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We create a new tactile recording system with which we develop a three-axis fingernail-color sensor that can measure a three-dimensional force applied to fingertips by observing the change of the fingernail’s color. Since the color change is complicated, the relationships between images and three-dimensional forces were assessed using convolution neural network (CNN) models. The success of this method depends on the input data size because the CNN model learning requires big data. Thus, to efficiently obtain big data, we developed a novel measuring device, which was composed of an electronic scale and a load cell, to obtain fingernail images with 0 $^\circ$ to 360 $^\circ$ directional tangential force. We performed a series of evaluation experiments to obtain movies of the color changes caused by the three-axis forces and created a data set for the CNN models by transforming the movies to still images. Although we produced a generalized CNN model that can evaluate the images of any person’s fingernails, its root means square error (RMSE) exceeded both the whole and individual models, and the individual models showed the smallest RMSE. Therefore, we adopted the individual models, which precisely evaluated the tangential-force direction of the test data in an $F_x$ - $F_y$ plane within around $\pm$ 2.5 $^\circ$ error at the peak points of the applied force. Although the fingernail-color sensor possessed almost the same level of accuracy as previous sensors for normal-force tests, the present fingernail-color sensor acts as the best tangential sensor because the RMSE obtained from tangential-force tests was around 1/3 that of previous studies.

Due to increasing demand for rehabilitation and therapy for cerebrovascular diseases, patients require advanced development of medical rehabilitation robots. In our laboratory, we focus on the formation capability of the substitute neural path caused by brain plasticity using the kinesthetic illusion (KI), which is effective for therapies using robots. In KI, people perceive an illusionary limb movement without an actual movement when a vibration stimulus is applied to a limb’s tendons. In previous research, the optimal frequency that induces the maximum KI has a correlation factor of about 0.5 with the tendon’s natural frequency when a human subject is in a state of laxity. However, we do not know whether the above finding can be applied to actual rehabilitation because muscles and tendons are sometimes in tonus during rehabilitation, a state that varies the natural frequency. In this study, we investigate the correlation between the optimal and natural frequencies of tendon by systematically changing their tension to clarify the effects on the illusion induced by the muscle and the tendon when they are in tonus. We identified a negative correlation between the optimal and natural frequencies when they are in tonus, although a positive correlation appeared when they are in laxity. This result suggests that KI’s optimal frequency should be changed based on the degree of the tendon and muscle tonus. Therefore, our present findings provide a suitable vibration frequency that induces KI due to the degree of the tendon and muscle tonus during robot therapies.

Movement of a grid of bars between the two hands creates the tactile illusion of a velvet-like material, namely, the velvet hand illusion (VHI). It was recently proposed that the VHI is caused by a masking effect; bar movement suppresses conscious perception of tactile inputs from the opposing hand. If this hypothesis sufficiently explains the VHI, the physical properties of the opposing hand should not affect the illusion. Another hypothesis suggests that the integration of inputs from the grid of bars and the hands plays a critical role in the VHI. To compare these two hypotheses, the VHI was elicited under two conditions; the grid of bars was between one hand and a soft texture or the grid of bars was between one hand and a hard texture. A hand was stimulated by moving bars while contacting the stationary texture held by the opposing hand. The grid of bars with the soft texture induced a stronger illusion and softer feeling than that with the hard texture. This result supports the integration hypothesis in which tactile inputs from both bars and textures attached to the opposing hand are integrated. Accepted version

The computer vision for binocular eyes system has many applications in robot applications and safety purposes. Based on the previous research, the combination of the area of sight of stereo vision will trigger the trigonometry intersection point for determine the distance of the objects from it baseline. The system programme codes is one of the issue need to confront consequent since there are various sorts of calculation that are in the same field, however has unmistakable of use. This project focuses on how to measure distances using binocular vision. The main objective is to evaluate the binocular vision system by calculating the distance of objects in real environment. Furthermore, the project proposes a new program algorithm for binocular vision system to work, in order to identify distance of an object with a basic equation has been derived and set in the designed algorithm. The setting environment are set to single and multi-objects measured, object in environment and changes of degree of bright light. Evaluation of the system shows the detected distances are consistence and the data were recorded. The value of the distances detected are then compared with the real environment distances. The result show distances measured moderate enough for proposed system to function and may facilitate improvements in computer vision system for industry.

