Search

Grip force control during robotic in-hand manipulation is usually modeled as a monolithic task, where complex controllers consider the placement of all fingers and the contact states between each finger and the gripped object in order to compute the necessary forces to be applied by each finger. Such approaches normally rely on object and contact models and do not generalize well to novel manipulation tasks. Here, we propose a modular grip stabilization method based on a proposition that explains how humans achieve grasp stability. In this biomimetic approach, independent tactile grip stabilization controllers ensure that slip does not occur locally at the engaged robot fingers. Local slip is predicted from the tactile signals of each fingertip sensor i.e., BioTac and BioTac SP by Syntouch. We show that stable grasps emerge without any form of central communication when such independent controllers are engaged in the control of multi-digit robotic hands. The resulting grasps are resistant to external perturbations while ensuring stable grips on a wide variety of objects.

Human tactile afferents provide essential feedback for grasp stability during dexterous object manipulation. Interacting forces between an object and the fingers induce slip events that are thought to provide information about grasp stability. To gain insight into this phenomenon, we made a transparent surface slip against a fixed fingerpad while monitoring skin deformation at the contact. Using microneurography, we simultaneously recorded the activity of single tactile afferents innervating the fingertips. This unique combination allowed us to describe how afferents respond to slip events and to relate their responses to surface deformations taking place inside their receptive fields. We found that all afferents were sensitive to slip events, but fast-adapting type I (FA-I) afferents in particular faithfully encoded compressive strain rates resulting from those slips. Given the high density of FA-I afferents in fingerpads, they are well suited to detect incipient slips and to provide essential information for the control of grip force during manipulation.

Human tactile afferents provide essential feedback for grasp stability during dexterous object manipulation. Interacting forces between an object and the fingers induce slip events that are thought to provide information about grasp stability. To gain insight into this phenomenon, we made a transparent surface slip against a fixed fingerpad while monitoring skin deformation at the contact. Using microneurography, we simultaneously recorded the activity of single tactile afferents innervating the fingertips. This unique combination allowed us to describe how afferents respond to slip events and to relate their responses to surface deformations taking place inside their receptive fields. We found that all afferents were sensitive to slip events, but fast-adapting type I (FA-I) afferents in particular faithfully encoded compressive strain rates resulting from those slips. Given the high density of FA-I afferents in fingerpads, they are well suited to detect incipient slips and to provide essential information for the control of grip force during manipulation.

Human tactile afferents provide essential feedback for grasp stability during dexterous object manipulation. Interacting forces between an object and the fingers induce slip events that are thought to provide information about grasp stability. To gain insight into this phenomenon, we made a transparent surface slip against a fixed fingerpad while monitoring skin deformation at the contact. Using microneurography, we simultaneously recorded the activity of single tactile afferents innervating the fingertips. This unique combination allowed us to describe how afferents respond to slip events and to relate their responses to surface deformations taking place inside their receptive fields. We found that all afferents were sensitive to slip events, but FA-I afferents in particular faithfully encoded compressive strain rates resulting from those slips. Given the high density of FA-I afferents in fingerpads, they are well suited to detect incipient slips and to provide essential information for the control of grip force during manipulation.

Background International medical graduates need to show their proficiencies to obtain a medical license in a new country. In 2016 the Swedish National Board of Health and Welfare redesigned the proficiency test for Doctors of Medicine. The theoretical test consists of around 180 MCQ/SBA. All tests are made public after being used in accordance with the Swedish Public Access to Information and Secrecy Act. Thus, new tests have to be continuously developed. In addition, as a public institution, the test giver is required to reply to all challenges of the items on the test. Summary of Work To involve the stakeholders and to improve the quality of the test, the items and corresponding answer keys were made public immediately after the test was finished. The test takers were invited to challenge any item and correct answer via a web form and support challenge with literature references. The item authors then reviewed and replied to each individual challenge. Based on these challenges and the associated review, definitive answer keys were decided. Three weeks after test admission, the test takers received their results, a copy of their test together with correct answers, and the response to their challenges. Summary of Results So far, 13 different tests have been given to totally 2,328 test takers. 3,047 challenges were submitted and resulted in 87 changes in answer keys or deletions of an item from the test (3.7% of the 2,360 items across all 13 tests). The number of changes/deletions has decreased significantly with the number of developed tests. Discussion & Conclusion We consider the number of test items that have been rejected or adjusted answer keys to be low. Nevertheless, it was necessary to build a system where the challenges from the test takers were built into the test process. In the Swedish educational system appealing a grade is not possible, but if any item in a test is incorrect, the 1992 administrative law requires test givers to promptly adjust te

