Evaluation of Simple Algorithms for Proportional Control of Prosthetic Hands Using Intramuscular Electromyography.

Although seemingly effortless, the control of the human hand is backed by an elaborate neuro-muscular mechanism. The end result is typically a smooth action with the precise positioning of the joints of the hand and an exerted force that can be modulated to enable precise interaction with the surroundings. Unfortunately, even the most sophisticated technology cannot replace such a comprehensive role but can offer only basic hand functionalities. This issue arises from the drawbacks of the prosthetic hand control strategies that commonly rely on surface EMG signals that contain a high level of noise, thus limiting accurate and robust multi-joint movement estimation. The use of intramuscular EMG results in higher quality signals which, in turn, lead to an improvement in prosthetic control performance. Here, we present the evaluation of fourteen common/well-known algorithms (mean absolute value, variance, slope sign change, zero crossing, Willison amplitude, waveform length, signal envelope, total signal energy, Teager energy in the time domain, Teager energy in the frequency domain, modified Teager energy, mean of signal frequencies, median of signal frequencies, and firing rate) for the direct and proportional control of a prosthetic hand. The method involves the estimation of the forces generated in the hand by using different algorithms applied to iEMG signals from our recently published database, and comparing them to the measured forces (ground truth). The results presented in this paper are intended to be used as a baseline performance metric for more advanced algorithms that will be made and tested using the same database.

Neurophysiology of slip sensation and grip reaction: insights for hand prosthesis control of slippage.

Sensory feedback is pivotal for a proficient dexterity of the hand. By modulating the grip force in function of the quick and not completely predictable change of the load force, grabbed objects are prevented to slip from the hand. Slippage control is an enabling achievement to all manipulation abilities. However, in hand prosthetics, the performance of even the most innovative research solutions proposed so far to control slippage remain distant from the human physiology. Indeed, slippage control involves parallel and compensatory activation of multiple mechanoceptors, spinal and supraspinal reflexes, and higher-order voluntary behavioral adjustments. In this work, we reviewed the literature on physiological correlates of slippage to propose a three-phases model for the slip sensation and reaction. Furthermore, we discuss the main strategies employed so far in the research studies that tried to restore slippage control in amputees. In the light of the proposed three-phase slippage model and from the weaknesses of already implemented solutions, we proposed several physiology-inspired solutions for slippage control to be implemented in the future hand prostheses. Understanding the physiological basis of slip detection and perception and implementing them in novel hand feedback system would make prosthesis manipulation more efficient and would boost its perceived naturalness, fostering the sense of agency for the hand movements.

Six-Month Assessment of a Hand Prosthesis with Intraneural Tactile Feedback.

OBJECTIVE: Hand amputation is a highly disabling event, which significantly affects quality of life. An effective hand replacement can be achieved if the user, in addition to motor functions, is provided with the sensations that are naturally perceived while grasping and moving. Intraneural peripheral electrodes have shown promising results toward the restoration of the sense of touch. However, the long-term usability and clinical relevance of intraneural sensory feedback have not yet been clearly demonstrated. METHODS: To this aim, we performed a 6-month clinical study with 3 transradial amputees who received implants of transverse intrafascicular multichannel electrodes (TIMEs) in their median and ulnar nerves. After calibration, electrical stimulation was delivered through the TIMEs connected to artificial sensors in the digits of a prosthesis to generate sensory feedback, which was then used by the subjects while performing different grasping tasks. RESULTS: All subjects, notwithstanding their important clinical differences, reported stimulation-induced sensations from the phantom hand for the whole duration of the trial. They also successfully integrated the sensory feedback into their motor control strategies while performing experimental tests simulating tasks of real life (with and without the support of vision). Finally, they reported a decrement of their phantom limb pain and a general improvement in mood state. INTERPRETATION: The promising results achieved with all subjects show the feasibility of the use of intraneural stimulation in clinical settings. ANN NEUROL 2019;85:137-154.