VHI (Velvet Hand Illusion) is an illusion phenomenon to make someone feel a smooth sensation like velvet fabric and it is expected to be applied to haptic devices. To achieve this goal, it is very important to elucidate the mechanism of VHI. In this research, we investigate whether the brain activation related to VHI can be measured with NIRS. As a result, it is confirmed that the right middle frontal gyrus plays an important role in illusion occurrence which is same as the previous fMRI research.

To develop devices of neurorehabilitation for the stroke patients, we focus on the Kinesthetic Illusion (KI), which is a proprioceptive illusion phenomena. In KI, we feel the joint movement sensation without actual movement, when the vibrating stimulation is applied to a specific tendon. In KI research, it is very important to clarify the optimal condition to induce the stronger illusion, which has not yet been clarified. In this study, we try to clarify the optimal condition for inducing KI from the view point of vibration engineering. This result will contribute toward development of a new mechatronics system inducing KI. In order to the abovementioned investigation, we assume that there is an important relationship between a natural frequency of the specific tendon and the optimal frequency for KI. We focus on the tendon of the Flexor Carpi Radialis muscle (FCR) which is related to the wrist joint movement in the extended direction and conduct a series of psychophysical experiments. As a result, a correlation of R = 0.50 is found between the optimal frequency for KI and a natural frequency of the tendon. This result demonstrates that the joint moving sensation of limbs can be controlled through a basic vibrating stimulation to induce KI by means of applying the natural frequency of the specific tendon.

Smoothness is one of the important factors in controlling texture sensation in tactile VR. In previous research, the authors utilized Velvet Hand Illusion (VHI), which is a tactile illusion phenomena, to generate a smooth texture on a dot-matrix display. Since the dot-matrix display can generate arbitrary figures, we are attempting to evaluate our new hypothesis of the VHI mechanism using this display. In our hypothesis, a cognitive mechanism called Gestalt grouping [3] is related to VHI occurrence. If tactile Gestalt were elucidated, we could understand the tactile sensation mechanism deeply and the various devices would be developed in the VR research field. In this paper, we investigate the relationship between tactile Gestalt and VHI through psychophysical experiments. In these experiments, the appearance intensity of tactile Gestalt is controlled by means of density and length of the lines formed on the dot-matrix display. It is concluded that the law of closure stated in the principle of Pragnanz is an essential condition related to tactile Gestalt to generate VHI.

Time-evolving tactile sensations are important in communication between animals as well as humans. In recent years, this research area has been defined as “tactileology,” and various studies have been conducted. This study utilized the tactile Gestalt theory to investigate these sensations. Since humans recognize shapes with their visual sense and melodies with their auditory sense based on the Prägnanz principle in the Gestalt theory, this study assumed that a time-evolving texture sensation is induced by a tactile Gestalt. Therefore, the operation of such a tactile Gestalt was investigated. Two psychophysical experiments were conducted to clarify the operation of a tactile Gestalt using a tactile illusion phenomenon called the velvet hand illusion (VHI). It was confirmed that the VHI is induced in a tactile Gestalt when the laws of closure and common fate are satisfied. Furthermore, it was clarified that the tactile Gestalt could be formulated using the proposed factors, which included the laws of elasticity and translation, and it had the same properties as a visual Gestalt. For example, the strongest Gestalt factor had the highest priority among multiple competing factors.

A tactile record and playback system will progress tactileology—a new cross-disciplinary field related to tactile sensations—as it will enhance its use in the instruction, archiving, and analysis of human manipulation. In this paper, we describe two key devices for achieving tactileology: a tactile sensor capturing human tactile sense (fingernail color sensor) and a robotic tactile sensor, both of which can detect not only normal force but also tangential force. This is beneficial because people manipulate objects and tools in various ways, such as grasping, picking, and rubbing. The fingernail color sensor registers the three-dimensional (3D) force applied to a fingertip by detecting the fingernail color change caused by blood distribution under the fingernail, which can be observed with green illumination and a miniature camera. Since detecting this color change is more complicated than using a robotic sensor, the relationships between the image and 3D force are learned using a convolutional neural network (CNN). In the robotic sensor, the 3D force applied to a robotic finger transforms into a bright area using an illuminated acrylic core, a rubber robotic finger skin, and a miniature camera. We measure normal force and tangential force by the brightness and movement of the bright area, respectively. Using a force gauge or an electronic scale for measurement, we perform a series of evaluation experiments. The experimental results show that the precision of both the fingernail color sensor and the robotic tactile sensor are sufficient for our system.