The study of dexterous manipulation has provided important insights into human sensorimotor control as well as inspiration for manipulation strategies in robotic hands. Previous work focused on experimental environment with restrictions. Here, we describe a method using the deformation and color distribution of the fingernail and its surrounding skin to estimate the fingertip forces, torques, and contact surface curvatures for various objects, including the shape and material of the contact surfaces and the weight of the objects. The proposed method circumvents limitations associated with sensorized objects, gloves, or fixed contact surface type. In addition, compared with previous single finger estimation in an experimental environment, we extend the approach to multiple finger force estimation, which can be used for applications such as human grasping analysis. Four algorithms are used, c.q., Gaussian process, convolutional neural networks, neural networks with fast dropout, and recurrent neural networks with fast dropout, to model a mapping from images to the corresponding labels. The results further show that the proposed method has high accuracy to predict force, torque, and contact surface., Article Number: PII S0263574719001383

Grip force control during robotic in-hand manipulation is usually modeled as a monolithic task, where complex controllers consider the placement of all fingers and the contact states between each finger and the gripped object in order to compute the necessary forces to be applied by each finger. Such approaches normally rely on object and contact models and do not generalize well to novel manipulation tasks. Here, we propose a modular grip stabilization method based on a proposition that explains how humans achieve grasp stability. In this biomimetic approach, independent tactile grip stabilization controllers ensure that slip does not occur locally at the engaged robot fingers. Local slip is predicted from the tactile signals of each fingertip sensor i.e., BioTac and BioTac SP by Syntouch. We show that stable grasps emerge without any form of central communication when such independent controllers are engaged in the control of multi-digit robotic hands. The resulting grasps are resistant to external perturbations while ensuring stable grips on a wide variety of objects.

Grip force control during robotic in-hand manipulation is usually modeled as a monolithic task, where complex controllers consider the placement of all fingers and the contact states between each finger and the gripped object in order to compute the necessary forces to be applied by each finger. Such approaches normally rely on object and contact models and do not generalize well to novel manipulation tasks. Here, we propose a modular grip stabilization method based on a proposition that explains how humans achieve grasp stability. In this biomimetic approach, independent tactile grip stabilization controllers ensure that slip does not occur locally at the engaged robot fingers. Local slip is predicted from the tactile signals of each fingertip sensor i.e., BioTac and BioTac SP by Syntouch. We show that stable grasps emerge without any form of central communication when such independent controllers are engaged in the control of multi-digit robotic hands. The resulting grasps are resistant to external perturbations while ensuring stable grips on a wide variety of objects.

Det är avgörande att det ställs samma höga krav på läkare från länder utanför EU som på svenskutbildade. Bilden av att det ställs olika krav på olika grupper vore förödande, skriver ansvariga för kunskapsprovet för läkare vid Umeå universitet ihop med Socialstyrelsen.

Understanding the neurophysiological signals underlying voluntary motor control and decoding them for controlling limb prostheses is one of the major challenges in applied neuroscience and rehabilitation engineering. While pattern recognition of continuous myoelectric (EMG) signals is arguably the most investigated approach for hand prosthesis control, its underlying assumption is poorly supported, i.e., that repeated muscular contractions produce consistent patterns of steady-state EMGs. In fact, it still remains to be shown that pattern recognition-based controllers allow natural control over multiple grasps in hand prosthesis outside well-controlled laboratory settings. Here, we propose an approach that relies on decoding the intended grasp from forearm EMG recordings associated with the onset of muscle contraction as opposed to the steady-state signals. Eight unimpaired individuals and two hand amputees performed four grasping movements with a variety of arm postures while EMG recordings subsequently processed to mimic signals picked up by conventional myoelectric sensors were obtained from their forearms and residual limbs, respectively. Off-line data analyses demonstrated the feasibility of the approach also with respect to the limb position effect. The sampling frequency and length of the classified EMG window that off-line resulted in optimal performance were applied to a controller of a research prosthesis worn by one hand amputee and proved functional in real-time when operated under realistic working conditions.

