Looking for Synergies in Healthy Upper Limb Motion: A Focus on the Wrist.

Recent studies on human upper limb motion highlighted the benefit of dimensionality reduction techniques to extrapolate informative joint patterns. These techniques can simplify the description of upper limb kinematics in physiological conditions, serving as a baseline for the objective assessment of movement alterations, or to be implemented in a robotic joint. However, the successful description of kinematic data requires a proper alignment of the acquisitions to correctly estimate kinematic patterns and their motion variability. Here, we propose a structured methodology to process and analyze upper limb kinematic data, considering time warping and task segmentation to register task execution on a common normalized completion time axis. Functional principal component analysis (fPCA) was used to extract patterns of motion of the wrist joint from the data collected by healthy participants performing activities of daily living. Our results suggest that wrist trajectories can be described as a linear combination of few functional principal components (fPCs). In fact, three fPCs explained more than 85% of the variance of any task. Wrist trajectories in the reaching phase of movement were highly correlated among participants and significantly more than trajectories in the manipulation phase ( [Formula: see text]). These findings may be useful in simplifying the control and design of robotic wrists, and could aid the development of therapies for the early detection of pathological conditions.

The relevance of signal timing in human-robot collaborative manipulation.

To achieve a seamless human-robot collaboration, it is crucial that robots express their intentions without perturbating or interrupting the task that a human partner is performing at that moment. Although it has not received much attention so far, this issue is important when robots assist humans in physical and manipulation tasks. The main question addressed here is whether there is a more appropriate time to inform a human partner that a robot is requesting to pass them an object. This question is posed in a reference scenario where human individuals are involved in a continuous pick-and-place task that cannot be interrupted. Our findings showed that providing a cue at the beginning of a reach-to-grasp movement could severely interfere with the ongoing human action, increasing the number of errors made by humans, slowing down and degrading the smoothness of their arm movement, and deflecting their gaze. These disruptive interferences strongly decreased, until they disappeared, when the robot provided the cue to the human partners shortly after the participants picked up an object, identifying this as the best signaling timing. The results of this work showed how the signaling timing may have a decisive influence on the performances of the human-robot teamwork and contribute to understanding the mechanisms underpinning the phenomenon of cognitive-motor interference in humans.

Optimal integration of intraneural somatosensory feedback with visual information: a single-case study.

Providing somatosensory feedback to amputees is a long-standing objective in prosthesis research. Recently, implantable neural interfaces have yielded promising results in this direction. There is now considerable evidence that the nervous system integrates redundant signals optimally, weighting each signal according to its reliability. One question of interest is whether artificial sensory feedback is combined with other sensory information in a natural manner. In this single-case study, we show that an amputee with a bidirectional prosthesis integrated artificial somatosensory feedback and blurred visual information in a statistically optimal fashion when estimating the size of a hand-held object. The patient controlled the opening and closing of the prosthetic hand through surface electromyography, and received intraneural stimulation proportional to the object's size in the ulnar nerve when closing the robotic hand on the object. The intraneural stimulation elicited a vibration sensation in the phantom hand that substituted the missing haptic feedback. This result indicates that sensory substitution based on intraneural feedback can be integrated with visual feedback and make way for a promising method to investigate multimodal integration processes.

On the choice of grasp type and location when handing over an object.

The human hand is capable of performing countless grasps and gestures that are the basis for social activities. However, which grasps contribute the most to the manipulation skills needed during collaborative tasks, and thus which grasps should be included in a robot companion, is still an open issue. Here, we investigated grasp choice and hand placement on objects during a handover when subsequent tasks are performed by the receiver and when in-hand and bimanual manipulation are not allowed. Our findings suggest that, in this scenario, human passers favor precision grasps during such handovers. Passers also tend to grasp the purposive part of objects and leave "handles" unobstructed to the receivers. Intuitively, this choice allows receivers to comfortably perform subsequent tasks with the objects. In practice, many factors contribute to a choice of grasp, e.g., object and task constraints. However, not all of these factors have had enough emphasis in the implementation of grasping by robots, particularly the constraints introduced by a task, which are critical to the success of a handover. Successful robotic grasping is important if robots are to help humans with tasks. We believe that the results of this work can benefit the wider robotics community, with applications ranging from industrial cooperative manipulation to household collaborative manipulation.

Comparison of linear frequency and amplitude modulation for intraneural sensory feedback in bidirectional hand prostheses.