In advanced missions, handling thin and soft membranes is difficult for robots. This task is composed of several sub-tasks, including turning and removing a sheet from a pile of papers on a table, folding paper, and sticking two pieces of paper together. In this study, a hand robot turns and removes a sheet from a pile of papers, and ensures that only one sheet is grasped. To perform this task, two robotic fingers compress the piled papers in the normal direction of the table with a specific force as they close. We therefore incorporated position-based force control into our system; for the force controller, we adopted stiffness control that calculates position modification proportionally to the difference between the target force and an external force measured by the tactile sensor. With this controller, the robot was able to remove a sheet from a pile of papers and ensure that only one sheet was removed. Using this discrimination, the maximum-minimum shearing forces are better classified than with normal force distribution deviation.

Stress-free interaction between humans and robots is necessary to support humans in daily life. In order to achieve this, we anticipate the development of new robots equipped with tactile and vision sensors for receiving human instructions. In this article, we focus on spontaneous movements that do not require training, such as pointing and force adjustment and that are suitable for daily care. These movements, which we call natural instructions, involve the transmission of human instructions to robots. In this experiment, we examine a robot equipped with vision and tactile sensors capable of receiving natural instructions. Our new robot accomplishes a retrieving and passing task using the natural instructions of finger pointing and tapping with the palm.

In this research, as a different approach to the conventional one which enhances the performance with hardware of a haptic device, we adopt another approach to make the brain feel as if the person is touching the real thing via an illusion. Thus, we study Velvet Hand Illusion (VHI) which is an illusionary phenomenon concerning tactile touch. In VHI, a hexagonal wire mesh is sandwiched between both hands and rubbing the wire mesh without relative motion between both hands generates a smooth feeling, like velvet. The brain activation at this time is measured by PocketNIRS, which contains two channels measuring the bilateral prefrontal cortex. We obtained the result that the prefrontal cortex was activated to roughly two times larger when VHI occurred than when touching real velvet fabric. Since different responses can be obtained in the prefrontal cortex during brain activation between real velvet and VHI, it is possible to use pocketNIRS for the evaluation of VHI.

To enhance the reality of touch feeling in VR, one effective presentation is the texture sensation of a virtual object. Although the texture sensation makes persons perceive a virtual object to be a real one, research on texture sensation has not always progressed due to the difficulty of developing a stimulus presentation device. To compensate for this hardware problem, we focus on the Velvet Hand Illusion (VHI), which is one of the tactile illusion phenomena, as a method of presenting texture sensation. In our previous study, VHI was generated by a tactile display using a refreshable braille display (dot-matrix display). Since the dot-matrix display can provide various dot patterns through combinations of stimulus-pin protrusions, it can be applied to clarify the essential stimulus conditions for VHI through a series of psychophysical experiments. We expect to obtain the essential conditions for VHI, which will then become the fundamentals of the VHI model. In the psychophysical experiments, two parallel lines formed by the dot-matrix display were reciprocated on the subject's palm. First, we investigated the relationship between the interval of pins forming lines and the VHI strength. Second, we investigated the relationship between the length of two parallel lines and the strength of VHI. As a result, VHI hardly occurred when the interval between pins forming lines was more than a two-point threshold. Consequently, it was clarified that the sensation of touching a line is an essential condition for VHI and that line length of 29 mm is the absolute threshold of VHI.

Since a robotic hand equipped with three-axis tactile sensors can detect not only grasped force caused by pinching motion but also slippage generated by sliding fingers, it can be applied to various tasks such as cap twisting, exploring object shape and detecting hardness. Although thin sheet handling is considered one of the more difficult tasks in robotics because of object flexibility and thinness, the versatility of the hand seems to accomplish this task. In this paper, we evaluate the sensing ability of this sheet thickness to obtain basic data for handling and turning thin flexible sheets. In this experiment, we used 1,000-yen bills as specimens because they have precise and stable size and mechanical properties. Experimental results showed that the robotic hand could not distinguish sheet numbers through a pinching grip causing normal force but could distinguish them through sliding fingers causing tangential force.