Continuous supplementary tactile feedback can be applied (and then removed) to enhance precision manipulation.

BACKGROUND: Human sensorimotor control of dexterous manipulation relies on afferent sensory signals. Explicit tactile feedback is generally not available to prosthetic hand users, who have to rely on incidental information sources to partly close the control loop, resulting in suboptimal performance and manipulation difficulty. Recent studies on non-invasive supplementary sensory feedback indicated that time-discrete vibrational feedback delivered upon relevant mechanical events outperforms continuous tactile feedback. However, we hypothesize that continuous tactile feedback can be more effective in non-routine manipulation tasks (i.e., tasks where the grip force is modified reactively in response to the sensory feedback due to the unpredictable behavior of the manipulated object, such as picking and holding a virtual fragile object) if delivered to highly sensitive areas. We further hypothesize that this continuous tactile feedback is not necessary during all the duration of the manipulation task, since adaptation occurs. METHODS: We investigated the effectiveness of continuous tactile feedback in precision manipulation, together with a new sensory feedback policy, where the continuous tactile feedback is gradually removed when the grasp reaches a steady state (namely, transient tactile feedback). We carried out an experiment in a virtual-reality setting with custom tactile feedback devices, which can apply continuous pressure and vibrations, attached to the thumb and index finger. We enrolled 24 healthy participants and instructed them to pick and hold a fragile virtual cube without breaking it. We compared their manipulation performance when using four different sensory feedback methods, i.e., no tactile feedback, discrete vibrations, continuous tactile feedback, and transient tactile feedback. The latter consisted of gradually removing the continuous feedback in the static phase of the grasp. RESULTS: Continuous tactile feedback leads to a significantly larger number of successful trials than discrete vibrational cues and no feedback conditions, yet the gradual removal of the continuous feedback yields to comparable outcomes. Moreover, the participants preferred the continuous stimuli over the vibrational cues and the removal in the static phase did not significantly impact their appreciation of the continuous tactile feedback. CONCLUSIONS: These results advocate for the use of continuous supplementary tactile feedback for fine manipulation control and indicate that it can seamlessly be removed in the static phase of the grasp, possibly due to the mechanism of sensory adaptation. This encourages the development of energy-efficient supplementary feedback devices for prosthetic and telemanipulation applications, where encumbrance and power consumption are burdensome constraints.

The preload force affects the perception threshold of muscle vibration-induced movement illusions.

The control and the execution of motor tasks are largely influenced by proprioceptive feedback, i.e. the information about the position and movement of the body. In 1972, it was discovered that a vibratory stimulation applied non-invasively to a muscle or a tendon induces a movement illusion consistent with the elongation of the vibrated muscle/tendon. Although this phenomenon was reported by several studies, it is still unclear how to reliably reproduce it because of the many different features of the stimulation altering the sensation (e.g. frequency, duration, location). By performing a psychophysical test, we analysed the effects of the stimulation point and the preload force on the minimum stimulation amplitude needed to elicit an illusion of movement. In particular, we stimulated two groups of healthy subjects on three target regions of the biceps brachii muscle (the distal tendon, the muscle belly and one of the proximal tendons) applying three preload force ranges (0.5-0.75N, 1-2N and 3-4N). Our results showed that the minimum stimulation amplitude eliciting a sensation is affected by the preload force. On the contrary, it did not change significantly among the three stimulated regions. Nevertheless, the reported vividness of the illusion of movement changed across the stimulated points decreasing while moving from the distal to the proximal tendons. Overall, these outcomes contribute to the scientific debate on the features that modulate the vibration-induced movement illusion proposing ways to increase the reliability of the procedure in basic and applied research studies.

Grip control and motor coordination with implanted and surface electrodes while grasping with an osseointegrated prosthetic hand.

