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When grasping objects, humans actively adjust grip force in response to surface slipperiness and motion. Previous studies have showed that corrective actions occur after tactile afferents signal surface friction or slip events. However, the influence of the mechanical behavior of the skin on the development of contact forces is poorly understood. In this study, using contact kinematics derived from a natural reach-and-grasp task, we applied a glass surface onto restrained fingers via a robotic manipulator under low- and high-friction conditions. Contact forces were measured with a force sensor, and skin deformations were captured using a high-speed camera. As expected, the normal force remained unaffected by friction, however, interestingly the tangential force rose more slowly and peaked lower under low friction. This resulted in a higher normal-to-tangential force ratio, resembling friction-dependent scaling of grip-to-load force ratio observed in active grasping. The skin partially slipped throughout contact development, with the proportion of the slipped area first decreasing and then increasing. The time course of tangential force correlated with the extent of skin slip, both varying with friction. The findings demonstrate that skin mechanics potentially influences the grip stabilization during the initial phase of object handling, which doesn’t involve feedback-driven grip force adjustments.

STRAS (Single access Transluminal Robotic Assistant for Surgeons) is a new robotic system based on the Anubis® platform of Karl Storz for application to intra-luminal surgical procedures. Pre-clinical testing of STRAS has recently permitted to demonstrate major advantages of the system in comparison with classic procedures. Benchmark methods permitting to establish objective criteria for ‘expertise’ need to be worked out now to effectively train surgeons on this new system in the near future. STRAS consists of three cable-driven sub-systems, one endoscope serving as guide, and two flexible instruments. The flexible instruments have three degrees of freedom and can be teleoperated by a single user via two specially designed master interfaces. In this study, small force sensors sewn into a wearable glove to ergonomically fit the master handles of the robotic system were employed for monitoring the forces applied by an expert and a trainee (complete novice) during all the steps of surgical task execution in a simulator task (4-step-pick-and-drop). Analysis of grip-force profiles is performed sensor by sensor to bring to the fore specific differences in handgrip force profiles in specific sensor locations on anatomically relevant parts of the fingers and hand controlling the master/slave system.

Hand exoskeletons are potential solutions for enhancing upper extremity function after stroke, yet achieving intuitive control remains challenging. We recently showed that isometric grip force tracking is preserved after stroke, providing a possible control source for a hand exoskeleton. In this study, we developed a hand exoskeleton with a soft compliant mechanism and novel force control strategy that leverages isometric grip force control of digits 3–5 to control an index–thumb pinch grip. We first present characterization of the compliant mechanisms output impedance (34.77 N/m), and output force (2.3 ± 0.57 N). We then present results of a study that assessed the intuitiveness of the strategy during a grip–lift–move task in ten unimpaired individuals. From four unimpaired individuals we also gathered user preferences on force sensitivity and operating mode, where in one mode flexion force from digits 3–5 caused index finger closing, while in the other mode it caused index finger opening. The strategy proved intuitive, improving movement frequency on the grip–lift–move task by 30%. Users preferred greater force sensitivity and using flexion force from digits 3–5 to drive index finger extension. The force control strategy incorporated into the exoskeleton shows promise warranting further investigation in neurologically impaired participants.

When manipulating objects, we use kinesthetic and tactile information to form an internal representation of their mechanical properties for cognitive perception and for preventing their slippage using predictive control of grip force. A major challenge in understanding the dissociable contributions of tactile and kinesthetic information to perception and action is the natural coupling between them. Unlike previous studies that addressed this question either by focusing on impaired sensory processing in patients or using local anesthesia, we used a behavioral study with a programmable mechatronic device that stretches the skin of the fingertips to address this issue in the intact sensorimotor system. We found that artificial skin-stretch increases the predictive grip force modulation in anticipation of the load force. Moreover, the stretch causes an immediate illusion of touching a harder object that does not depend on the gradual development of the predictive modulation of grip force.