In a previous study, we developed an all-in-type optical three-axis tactile sensor to address two issues: the first is to be able to use external devices such as a CCD camera and light source; the other is the insensible zone. We miniaturized its whole structure through adoption of a CMOS board camera equipped with LEDs. Since a USB is installed in the CMOS camera as an interface, an additional image processing board is not required. Furthermore, it is equipped with a rubber dome including a sensing element array to remove the insensible zone because rubber is filled in between the sensing elements. However, even if it accepted under around 1-N force, no output of brightness appeared. In this paper, we enhance the characteristic in the low level applied force through improvement of image processing. Furthermore, the present sensor showed higher output level of normal and tangential forces through a series of experiments comparing the present and ordinal three-axis tactile sensors.

If the theory of affordance is applied to a robot, performing the whole process of recognition and planning is not always required in its computer. Since the tactile sensing of a robot is important to perform any task, we focus on tactile sensing and introduce a new concept called the artificial tactile affordance system (ATAS). Its basic idea is the implementation of a recurrent mechanism in which information obtained from the object and the behavior performed by the robot's inducing the next behavior. We intend to implement ATAS based on the following two methodologies: (1) after each rule is transformed into an algorithm, a program module is coded based on the algorithm; ATAS is composed of several program modules, and a module is selected from the set of modules based on sensor information; (2) a set of rules is expressed as a table composed of sensor input columns and behavior output columns, and the table rows correspond to rules; since each rule is transformed to a string of 0 and 1, we treat a long string composed of rule strings as a gene to obtain an optimum gene that adapts to its environment using a genetic algorithm (GA). For methodology 1, we established an ATAS composed of 3 to 5 modules to accomplish such tasks as object grasping, pick and place, cap screwing, and assembling. Using methodology 1, a two-hand-arm robot equipped with an optical three- axis tactile sensor performed the above tasks. For methodology 2, we propose the Evolutionary Behavior Table System (EBTS) that uses a GA to acquire the autonomous cooperation behavior of multiple mobile robots. In validation experiments, three agents equipped with behavior tables conveyed an object to a specified goal with higher scores than the four-agent condition. Since the redundant agent does not interrupt the other agents, the agent acquires the collective behavior of not interrupting other agents based on its environment information. Methodology 1 is very effective for such fine control as handling tasks of humanoid robots, and methodology 2 is very useful to obtain general robotic behavior that is suitable for the environment.

In the velvet hand illusion (VHI), a person rubs his/her hands together on either side of wires strung through a frame, producing the sensation of rubbing a very smooth and soft surface like velvet. We investigate the VHI mechanism to obtain an effective hint for a new tactile display because such tactile illusions play a good role in deceiving the brain so that operators believe that a virtual sensation is real. To elucidate the VHI mechanism, we propose two approaches: one uses psychophysics to obtain human mental models; the other is a finite element method (FEM) to evaluate the tactile stimulus that causes VHI. Based on psychophysical experiments using Thurstone's Paired Comparison, VHI strength depends on the distance between two adjacent wires, and VHI caused by wide spacing of wires is considerably stronger than that caused by narrow spacing. In FEM analysis, a mesh model of fingertips is produced to mimic an actual finger to evaluate the strain energy density (SED) because one mechanoreceptive unit is a slowly adaptive mechanoreceptive type I unit (SAI) that well responds to SED. There is a considerable difference between the SEDs of the one-finger case and the two-finger case (VHI case): the peak SED value for the VHI case is around half of that for the one-finger case. The VHI mechanism is assumed as follows: although the area bounded by two wires moves relative to the hands, tangential force does not occur on the hand surface except for the wire-passing portion, causing operators to experience the illusion of touching a smooth virtual film with a zero coefficient of friction. Since VHI decreases with a decrease of wire spacing and an increase of the peak value of SED, excessive temporal stimulus generated by wire prevents VHI from increasing.

We develop a new rehabilitation device that combines the effects of two illusions: the kinesthetic illusion (KI) and the rubber hand illusion (RHI). We investigate whether KI can be reinforced with RHI where the former is caused by applying the oscillator's vibration to the flexor carpi radialis muscle (FCR) of a right hand. RHI is caused by showing moving images of a right hand overlapped on the subject's hand through a display pad. The illusion's vividness is induced in the right hand was represented by the left hand and measured by a rotary encoder, which can measure the joint angle of the flexion and the extension motion of the right wrist. We conducted experiments that quantitatively compared the KI strength that was reinforced by the visual stimulus with the pure KI strength, where the enhanced KI strength was about 1.4 to 1.5 times stronger than the unenhanced KI.

