness. Additionally, even with optimal scaling and high fidelity playback, subjects could identify which of two reproductions corresponds to a real texture with only 71 % accuracy, as compared to 95 % accuracy when using real texture alternatives. We conclude that while tribometry and vibrometry data can be useful for texture classification, they appear to contribute only partially to texture perception. We propose that spatially distributed excitation of skin within the fingerpad may play an additional key role, and may thus be able to contribute to high fidelity texture reproduction.

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This paper introduces a novel rendering algorithm for virtual textures, specifically those with characteristic length scales below 1 mm. By leveraging the relatively lossy mode of human tactile perception at this length scale, a virtual texture with wide-band spectral characteristics can be reduced to a spatial sequence of single-frequency texels, where each frequency is pulled stochastically from a distribution. A psychophysical study was conducted to demonstrate that, below a limiting physical texel length, virtual textures defined by identical frequency distributions are perceptually indiscriminable. Additionally, an exploratory study mapped the distribution parameters of the texel-based rendering to spectral characteristics of perceptually similar multi-frequency virtual textures.

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Friction modulation technology enables the creation of textural effects on flat haptic displays. However, an intuitive and manageably small design space for construction of such haptic textures remains an unfulfilled goal for user interface designers. In this paper, we explore perceptually relevant features of fine texture for use in texture construction and modification. Beginning with simple sinusoidal patterns of friction force that vary in frequency and amplitude, we define irregularity, essentially a variable amount of introduced noise, as a third building block of a texture pattern. We demonstrate using multidimensional scaling that all three parameters are scalable features perceptually distinct from each other. Additionally, participants' verbal descriptions of this 3-dimensional design space provide insight into their intuitive interpretation of the physical parameter changes.

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Wearable cognitive assistants (WCA) are anticipated to become a widely-used application class, in conjunction with emerging network infrastructures like 5G that incorporate edge computing capabilities. While prototypical studies of such applications exist today, the relationship between infrastructure service provisioning and its implication for WCA usability is largely unexplored despite the relevance that these applications have for future networks. This paper presents an experimental study assessing how WCA users react to varying end-to-end delays induced by the application pipeline or infrastructure. Participants interacted directly with an instrumented task-guidance WCA as delays were introduced into the system in a controllable fashion. System and task state were tracked in real time, and biometric data from wearable sensors on the participants were recorded. Our results show that periods of extended system delay cause users to correspondingly (and substantially) slow down in their guided task execution, an effect that persists for a time after the system returns to a more responsive state. Furthermore, the slow-down in task execution is correlated with a personality trait, neuroticism, associated with intolerance for time delays. We show that our results implicate impaired cognitive planning, as contrasted with resource depletion or emotional arousal, as the reason for slowed user task executions under system delay. The findings have several implications for the design and operation of WCA applications as well as computational and communication infrastructure, and additionally for the development of performance analysis tools for WCA.

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In this article, we have developed a novel button click rendering mechanism based on active lateral force feedback. The effect can be localized because electroadhesion between a finger and a surface can be localized. Psychophysical experiments were conducted to evaluate the quality of a rendered button click, which subjects judged to be acceptable. Both the experiment results and the subjects' comments confirm that this button click rendering mechanism has the ability to generate a range of realistic button click sensations that could match subjects' different preferences. We can, thus, generate a button click on a flat surface without macroscopic motion of the surface in the lateral or normal direction, and can localize this haptic effect to an individual finger.

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[This corrects the article DOI: 10.1371/journal.pone.0226880.].

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Haptic exploration is a key skill for both robots and humans to discriminate and handle unknown objects or to recognize familiar objects. Its active nature is evident in humans who from early on reliably acquire sophisticated sensory-motor capabilities for active exploratory touch and directed manual exploration that associates surfaces and object properties with their spatial locations. This is in stark contrast to robotics. In this field, the relative lack of good real-world interaction models-along with very restricted sensors and a scarcity of suitable training data to leverage machine learning methods-has so far rendered haptic exploration a largely underdeveloped skill. In robot vision however, deep learning approaches and an abundance of available training data have triggered huge advances. In the present work, we connect recent advances in recurrent models of visual attention with previous insights about the organisation of human haptic search behavior, exploratory procedures and haptic glances for a novel architecture that learns a generative model of haptic exploration in a simulated three-dimensional environment. This environment contains a set of rigid static objects representing a selection of one-dimensional local shape features embedded in a 3D space: an edge, a flat and a convex surface. The proposed algorithm simultaneously optimizes main perception-action loop components: feature extraction, integration of features over time, and the control strategy, while continuously acquiring data online. Inspired by the Recurrent Attention Model, we formalize the target task of haptic object identification in a reinforcement learning framework and reward the learner in the case of success only. We perform a multi-module neural network training, including a feature extractor and a recurrent neural network module aiding pose control for storing and combining sequential sensory data. The resulting haptic meta-controller for the rigid 16 × 16 tactile sensor array moving in a physics-driven simulation environment, called the Haptic Attention Model, performs a sequence of haptic glances, and outputs corresponding force measurements. The resulting method has been successfully tested with four different objects. It achieved results close to 100% while performing object contour exploration that has been optimized for its own sensor morphology.

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This paper describes a prototype guidance system, "FingerSight," to help people without vision locate and reach to objects in peripersonal space. It consists of four evenly spaced tactors embedded into a ring worn on the index finger, with a small camera mounted on top. Computer-vision analysis of the camera image controls vibrotactile feedback, leading users to move their hand to near targets. Two experiments tested the functionality of the prototype system. The first found that participants could discriminate between five different vibrotactile sites (four individual tactors and all simultaneously) with a mean accuracy of 88.8% after initial training. In the second experiment, participants were blindfolded and instructed to move their hand wearing the device to one of four locations within arm's reach, while hand trajectories were tracked. The tactors were controlled using two different strategies: (1) repeatedly signal axis with largest error, and (2) signal both axes in alternation. Participants demonstrated essentially straight-line trajectories toward the target under both instructions, but the temporal parameters (rate of approach, duration) showed an advantage for correction on both axes in sequence.

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An electrostatic friction modulation device based on a tablet computer was used to present pattern stimuli to the fingertip for two tasks: detecting patches of friction and matching a frictional pattern to the visual image that produced it. In the detection task, friction patterns were displayed on zero, one two or three cells in a matrix. Errors, whether misses or false alarms, were few. Duration of target-present trials was a linear function of the number of patterns in the display. The intercept indicated an average of under 1 sec to test a location for the presence of a friction patch. The slope was 1.0 sec per item, representing the time to confirm friction change, verify the location, and report. In contrast to fast and accurate detection of friction modulation, identification of patterns by matching to a visual display was at chance, although the patterns were differentiated by form and scale. Given that the patterns fall within the normal acuity of the fingertip, along with previous evidence that fingertip motion per se does not preclude pattern recognition, it appears that the failure to match tactual patterns to visual images resides in processes inherent in information pickup from friction-modulation displays.

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When assessing the value of visualizations, researchers traditionally focus on efficiency, comprehension, or insight. However, analyzing successful data physicalizations leads to a deep appreciation for hedonic qualities. Informed by the role of emotion in psychology, art, design, marketing, and HCI, we argue for an expanded definition of value, applicable to all forms of data visualization.