BACKGROUND: Replacement of a lost limb by an artificial substitute is not yet ideal. Resolution and coordination of motor control approximating that of a biological limb could dramatically improve the functionality of prosthetic devices, and thus reduce the gap towards a suitable limb replacement. METHODS: In this study, we investigated the control resolution and coordination exhibited by subjects with transhumeral amputation who were implanted with epimysial electrodes and an osseointegrated interface that provides bidirectional communication in addition to skeletal attachment (e-OPRA Implant System). We assessed control resolution and coordination in the context of routine and delicate grasping using the Pick and Lift and the Virtual Eggs Tests. Performance when utilizing implanted electrodes was compared with the standard-of-care technology for myoelectric prostheses, namely surface electrodes. RESULTS: Results showed that implanted electrodes provide superior controllability over the prosthetic terminal device compared to conventional surface electrodes. Significant improvements were found in the control of the grip force and its reliability during object transfer. However, these improvements failed to increase motor coordination, and surprisingly decreased the temporal correlation between grip and load forces observed with surface electrodes. We found that despite being more functional and reliable, prosthetic control via implanted electrodes still depended highly on visual feedback. CONCLUSIONS: Our findings indicate that incidental sensory feedback (visual, auditory, and osseoperceptive in this case) is insufficient for restoring natural grasp behavior in amputees, and support the idea that supplemental tactile sensory feedback is needed to learn and maintain the motor tasks internal model, which could ultimately restore natural grasp behavior in subjects using prosthetic hands.

Development of an Embedded Myokinetic Prosthetic Hand Controller.

The quest for an intuitive and physiologically appropriate human machine interface for the control of dexterous prostheses is far from being completed. In the last decade, much effort has been dedicated to explore innovative control strategies based on the electrical signals generated by the muscles during contraction. In contrast, a novel approach, dubbed myokinetic interface, derives the control signals from the localization of multiple magnetic markers (MMs) directly implanted into the residual muscles of the amputee. Building on this idea, here we present an embedded system based on 32 magnetic field sensors and a real time computation platform. We demonstrate that the platform can simultaneously localize in real-time up to five MMs in an anatomically relevant workspace. The system proved highly linear (R2 = 0.99) and precise (1% repeatability), yet exhibiting short computation times (4 ms) and limited cross talk errors (10% the mean stroke of the magnets). Compared to a previous PC implementation, the system exhibited similar precision and accuracy, while being ~75% faster. These results proved for the first time the viability of using an embedded system for magnet localization. They also suggest that, by using an adequate number of sensors, it is possible to increase the number of simultaneously tracked MMs while introducing delays that are not perceivable by the human operator. This could allow to control more degrees of freedom than those controllable with current technologies.

Humans adjust their grip force when passing an object according to the observed speed of the partner's reaching out movement.

The way an object is released by the passer to a partner is fundamental for the success of the handover and for the experienced fluency and quality of the interaction. Nonetheless, although its apparent simplicity, object handover involves a complex combination of predictive and reactive control mechanisms that were not fully investigated so far. Here, we show that passers use visual-feedback based anticipatory control to trigger the beginning of the release, to launch the appropriate motor program, and adapt such predictions to different speeds of the receiver's reaching out movements. In particular, the passer starts releasing the object in synchrony with the collision with the receiver, regardless of the receiver's speed, but the passer's speed of grip force release is correlated with receiver speed. When visual feedback is removed, the beginning of the passer's release is delayed proportionally with the receiver's reaching out speed; however, the correlation between the passer's peak rate of change of grip force is maintained. In a second study with 11 participants receiving an object from a robotic hand programmed to release following stereotypical biomimetic profiles, we found that handovers are experienced as more fluent when they exhibit more reactive release behaviours, shorter release durations, and shorter handover durations. The outcomes from the two studies contribute understanding of the roles of sensory input in the strategy that empower humans to perform smooth and safe handovers, and they suggest methods for programming controllers that would enable artificial hands to hand over objects with humans in an easy, natural and efficient way.