In human-and-robot cooperative tasks, a robot must estimate human intentions. For example, if we want a gadget from another person, we naturally and casually point at it with our index finger. In this paper, we develop an object detection system through finger pointing using a stereo vision sensor to apply the above simple gesture to human-and-robot cooperative tasks. In this system, the robot calculates the pointing direction to detect the object indicated by the fingertip based on image processing of the pointing finger. We improved our algorithm to enhance its accuracy using two methods. One uses the convex hull to solve the problem that determination of the fingertip candidates depends on the contour condition; the other calculates the movement amount of the pointed object's center. Our evaluation test shows that the former method enables our system to detect the fingertips in all the frames, and the latter method can identify whether the human is intentionally pointing at the object.

Future robots will require the ability to handle flexible objects for home use, medical use, and further industrial use. In this work, we study the function of a robotic hand-arm equipped with three-axis tactile sensors: the difficult capability to handle such material as flexible membranes and cables. First, an experiment shows how the robot hand can distinguish whether the slid object is just 1 sheet or more than 2 using two fingers, each of which is loaded with tactile sensors. Second, it shows the prospect of new handling methods for flexible objects by turning over paper sheets with the same robot hand and sensor.

We developed a tactile mouse that presents convex dot-patterns on a human palm to obtain the design parameters of haptic devices for virtual reality (VR). In a tactile VR study, we focused on the following issue, “which tactile perception is superior, active or passive touch?”, because it is related to the design of haptic devices that can present detailed information in tactile VR. This study evaluates the differences in perception precision between active and passive touch to clarify the best presentation method in VR through a series of psychophysical experiments using a tactile mouse. Since the presentation precision of virtual figures depends on the sharpness of the edges generated by dot-patterns, our experiment subjects evaluate the slope of the oblique edges. In a psychophysical experiment, two oblique edges of dot-patterns are presented consecutively and subjects compare them to determine which is larger. We evaluate the perception precision using the difference threshold of the edge angles calculated by the simplified constant stimuli method. Experimental results show that the perception precision at low speed (45 and 90 mm/s) of edge movement is better than at high speed (130 and 170 mm/s) and also that there is no significant difference between active and passive touching.

The optical three-axis tactile sensor has attractive characteristics such as three-axis force distribution measurement, resilience against impact force, and flexible contact. In this paper, we demonstrate the usefulness of this tactile sensor in humanrobot collaboration and communication through a simple assembly task. In the task, we include two new skills that cannot be performed without three-axis tactile sensors: one of them is loose grip status; the other is to use an object grasped by a hand as a sensor. To accomplish these skills, we perform a series of basic experiments: one of them is the loose grip test, in which a hand-arm robot grasps a stick horizontally and then releases its grasping force to make the stick attitude vertical; the other is hole search tests, in which the hand-arm robot grasps a stick like a cane to search for a hole on a plate by sliding the stick on the plate and evaluating variation in moment measured by the tactile sensor. In the verification, the hand-arm robot assembles an arch composed of two columns, a top beam and a base through triaxial data obtained from the three-axis tactile sensor.

Although several actuator principles for tactile displays composed of many micro-actuators exist, current actuators do not produce sufficient stroke and force generation. In order to compensate their shortage ability, we developed a new pin-matrix tactile display in which pin-protrusion distribution synchronizes pitch and roll moments applied to the display. In the present study, we evaluated the versatility of a virtual tilt pad presentation that is a progression from our previous study. In the tilt pad presentation, the rotations around the x -axis and y -axis are managed by the centroid position of the operator's fingers. In the evaluation, the subjects tried to compare the size of two virtual spheres to evaluate the 3D-shape presentation capability of the display. Since the sensation thresholds for each subject were low enough, we proved that operators could appreciate a fine distinction of sphere radii generated by the proposed display. In the case of a relatively large sphere, which is the most difficult case because it has the smallest curvature, the discrimination tasks improved with slight tapping as compared to pressing and rubbing with the fingers. Consequently, the manner of presentation can compensate the shortage ability of micro-actuators.

