Comparison of vibrotactile and joint-torque feedback in a myoelectric upper-limb prosthesis

Integration of proprioception in upper limb prostheses through non-invasive strategies: a review

Proprioception plays a key role in moving our body dexterously and effortlessly. Nevertheless, the majority of investigations evaluating the benefits of providing supplemental feedback to prosthetics users focus on delivering touch restitution. These studies evaluate the influence of touch sensation in an attempt to improve the controllability of current robotic devices. Contrarily, investigations evaluating the capabilities of proprioceptive supplemental feedback have yet to be comprehensively analyzed to the same extent, marking a major gap in knowledge within the current research climate. The non-invasive strategies employed so far to restitute proprioception are reviewed in this work. In the absence of a clearly superior strategy, approaches employing vibrotactile, electrotactile and skin-stretch stimulation achieved better and more consistent results, considering both kinesthetic and grip force information, compared with other strategies or any incidental feedback. Although emulating the richness of the physiological sensory return through artificial feedback is the primary hurdle, measuring its effects to eventually support the integration of cumbersome and energy intensive hardware into commercial prosthetic devices could represent an even greater challenge. Thus, we analyze the strengths and limitations of previous studies and discuss the possible benefits of coupling objective measures, like neurophysiological parameters, as well as measures of prosthesis embodiment and cognitive load with behavioral measures of performance. Such insights aim to provide additional and collateral outcomes to be considered in the experimental design of future investigations of proprioception restitution that could, in the end, allow researchers to gain a more detailed understanding of possibly similar behavioral results and, thus, support one strategy over another.

VIBES: Vibro-Inertial Bionic Enhancement System in a Prosthetic Socket

The use of vibrotactile feedback is of growing interest in the field of prosthetics, but few devices fully integrate this technology in the prosthesis to transmit high-frequency contact information (such as surface roughness and first contact) arising from the interaction of the prosthetic device with external items. This study describes a wearable vibrotactile system for high-frequency tactile information embedded in the prosthetic socket. The device consists of two compact planar vibrotactile actuators in direct contact with the user's skin to transmit tactile cues. These stimuli are directly related to the acceleration profiles recorded with two IMUS placed on the distal phalanx of a soft under-actuated robotic prosthesis (Soft-Hand Pro). We characterized the system from a psychophysical point of view with fifteen able-bodied participants by computing participants' Just Noticeable Difference (JND) related to the discrimination of vibrotactile cues delivered on the index finger, which are associated with the exploration of different sandpapers. Moreover, we performed a pilot experiment with one SoftHand Pro prosthesis user by designing a task, i.e. Active Texture Identification, to investigate if our feedback could enhance users' roughness discrimination. Results indicate that the device can effectively convey contact and texture cues, which users can readily detect and distinguish.

Haptic shared control improves neural efficiency during myoelectric prosthesis use

Clinical myoelectric prostheses lack the sensory feedback and sufficient dexterity required to complete activities of daily living efficiently and accurately. Providing haptic feedback of relevant environmental cues to the user or imbuing the prosthesis with autonomous control authority have been separately shown to improve prosthesis utility. Few studies, however, have investigated the effect of combining these two approaches in a shared control paradigm, and none have evaluated such an approach from the perspective of neural efficiency (the relationship between task performance and mental effort measured directly from the brain). In this work, we analyzed the neural efficiency of 30 non-amputee participants in a grasp-and-lift task of a brittle object. Here, a myoelectric prosthesis featuring vibrotactile feedback of grip force and autonomous control of grasping was compared with a standard myoelectric prosthesis with and without vibrotactile feedback. As a measure of mental effort, we captured the prefrontal cortex activity changes using functional near infrared spectroscopy during the experiment. It was expected that the prosthesis with haptic shared control would improve both task performance and mental effort compared to the standard prosthesis. Results showed that only the haptic shared control system enabled users to achieve high neural efficiency, and that vibrotactile feedback was important for grasping with the appropriate grip force. These results indicate that the haptic shared control system synergistically combines the benefits of haptic feedback and autonomous controllers, and is well-poised to inform such hybrid advancements in myoelectric prosthesis technology.