Background When exposed to a novel dynamic perturbation, participants adapt by changing their movements’ dynamics. This adaptation is achieved by constructing an internal representation of the perturbation, which allows for applying forces that compensate for the novel external conditions. To form an internal representation, the sensorimotor system gathers and integrates sensory inputs, including kinesthetic and tactile information about the external load. The relative contribution of the kinesthetic and tactile information in force-field adaptation is poorly understood. Methods In this study, we set out to establish the effect of augmented tactile information on adaptation to force-field. Two groups of participants received a velocity-dependent tangential skin deformation from a custom-built skin-stretch device together with a velocity-dependent force-field from a kinesthetic haptic device. One group experienced a skin deformation in the same direction of the force, and the other in the opposite direction. A third group received only the velocity-dependent force-field. Results We found that adding a skin deformation did not affect the kinematics of the movement during adaptation. However, participants who received skin deformation in the opposite direction adapted their manipulation forces faster and to a greater extent than those who received skin deformation in the same direction of the force. In addition, we found that skin deformation in the same direction to the force-field caused an increase in the applied grip-force per amount of load force, both in response and in anticipation of the stretch, compared to the other two groups. Conclusions Augmented tactile information affects the internal representations for the control of manipulation and grip forces, and these internal representations are likely updated via distinct mechanisms. We discuss the implications of these results for assistive and rehabilitation devices.

Previous studies (Haswell et al. in Nat Neurosci 12:970–972, 2009; Marko et al. in Brain J Neurol 138:784–797, 2015) reported that people with autism rely less on vision for learning to reach in a force field. This suggested a possibility that they have difficulties in extracting force information from visual motion signals, a process called inverse dynamics computation. Our recent study (Takamuku et al. in J Int Soc Autism Res 11:1062–1075, 2018) examined the ability of inverse computation with two perceptual tasks and found similar performances in typical and autistic adults. However, this tested the computation only in the context of sensory perception while it was possible that the suspected disability is specific to the motor domain. Here, in order to address the concern, we tested the use of inverse dynamics computation in the context of motor control by measuring changes in grip timing caused by seeing/not seeing a controlled object. The motion of the object was informative of its inertial force and typical participants improved their grip timing based on the visual feedback. Our interest was on whether the autism participants show the same improvement. While some autism participants showed atypical hand slowing when seeing the controlled object, we found no evidence of abnormalities in the inverse computation in our grip timing task or in a replication of the perceptual task. This suggests that the ability of inverse dynamics computation is preserved not only for sensory perception but also for motor control in adults with autism.

Purpose Chemotherapy-induced peripheral neuropathy (CIPN) commonly involves hand dexterity impairment. However, the factors affecting hand dexterity impairment are unknown and there is currently no established treatment. The purpose of the current study was to clarify factors influencing hand dexterity impairment in taxane-induced peripheral neuropathy using subjective and objective assessments. Methods We assessed patient characteristics, treatment-related factors, subjective symptoms of CIPN (Patient Neurotoxicity Questionnaire [PNQ]), psychological symptoms, and upper limb dysfunction (Quick Disabilities of the Arm, Shoulder and Hand [Quick DASH]). Quantitative assessments were pinch strength, sensory threshold, hand dexterity impairment, and grip force control. Multiple regression analysis was performed using hand dexterity impairment as the dependent variable and age and PNQ, Quick DASH, and control of grip force as independent variables. Results Forty-three breast cancer patients were included in the analysis. Hand dexterity impairment in taxane-induced peripheral neuropathy patients was significantly correlated with age, grip force control, and PNQ sensory scores ( p  < 0.008). Multiple regression analysis demonstrated that PNQ sensory scores and grip force control were significantly associated with hand dexterity impairment ( p  < 0.01). Conclusion Subjective symptoms (numbness and pain) and grip force control contributed to impaired hand dexterity in taxane-induced peripheral neuropathy.