This paper presents experimental results of object handling motions to evaluate tactile slippage sensation in a multi fingered robot arm with optical three-axis tactile sensors installed on its two hands. The optical three-axis tactile sensor is a type of tactile sensor capable of defining normal and shear forces simultaneously. Shear force distribution is used to define slippage sensation in the robot hand system. Based on tactile slippage analysis, a new control algorithm was proposed. To improve performance during object handling motions, analysis of slippage direction is conducted. The control algorithm is classified into two phases: grasp-move-release and grasp-twist motions. Detailed explanations of the control algorithm based on the existing robot arm control system are presented. The experiment is conducted using a bottle cap, and the results reveal good performance of the proposed control algorithm to accomplish the proposed object handling motions.

Stochastic Resonance (SR) is a significant concern for design of robotic tactile sensors because of its considerable enhancement of sensitivity of human tactile sensation. In the last few decades, researchers have found that noise previously considered detrimental in fact provides the benefit of SR phenomena. However, there are no experimental results for dependence on vibrotactile frequency, which issued as basic data for robotic tactile sensors. In this paper, we investigated the influence of the SR phenomena on human tactile sensation in the context of frequency-dependence of absolute thresholds (AT). We developed a system composed of an experimental apparatus and a computer program based on psychophysics in order to measure the AT of human vibrotactile sensation. We performed three series of psychophysical experiments using normal vibration, 8-mm-sized stimulus point and the continuous sinusoidal signals of 32, 50 and 75 Hz to obtain the AT variation in frequency. The results show that since normal ATs decrease with appropriate noise, SR is observed in normal stimuli tests in the frequency range from 32 to 70 Hz. Since the inclination of the curve of AT in a double logarithmic graph is around -1 in both with-noise and without-noise conditions, SR is caused by the FA-I mechanoreceptive unit in the range of frequency.

Tactile illusions as a practical method in virtual reality allow us to induce a real feeling of an object's properties such as shape or texture although the object not physically exists. The moving wires between two hands induce a velvet-like sensation to hands called Velvet Hand Illusion (VHI). We have proposed that VHI can be used in a tactile display in virtual reality. In order to examine this, first, it was mandatory to be revealed physical parameters which might be the effect on the strength of VHI. We investigated effects of distance (D), stroke (r) and velocity (V) of wires on the intensity of VHI by conducting the psychophysical experiments. In accordance with the experimental results, we could propose a psychophysiological model based on the mechanoreceptors afferent units for VHI including type one of slow and fast adaptive mechanoreceptive units (SAI and FAI). In the end, we examined quality and intensity of VHI to be produced by a tactile display in compared with VHI-based two wires. This result indicated that VHI can produce by tactile display so that a person to interpret velvet-like texture in his/her hand.

This paper presents application of a new tactile slippage sensation algorithm in robot hand control system. The optical three-axis tactile sensor is a type of tactile sensor capable of defining normal and shear forces simultaneously. The tactile sensor is mounted on fingertip of robotic hand. Shear force distribution is used to define slippage sensation in the robot hand system. Based on tactile slippage analysis, a new control algorithm was proposed. To improve performance during object handling motions, analysis of slippage direction is conducted. The control algorithm is classified into two phases: grasp-move-release and grasp-twist motions. Detailed explanations of the control algorithm based on the existing robot arm control system are presented. The experiment is conducted using a bottle cap, and the results reveal good performance of the proposed control algorithm to accomplish the proposed object handling motions.

In the present research, we have investigated several characteristics of one kind of tactile illusion, called the Velvet Hand Illusion (VHI), to utilize the experimental results to generate virtual feeling of a material. In VHI, a human subject gently rubs his/her hands on both sides of a wire grid strung through a frame. The sensation produced on his/her hands is very smooth and slippery, like velvet. We focused on the VHI mechanism for new tactile displays in the virtual reality field because such tactile illusions play a useful role in deceiving the brain so that operators believe a virtual sensation is real. VHI characteristics are obtained from accomplishing a series of psychophysical experiments using Thurstone’s method of paired comparison. In the experiment, the stroke movement distance of wires, r, is varied under constant wire spacing, D; the velocity of wire movement is varied, with both wire spacing and stroke movement distance of the wires held constant. It is found that the strongest VHI was obtained at r/D≅1 and that the strongest VHI occurred at a specific velocity generating tangential vibration of around 50 Hz. Since VHI requires both compressive stress and tangential stimulus, it is caused by not just one of the four varieties of mechanoreceptive units, but two or more of them. This finding confirms that VHI does not occur in the mechanoreceptive units themselves but in the brain.