Can Virtual Reality Trainers Improve the Compliance Discrimination Abilities of Trainee Surgeons?

The assessment of tissue compliance using a handheld tool is an important skill in medical areas such as laparoscopic and dental surgery. The increasing prevalence of virtual reality devices raises the question of whether we can exploit these systems to accelerate the training of compliance discrimination in trainee surgeons. We used a haptic feedback device and stylus to assess the abilities of naïve participants to detect compliance differences with and without knowledge of results (KR) (groups 1 and 2), as well as the abilities of participants who had undergone repetitive training over several days (group 3). Kinematic analyses were carried out to objectively measure the probing action. Untrained participants had poor detection thresholds (mean just noticeable difference, JND = 33%), and we found no effect of KR (provided after each trial) on performance (mean JND = 35%). Intensive training dramatically improved group performance (mean JND = 12%). Probing action (in particular, slower movement execution) was associated with better detection thresholds, but training did not lead to systematic changes in probing behaviour. These findings set a benchmark for training systems that act to increase perceptual sensitivity and guide the learner toward optimal movement strategies to improve discrimination

Identifying Haptic Exploratory Procedures by Analyzing Hand Dynamics and Contact Force

Haptic exploratory procedures (EPs) are prototypical hand movements that are linked to the acquisition of specific object properties. In studies of haptic perception, hand movements are often classified into these EPs. Here, we aim to investigate several EPs in a quantitative manner to understand how hand dynamics and contact forces differ between them. These dissimilarities are then used to construct an EP identification model capable of discriminating between EPs based on the index finger position and contact force. The extent to which the instructed EPs were distinct, repeatable, and similar across subjects was confirmed by showing that more than 95 percent of the analyzed trials were classified correctly. Finally, the method is employed to investigate haptic exploratory behavior during similarity judgments based on several object properties. It seems that discrimination based on material properties (hardness, roughness, and temperature) yields more consistent classification results compared to discrimination based on the acquisition of shape information. © 2013 IEEE

Active Haptic Exploration of Softness: Indentation Force Is Systematically Related to Prediction, Sensation and Motivation

Active finger movements play a crucial role in natural haptic perception. For the perception of different haptic properties people use different well-chosen movement schemes (Lederman and Klatzky, 1987). The haptic property of softness is stereotypically judged by repeatedly pressing one’s finger against an objects’ surface, actively indenting the object. It has been shown that people adjust the peak indentation forces of their pressing movements to the expected stimulus’ softness in order to improve perception (Kaim and Drewing, 2011). Here, we aim to clarify the mechanisms underlying such adjustments. We disentangle how people modulate executed peak indentation forces depending on predictive vs. sensory signals to softness, and investigate the influence of the participants’ motivational state on movement adjustments. In Experiment 1, participants performed a two alternative forced-choice (2AFC) softness discrimination task for stimulus pairs from one of four softness categories. We manipulated the predictability of the softness category. Either all stimuli of the same category were presented in a blocked fashion, which allowed predicting the softness category of the upcoming pair (predictive signals high), or stimuli from different categories were randomly intermixed, which made prediction impossible (predictive signals low). Sensory signals to softness category of the two stimuli in a pair are gathered during exploration. We contrasted the first indentation (sensory signals low) and last indentation (sensory signals high) in order to examine the effect of sensory signals. The results demonstrate that participants systematically apply lower forces when softer objects (as compared to harder objects) are indicated by predictive signals. Notably, sensory signals seemed to be not as relevant as predictive signals. However, in Experiment 2, we manipulated participant motivation by introducing rewards for good performance, and showed that the use of sensory information for movement adjustments can be fostered by high motivation. Overall, the present study demonstrates that exploratory movements are adjusted to the actual perceptual situation and that in the process of fine-tuning, closed- and open-loop mechanisms interact, with varying contributions depending on the observer’s motivation