The ability to finely control hand grip forces can be compromised by neuromuscular or musculoskeletal disorders. Therefore, it is recommended to include the training and assessment of grip force control in rehabilitation therapy. The benefits of robot-mediated therapy have been widely reported in the literature, and its combination with virtual reality and biofeedback can improve rehabilitation outcomes. However, the existing systems for hand rehabilitation do not allow both monitoring/training forces exerted by single fingers and providing biofeedback. This paper describes the development of a system for the assessment and recovery of grip force control. An exoskeleton for hand rehabilitation was instrumented to sense grip forces at the fingertips, and two operation modalities are proposed: (i) an active-assisted training to assist the user in reaching target force values and (ii) virtual reality games, in the form of tracking tasks, to train and assess the user’s grip force control. For the active-assisted modality, the control of the exoskeleton motors allowed generating additional grip force at the fingertips, confirming the feasibility of this modality. The developed virtual reality games were positively accepted by the volunteers and allowed evaluating the performance of healthy and pathological users.

During manipulation, object slipping is prevented by modulating the grip force (GF) in synchrony with motion-related inertial forces, i.e., load force (LF). However, due to conduction delays of the sensory system, GF must be modulated in advance based on predictions of LF changes. It has been proposed that such predictive force control relies on internal representations, i.e., internal models, of the relation between the dynamic of the environment and movement kinematics. Somatosensory and visual feedback play a primary role in building these internal representations. For instance, it has been shown that manipulation-dependent somatosensory signals contribute to building internal representations of gravity in normal and altered gravitational contexts. Furthermore, delaying the timing of visual feedback of object displacement has been shown to affect GF. Here, we explored whether and the extent to which spatial features of visual feedback movement, such as motion direction, may contribute to GF control. If this were the case, a spatial mismatch between actual (somatosensory) and visual feedback of object motion would elicit changes in GF modulation. We tested this hypothesis by asking participants to generate vertical object movements while visual feedback of object position was congruent (0° rotation) or incongruent (180° or 90°) with the actual object displacement. The role of vision on GF control was quantified by the temporal shift of grip force modulation as a function of visual feedback orientation and actual object motion direction. GF control was affected by visual feedback when this was incongruent in the vertical (180°), but not horizontal dimension. Importantly, 180° visual feedback rotation delayed and anticipated GF modulation during upward and downward actual movements, respectively. Our findings suggest that during manipulation, spatial features of visual feedback motion are used to predict upcoming LF changes. Furthermore, the present study provides evidence that internal model of gravity contributes to GF control by influencing sensory reweighting processes during object manipulation.

Background Training increases the functional use of an upper limb prosthesis, but little is known about how people learn to use their prosthesis. The aim of this study was to describe the changes in performance with an upper limb myoelectric prosthesis during practice. The results provide a basis to develop an evidence-based training program. Methods Thirty-one able-bodied participants took part in an experiment as well as thirty-one age- and gender-matched controls. Participants in the experimental condition, randomly assigned to one of four groups, practiced with a myoelectric simulator for five sessions in a two-weeks period. Group 1 practiced direct grasping, Group 2 practiced indirect grasping, Group 3 practiced fixating, and Group 4 practiced a combination of all three tasks. The Southampton Hand Assessment Procedure (SHAP) was assessed in a pretest, posttest, and two retention tests. Participants in the control condition performed SHAP two times, two weeks apart with no practice in between. Compressible objects were used in the grasping tasks. Changes in end-point kinematics, joint angles, and grip force control, the latter measured by magnitude of object compression, were examined. Results The experimental groups improved more on SHAP than the control group. Interestingly, the fixation group improved comparable to the other training groups on the SHAP. Improvement in global position of the prosthesis leveled off after three practice sessions, whereas learning to control grip force required more time. The indirect grasping group had the smallest object compression in the beginning and this did not change over time, whereas the direct grasping and the combination group had a decrease in compression over time. Moreover, the indirect grasping group had the smallest grasping time that did not vary over object rigidity, while for the other two groups the grasping time decreased with an increase in object rigidity. Conclusions A training program should spend more time on learning fine control aspects of the prosthetic hand during rehabilitation. Moreover, training should start with the indirect grasping task that has the best performance, which is probably due to the higher amount of useful information available from the sound hand.