Molecular mechanisms by which targeted muscle reinnervation improves the microenvironment of spinal cord motor neurons and target muscles

Targeted muscle reinnervation is a clinically valuable nerve transfers technology used to reconstruct the information sources reconstruct the motor nerve information sources lost because of nerve injury. This study aimed to investigate the effects and underlying molecular mechanisms of hind limb TMR on motor neurons and target muscles in rats after tibial nerve transection (TNT). Immunohistochemistry was performed to detect acetylcholinesterase expression in the target muscles and myelin basic protein, neuregulin-1 (NRG1), and ErbB2 expression in the tibial nerve of rats. Masson's trichrome staining was performed to observe fibrillar collagen expression in the target muscles. Western blot analysis was used to detect the protein expression of NRG1 and its receptor, ErbB2, in the target muscles. TMR significantly enhanced NRG1, ErbB2, and myelin basic protein expression in nerve fibers compared with those in the TNT group and exerted a protective effect on the maintenance of a large number of nerve fibers and myelin sheath thickness. The above results indicated that TMR can regulate NRG1 and ErbB2 expression in residual nerve fibers and protect the integrity of the myelin sheath, thus improving the functional status of the target muscles, which is beneficial for restoring hind limb motor function after TNT.

EMG feedback outperforms force feedback in the presence of prosthesis control disturbance

Closing the prosthesis control loop by providing artificial somatosensory feedback can improve utility and user experience. Additionally, closed-loop control should be more robust with respect to disturbance, but this might depend on the type of feedback provided. Thus, the present study investigates and compares the performance of EMG and force feedback in the presence of control disturbances. Twenty able-bodied subjects and one transradial amputee performed delicate and power grasps with a prosthesis in a functional task, while the control signal gain was temporarily increased (high-gain disturbance) or decreased (low-gain disturbance) without their knowledge. Three outcome measures were considered: the percentage of trials successful in the first attempt (reaction to disturbance), the average number of attempts in trials where the wrong force was initially applied (adaptation to disturbance), and the average completion time of the last attempt in every trial. EMG feedback was shown to offer significantly better performance compared to force feedback during power grasping in terms of reaction to disturbance and completion time. During power grasping with high-gain disturbance, the median first-attempt success rate was significantly higher with EMG feedback (73.3%) compared to that achieved with force feedback (60%). Moreover, the median completion time for power grasps with low-gain disturbance was significantly longer with force feedback than with EMG feedback (3.64 against 2.48 s, an increase of 32%). Contrary to our expectations, there was no significant difference between feedback types with regards to adaptation to disturbances and the two feedback types performed similarly in delicate grasps. The results indicated that EMG feedback displayed better performance than force feedback in the presence of control disturbances, further demonstrating the potential of this approach to provide a reliable prosthesis-user interaction.

Just noticeable differences for elbow joint torque feedback

Joint torque feedback is a new and promising means of kinesthetic feedback imposed by a wearable device. The torque feedback provides the wearer temporal and spatial information during a motion task. Nevertheless, little research has been conducted on quantifying the psychophysical parameters of how well humans can perceive external torques under various joint conditions. This study aims to investigate the just noticeable difference (JND) perceptual ability of the elbow joint to joint torques. The paper focuses on the ability of two primary joint proprioceptors, the Golgi-tendon organ (GTO) and muscle spindle (MS), to detect elbow torques, since touch and pressure sensors were masked. We studied 14 subjects while the arm was isometrically contracted (static condition) and was moving at a constant speed (dynamic condition). In total there were 10 joint conditions investigated, which varied the direction of the arm's movement and the preload direction as well as torque direction. The JND torques under static conditions ranged from 0.097 Nm with no preload to 0.197 Nm with a preload of 1.28 Nm. The maximum dynamic JND torques were 0.799 Nm and 0.428 Nm, when the arm was flexing and extending at 213 degrees per second, respectively.