Contact Force and Scanning Velocity during Active Roughness Perception

Haptic perception is bidirectionally related to exploratory movements, which means that exploration influences perception, but perception also influences exploration. We can optimize or change exploratory movements according to the perception and/or the task, consciously or unconsciously. This paper presents a psychophysical experiment on active roughness perception to investigate movement changes as the haptic task changes. Exerted normal force and scanning velocity are measured in different perceptual tasks (discrimination or identification) using rough and smooth stimuli. The results show that humans use a greater variation in contact force for the smooth stimuli than for the rough stimuli. Moreover, they use higher scanning velocities and shorter break times between stimuli in the discrimination task than in the identification task. Thus, in roughness perception humans spontaneously use different strategies that seem effective for the perceptual task and the stimuli. A control task, in which the participants just explore the stimuli without any perceptual objective, shows that humans use a smaller contact force and a lower scanning velocity for the rough stimuli than for the smooth stimuli. Possibly, these strategies are related to aversiveness while exploring stimuli

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility

A survey of dextrous manipulation

technical reportThe development of mechanical end effectors capable of dextrous manipulation is a rapidly growing and quite successful field of research. It has in some sense put the focus on control issues, in particular, how to control these remarkably humanlike manipulators to perform the deft movement that we take for granted in the human hand. The kinematic and control issues surrounding manipulation research are clouded by more basic concerns such as: what is the goal of a manipulation system, is the anthropomorphic or functional design methodology appropriate, and to what degree does the control of the manipulator depend on other sensory systems. This paper examines the potential of creating a general purpose, anthropomorphically motivated, dextrous manipulation system. The discussion will focus on features of the human hand that permit its general usefulness as a manipulator. A survey of machinery designed to emulate these capabilities is presented. Finally, the tasks of grasping and manipulation are examined from the control standpoint to suggest a control paradigm which is descriptive, yet flexible and computationally efficient1

Tactile Perception And Visuotactile Integration For Robotic Exploration

As the close perceptual sibling of vision, the sense of touch has historically received less than deserved attention in both human psychology and robotics. In robotics, this may be attributed to at least two reasons. First, it suffers from the vicious cycle of immature sensor technology, which causes industry demand to be low, and then there is even less incentive to make existing sensors in research labs easy to manufacture and marketable. Second, the situation stems from a fear of making contact with the environment, avoided in every way so that visually perceived states do not change before a carefully estimated and ballistically executed physical interaction. Fortunately, the latter viewpoint is starting to change. Work in interactive perception and contact-rich manipulation are on the rise. Good reasons are steering the manipulation and locomotion communities’ attention towards deliberate physical interaction with the environment prior to, during, and after a task. We approach the problem of perception prior to manipulation, using the sense of touch, for the purpose of understanding the surroundings of an autonomous robot. The overwhelming majority of work in perception for manipulation is based on vision. While vision is a fast and global modality, it is insufficient as the sole modality, especially in environments where the ambient light or the objects therein do not lend themselves to vision, such as in darkness, smoky or dusty rooms in search and rescue, underwater, transparent and reflective objects, and retrieving items inside a bag. Even in normal lighting conditions, during a manipulation task, the target object and fingers are usually occluded from view by the gripper. Moreover, vision-based grasp planners, typically trained in simulation, often make errors that cannot be foreseen until contact. As a step towards addressing these problems, we present first a global shape-based feature descriptor for object recognition using non-prehensile tactile probing alone. Then, we investigate in making the tactile modality, local and slow by nature, more efficient for the task by predicting the most cost-effective moves using active exploration. To combine the local and physical advantages of touch and the fast and global advantages of vision, we propose and evaluate a learning-based method for visuotactile integration for grasping

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility

Spatial-Temporal Characteristics of Multisensory Integration

abstract: We experience spatial separation and temporal asynchrony between visual and haptic information in many virtual-reality, augmented-reality, or teleoperation systems. Three studies were conducted to examine the spatial and temporal characteristic of multisensory integration. Participants interacted with virtual springs using both visual and haptic senses, and their perception of stiffness and ability to differentiate stiffness were measured. The results revealed that a constant visual delay increased the perceived stiffness, while a variable visual delay made participants depend more on the haptic sensations in stiffness perception. We also found that participants judged stiffness stiffer when they interact with virtual springs at faster speeds, and interaction speed was positively correlated with stiffness overestimation. In addition, it has been found that participants could learn an association between visual and haptic inputs despite the fact that they were spatially separated, resulting in the improvement of typing performance. These results show the limitations of Maximum-Likelihood Estimation model, suggesting that a Bayesian inference model should be used.Dissertation/ThesisDoctoral Dissertation Human Systems Engineering 201