Human grasping and manipulation control critically depends on tactile feedback. Without this feedback, the ability for fine control of a prosthesis is limited in upper limb amputees. Although various approaches have been investigated in the past, at present there is no commercially available device able to restore tactile feedback in upper limb amputees. Based on the Discrete Event-driven Sensory feedback Control (DESC) policy we present a device able to deliver short-lasting vibrotactile feedback to transradial amputees using commercially available myoelectric hands. The device (DESC-glove) comprises sensorized thimbles to be placed on the prosthesis digits, a battery-powered electronic board, and vibrating units embedded in an arm-cuff being transiently activated when the prosthesis makes and breaks contact with objects. The consequences of using the DESC-glove were evaluated in a longitudinal study. Five transradial amputees were equipped with the device for onemonth at home. Through a simple test proposed here for the first time-the virtual eggs test-we demonstrate the effectiveness of the device for prosthetic control in daily life conditions. In the future the device could be easily exploited as an add-on to complement myoelectric prostheses or even embedded in prosthetic sockets to enhance their control by upper limb amputees.

The temporal evolution of surface strain, resulting from a combination of normal and tangential loading forces on the fingerpad, was calculated from high-resolution images. A customized robotic device loaded the fingertip with varying normal force, tangential direction and tangential speed. We observed strain waves that propagated from the periphery to the centre of the contact area. Consequently, different regions of the contact areawere subject to varying degrees of compression, stretch and shear. The spatial distribution of both the strains and the strain energy densities depended on the stimulus direction. Additionally, the strains varied with the normal force level and were substantial, e.g. peak strains of 50% with a normal force of 5 N, i.e. at force levels well within the range of common dexterous manipulation tasks. While these observations were consistent with some theoretical predictions from contact mechanics, we also observed substantial deviations as expected given the complex geometry and mechanics of fingertips. Specifically, from in-depth analyses, we conclude that some of these deviations depend on local fingerprint patterns. Our data provide useful information for models of tactile afferent responses and background for the design of novel haptic interfaces.

WAY-EEG-GAL is a dataset designed to allow critical tests of techniques to decode sensation, intention, and action from scalp EEG recordings in humans who perform a grasp-and-lift task. Twelve participants performed lifting series in which the object's weight (165, 330, or 660 g), surface friction (sandpaper, suede, or silk surface), or both, were changed unpredictably between trials, thus enforcing changes in fingertip force coordination. In each of a total of 3,936 trials, the participant was cued to reach for the object, grasp it with the thumb and index finger, lift it and hold it for a couple of seconds, put it back on the support surface, release it, and, lastly, to return the hand to a designated rest position. We recorded EEG (32 channels), EMG (five arm and hand muscles), the 3D position of both the hand and object, and force/torque at both contact plates. For each trial we provide 16 event times (e.g., 'object lift-off') and 18 measures that characterize the behaviour (e. g., 'peak grip force').

Reflex responses in jaw opening muscles can be evoked when a brittle object cracks between the teeth and suddenly unloads the jaw. We hypothesized that this reflex response is flexible and, as such, is modulated according to the instructed goal of biting through an object. Study participants performed two different biting tasks when holding a peanut-half stacked on a chocolate piece between their incisors. In one task, they were asked to split the peanut-half only (single-split task) and, in the other task, they were asked to split both the peanut and the chocolate in one action (double-split task). In both tasks, the peanut split evoked a jaw opening muscle response, quantified from EMG recordings of the digastric muscle in a window 20-60 ms following peanut split. Consistent with our hypothesis, we found that the jaw opening muscle response in the single-split trials was about twice the size of the jaw opening muscle response in the double-split trials. A linear model that predicted the jaw opening muscle response on a single trial basis indicated that task settings played a significant role in this modulation but also that the pre-split digastric muscle activity contributed to the modulation. These findings demonstrate that, like reflex responses to mechanical perturbations in limb muscles, reflex responses in jaw muscles not only show gain-scaling but also are modulated by subject intent.

Although splitting of food items between the incisors often requires high bite forces, rarely do the teeth harmfully collide when the jaw quickly closes after split. Previous studies indicate that the force-velocity relationship of the jaw closing muscles principally explains the prompt dissipation of jaw closing force. Here, we asked whether people could regulate the dissipation of jaw closing force during food splitting. We hypothesized that such regulation might be implemented via differential recruitment of masseter muscle portions situated along the anteroposterior axis because these portions will experience a different shortening velocity during jaw closure. Study participants performed two different tasks when holding a peanut-half stacked on a chocolate piece between their incisors. In one task, they were asked to split the peanut-half only (single-split trials) and, in the other, to split both the peanut and the chocolate in one action (double-split trials). In double-split trials following the peanut split, the intensity of the tooth impact on the chocolate piece was on average 2.5 times greater than in single-split trials, indicating a substantially greater loss of jaw closing force in the single-split trials. We conclude that control of jaw closing force dissipation following food splitting depends on task demands. Consistent with our hypothesis, converging neurophysiological and morphometric data indicated that this control involved a differential activation of the jaw closing masseter muscle along the anteroposterior axis. These latter findings suggest that the regulation of jaw closing force after sudden unloading of the jaw exploits masseter muscle compartmentalization.