Closed-loop control of a prosthetic finger via evoked proprioceptive information

Objective.Proprioceptive information plays an important role for recognizing and coordinating our limb's static and dynamic states relative to our body or the environment. In this study, we determined how artificially evoked proprioceptive feedback affected the continuous control of a prosthetic finger.Approach.We elicited proprioceptive information regarding the joint static position and dynamic movement of a prosthetic finger via a vibrotactor array placed around the subject's upper arm. Myoelectric signals of the finger flexor and extensor muscles were used to control the prosthesis, with or without the evoked proprioceptive feedback. Two control modes were evaluated: the myoelectric signal amplitudes were continuously mapped to either the position or the velocity of the prosthetic joint.Main results.Our results showed that the evoked proprioceptive information improved the control accuracy of the joint angle, with comparable performance in the position- and velocity-control conditions. However, greater angle variability was prominent during position-control than velocity-control. Without the proprioceptive feedback, the position-control tended to show a smaller angle error than the velocity-control condition.Significance.Our findings suggest that closed-loop control of a prosthetic device can potentially be achieved using non-invasive evoked proprioceptive feedback delivered to intact participants. Moreover, the evoked sensory information was integrated during myoelectric control effectively for both control strategies. The outcomes can facilitate our understanding of the sensorimotor integration process during human-machine interactions, which can potentially promote fine control of prosthetic hands.

Getting a Grip on the Impact of Incidental Feedback From Body-Powered and Myoelectric Prostheses

Sensory feedback from body-powered and myoelectric prostheses are limited, but in different ways. Currently, there are no empirical studies on how incidental feedback differs between body-powered and myoelectric prostheses, or how these differences impact grasping. Thus, the purpose of this study was to quantify differences in grasping performance between body-powered and myoelectric prosthesis users when presented with different forms of feedback. Nine adults with upper limb loss and nine without (acting as controls) completed two tasks in a virtual environment. In the first task, participants used visual, vibration, or force feedback to assist in matching target grasp apertures. In the second task, participants used either visual or force feedback to identify the stiffness of a virtual object. Participants using either prosthesis type improved their accuracy and reduced their variability compared to the no feedback condition when provided with any form of feedback (p < 0.001). However, participants using body-powered prostheses were significantly more accurate and less variable at matching grasp apertures than those using myoelectric prostheses across all feedback conditions. When identifying stiffness, body-powered prosthesis users were more accurate using force feedback (64% compared to myoelectric users' 39%) while myoelectric users were more accurate using visual feedback (65% compared to body-powered users' 53%). This study supports previous findings that body-powered prosthesis users receive limited force and proprioceptive feedback, while myoelectric prosthesis users receive almost no force or proprioceptive feedback from their device. This work can inform future supplemental feedback that enhances rather than reproduces existing incidental feedback.

Evaluation of Optimal Vibrotactile Feedback for Force-Controlled Upper Limb Myoelectric Prostheses

The main goal of this study is to evaluate how to optimally select the best vibrotactile pattern to be used in a closed loop control of upper limb myoelectric prostheses as a feedback of the exerted force. To that end, we assessed both the selection of actuation patterns and the effects of the selection of frequency and amplitude parameters to discriminate between different feedback levels. A single vibrotactile actuator has been used to deliver the vibrations to subjects participating in the experiments. The results show no difference between pattern shapes in terms of feedback perception. Similarly, changes in amplitude level do not reflect significant improvement compared to changes in frequency. However, decreasing the number of feedback levels increases the accuracy of feedback perception and subject-specific variations are high for particular participants, showing that a fine-tuning of the parameters is necessary in a real-time application to upper limb prosthetics. In future works, the effects of training, location, and number of actuators will be assessed. This optimized selection will be tested in a real-time proportional myocontrol of a prosthetic hand.

Myoelectric Control for Upper Limb Prostheses

State-of-the-art high-end prostheses are electro-mechanically able to provide a great variety of movements. Nevertheless, in order to functionally replace a human limb, it is essential that each movement is properly controlled. This is the goal of prosthesis control, which has become a growing research field in the last decades, with the ultimate goal of reproducing biological limb control. Therefore, exploration and development of prosthesis control are crucial to improve many aspects of an amputee’s life. Nowadays, a large divergence between academia and industry has become evident in commercial systems. Although several studies propose more natural control systems with promising results, basic one degree of freedom (DoF), a control switching system is the most widely used option in industry because of simplicity, robustness and inertia. A few classification controlled prostheses have emerged in the last years but they are still a low percentage of the used ones. One of the factors that generate this situation is the lack of robustness of more advanced control algorithms in daily life activities outside of laboratory conditions. Because of this, research has shifted towards more functional prosthesis control. This work reviews the most recent literature in upper limb prosthetic control. It covers commonly used variants of possible biological inputs, its processing and translation to actual control, mostly focusing on electromyograms as well as the problems it will have to overcome in near future.