Recent studies have shown that direct nerve stimulation can be used to provide sensory feedback to hand amputees. The intensity of the elicited sensations can be modulated using the amplitude or frequency of the injected stimuli. However, a comprehensive comparison of the effects of these two encoding strategies on the amputees' ability to control a prosthesis has not been performed. In this paper, we assessed the performance of two trans-radial amputees controlling a myoelectric hand prosthesis while receiving grip force sensory feedback encoded using either linear modulation of amplitude (LAM) or linear modulation of frequency (LFM) of direct nerve stimulation (namely, bidirectional prostheses). Both subjects achieved similar and significantly above-chance performance when they were asked to exploit LAM or LFM in different tasks. The feedbacks allowed them to discriminate, during manipulation through the robotic hand, objects of different compliances and shapes or different placements on the prosthesis. Similar high performances were obtained when they were asked to apply different levels of force in a random order on a dynamometer using LAM or LFM. In contrast, only the LAM strategy allowed the subjects to continuously modulate the grip pressure on the dynamometer. Furthermore, when long-lasting trains of stimulation were delivered, LFM strategy generated a very fast adaptation phenomenon in the subjects, which caused them to stop perceiving the restored sensations. Both encoding approaches were perceived as very different from the touch feelings of the healthy limb (natural). These results suggest that the choice of specific sensory feedback encodings can have an effect on user performance while grasping. In addition, our results invite the development of new approaches to provide more natural sensory feelings to the users, which could be addressed by a more biomimetic strategy in the future.

The S-Finger: A Synergetic Externally Powered Digit With Tactile Sensing and Feedback.

Partial hand amputation is by far the most common type of amputation worldwide. Nevertheless, regardless of their potential clinical and socioeconomic impact, battery-powered partial hand prostheses, namely, powered digits, have modestly progressed so far, and very few clinical solutions are available today. Here, we present a mechanical architecture, an alternative to state-of-the-art solutions, which exploits a high efficiency, non-back drivable mechanical transmission based on a face-gear pair and a miniaturized clutch. We took inspiration from the synergetic prehension approach proposed by Childress for whole hand amputation. The finger was equipped with a myoelectric controller and a tactile sensor able to provide users with discrete event sensory feedback. Measured speed (90°/s) and force (6.5 N) of the newly dubbed S-Finger proved comparable with those of clinically available prostheses. The design demonstrated to be compact and rugged enough to undergo a clinical viability test with two partial hand amputees, fitted with custom three-fingered research prostheses using the S-Finger. The subjects successfully completed several dexterity tests and gave relevant feedback for the development of a second-generation device. These results contribute to the increasing research endeavors in the field of partial hand amputation.

Electro-cutaneous stimulation on the palm elicits referred sensations on intact but not on amputated digits.

OBJECTIVE: 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. Early studies have shown that non-invasive electro-cutaneous stimulation (ES) can induce referred sensations that are spread to a wider and/or more distant area, with respect to the electrodes. Building on this, we sought to exploit this effect to provide somatotopically matched sensory feedback to people with partial hand (digital) amputations. APPROACH: For the first time, this work investigated the possibility of inducing referred sensations in the digits by activating the palmar nerves. Specifically, we electrically stimulated 18 sites on the palm of non-amputees to evaluate the effects of sites and stimulation parameters on modality, magnitude, and location of the evoked sensations. We performed similar tests with partial hand amputees by testing those sites that had most consistently elicited referred sensations in non-amputees. MAIN RESULTS: We demonstrated referred sensations in non-amputees from all stimulation sites in one form or another. Specifically, the stimulation of 16 of the 18 sites gave rise to reliable referred sensations. Amputees experienced referred sensations to unimpaired digits, just like non-amputees, but we were unable to evoke referred sensations in their missing digits: none of them reported sensations that extended beyond the tip of the stump. SIGNIFICANCE: The possibility of eliciting referred sensations on the digits may be exploited in haptic systems for providing touch sensations without obstructing the fingertips or their movements. The study also suggests that the phenomenon of referred sensations through ES may not be exploited for partial hand prostheses, and it invites researchers to explore alternative approaches. Finally, the results seem to confirm previous studies suggesting that the stumps in partial hand amputees partially acquire the role of the missing fingertips, physiologically and cognitively.

The myokinetic control interface: tracking implanted magnets as a means for prosthetic control.

Upper limb amputation deprives individuals of their innate ability to manipulate objects. Such disability can be restored with a robotic prosthesis linked to the brain by a human-machine interface (HMI) capable of decoding voluntary intentions, and sending motor commands to the prosthesis. Clinical or research HMIs rely on the interpretation of electrophysiological signals recorded from the muscles. However, the quest for an HMI that allows for arbitrary and physiologically appropriate control of dexterous prostheses, is far from being completed. Here we propose a new HMI that aims to track the muscles contractions with implanted permanent magnets, by means of magnetic field sensors. We called this a myokinetic control interface. We present the concept, the features and a demonstration of a prototype which exploits six 3-axis sensors to localize four magnets implanted in a forearm mockup, for the control of a dexterous hand prosthesis. The system proved highly linear (R2 = 0.99) and precise (1% repeatability), yet exhibiting short computation delay (45 ms) and limited cross talk errors (10% the mean stroke of the magnets). Our results open up promising possibilities for amputees, demonstrating the viability of the myokinetic approach in implementing direct and simultaneous control over multiple digits of an artificial hand.