Our sense of touch is essential in everyday life. It enables us to execute fast and accurate manipulations with our fingers. The loss of tactile sensations severely impairs these capabilities. Tactile information relies on thousands of sensors, called mechanoreceptors, distributed all over the skin surface. These mechanoreceptors act as transducers, i.e., they convert mechanical stresses into electrical signals that are transmitted to the central nervous system. The hands and fingers are the source of most tactile interactions and contain a high density of these sensors. To better understand how the tactile system works, it is crucial to understand the properties of the signals produced by the mechanoreceptors and to relate them to the mechanics taking place in the skin. In this thesis, methods were developed to measure the deformations of the fingertip skin during precisely controlled stimulations mimicking tactile interactions of everyday life. In a first part, vibrations resulting from the active exploration of textured surfaces with the fingertip were recorded in the forearm, showing that these vibrations travel along the hand and forearm and can be sensed far away from the contact point. In the second part, we described contact changes and strains taking place in the skin at the interface between the finger and the contact during the onset of a slip. These measurements provide an insight on the information available at the contact region during object manipulation. In the third part, we recorded fingertip afferent neuron responses to similar stimuli and showed a specific response of some neurons to the slips taking place in the contact area. In all three parts, our results provide useful information for the design of sensory prostheses and tactile displays., (FSA - Sciences de l) -- UCL, 2014

We demonstrate a simple approach with which finger force can be measured from nail coloration. By automatically extracting features from nail images of a finger-mounted CCD camera, we can directly relate these images to the force measured by a force-torque sensor. The method automatically corrects orientation and illumination differences. Using Gaussian processes, we can relate prepro-cessed images of the finger nail to measured force and torque of the finger, allowing us to predict the finger force at a level of 95%-98% accuracy at force ranges up to 10N, and torques around 90% accuracy, based on training data gathered in 90s. © 2013 IEEE.

Sensory information from tactile mechanoreceptors located in the glabrous skin of the hand is crucial for skillful object exploration and manipulation. These mechanoreceptors reliably encode the direction of fingertip forces, and the brain certainly relies on this information in both sensorimotor and cognitive tasks. In this study, we examined human ability to discriminate the direction of force stimuli applied to the volar surface of the index fingertip on the basis of tactile information only. We show that humans can discriminate three-dimensional (3D) force stimuli whose directions differ by an angle as small as 7.1 ° in the plane tangential to the skin surface. Moreover, we found that the discrimination ability was mainly affected by the time-varying phases of the stimulus, because adding a static plateau phase to the stimulus improved the discrimination threshold only to a limited extent.

Modern theories of motor control incorporate forward models that combine sensory information and motor commands to predict future sensory states. Such models circumvent unavoidable neural delays associated with on-line feedback control. Here we show that signals in human muscle spindle afferents during unconstrained wrist and finger movements predict future kinematic states of their parent muscle. Specifically, we show that the discharges of type Ia afferents are best correlated with the velocity of length changes in their parent muscles approximately 100-160 ms in the future and that their discharges vary depending on motor sequences in a way that cannot be explained by the state of their parent muscle alone. We therefore conclude that muscle spindles can act as "forward sensory models": they are affected both by the current state of their parent muscle and by efferent (fusimotor) control, and their discharges represent future kinematic states. If this conjecture is correct, then sensorimotor learning implies learning how to control not only the skeletal muscles but also the fusimotor system.

Tactile sensory feedback is essential for dexterous object manipulation. Users of hand myoelectric prostheses without tactile feedback must depend essentially on vision to control their device. Indeed, improved tactile feedback is one of their main priorities. Previous research has provided evidence that conveying tactile feedback can improve prostheses control, although additional effort is required to solve problems related to pattern recognition learning, unpleasant sensations, sensory adaptation, and low spatiotemporal resolution. Still, these studies have mainly focused on providing stimulation to hairy skin regions close to the amputation site, i.e., usually to the upper arm. Here, we explored the possibility to provide tactile feedback to the glabrous skin of toes, which have mechanical and neurophysiological properties similar to the fingertips. We explored this paradigm in a grasp-and-lift task, in which healthy participants controlled two opposing digits of a robotic hand by changing the spacing of their index finger and thumb. The normal forces applied by the robotic fingertips to a test object were fed back to the right big and second toe. We show that within a few lifting trials, all the participants incorporated the force feedback received by the foot in their sensorimotor control of the robotic hand.