Improving internal model strength and performance of prosthetic hands using augmented feedback.

BACKGROUND: The loss of an arm presents a substantial challenge for upper limb amputees when performing activities of daily living. Myoelectric prosthetic devices partially replace lost hand functions; however, lack of sensory feedback and strong understanding of the myoelectric control system prevent prosthesis users from interacting with their environment effectively. Although most research in augmented sensory feedback has focused on real-time regulation, sensory feedback is also essential for enabling the development and correction of internal models, which in turn are used for planning movements and reacting to control variability faster than otherwise possible in the presence of sensory delays. METHODS: Our recent work has demonstrated that audio-augmented feedback can improve both performance and internal model strength for an abstract target acquisition task. Here we use this concept in controlling a robotic hand, which has inherent dynamics and variability, and apply it to a more functional grasp-and-lift task. We assessed internal model strength using psychophysical tests and used an instrumented Virtual Egg to assess performance. RESULTS: Results obtained from 14 able-bodied subjects show that a classifier-based controller augmented with audio feedback enabled stronger internal model (p = 0.018) and better performance (p = 0.028) than a controller without this feedback. CONCLUSIONS: We extended our previous work and accomplished the first steps on a path towards bridging the gap between research and clinical usability of a hand prosthesis. The main goal was to assess whether the ability to decouple internal model strength and motion variability using the continuous audio-augmented feedback extended to real-world use, where the inherent mechanical variability and dynamics in the mechanisms may contribute to a more complicated interplay between internal model formation and motion variability. We concluded that benefits of using audio-augmented feedback for improving internal model strength of myoelectric controllers extend beyond a virtual target acquisition task to include control of a prosthetic hand.

The rubber foot illusion.

BACKGROUND: Lower-limb amputation causes the individual a huge functional impairment due to the lack of adequate sensory perception from the missing limb. The development of an augmenting sensory feedback device able to restore some of the missing information from the amputated limb may improve embodiment, control and acceptability of the prosthesis. FINDINGS: In this work we transferred the Rubber Hand Illusion paradigm to the lower limb. We investigated the possibility of promoting body ownership of a fake foot, in a series of experiments fashioned after the RHI using matched or mismatched (vibrotactile) stimulation. The results, collected from 19 healthy subjects, demonstrated that it is possible to elicit the perception of possessing a rubber foot when modality-matched stimulations are provided synchronously on the biological foot and to the corresponding rubber foot areas. Results also proved that it is possible to enhance the illusion even with modality-mismatched stimulation, even though illusion was lower than in case of modality-matched stimulation. CONCLUSIONS: We demonstrated the possibility of promoting a Rubber Foot Illusion with both matched and mismatched stimulation.

Humans can integrate feedback of discrete events in their sensorimotor control of a robotic hand.

Providing functionally effective sensory feedback to users of prosthetics is a largely unsolved challenge. Traditional solutions require high band-widths for providing feedback for the control of manipulation and yet have been largely unsuccessful. In this study, we have explored a strategy that relies on temporally discrete sensory feedback that is technically simple to provide. According to the Discrete Event-driven Sensory feedback Control (DESC) policy, motor tasks in humans are organized in phases delimited by means of sensory encoded discrete mechanical events. To explore the applicability of DESC for control, we designed a paradigm in which healthy humans operated an artificial robot hand to lift and replace an instrumented object, a task that can readily be learned and mastered under visual control. Assuming that the central nervous system of humans naturally organizes motor tasks based on a strategy akin to DESC, we delivered short-lasting vibrotactile feedback related to events that are known to forcefully affect progression of the grasp-lift-and-hold task. After training, we determined whether the artificial feedback had been integrated with the sensorimotor control by introducing short delays and we indeed observed that the participants significantly delayed subsequent phases of the task. This study thus gives support to the DESC policy hypothesis. Moreover, it demonstrates that humans can integrate temporally discrete sensory feedback while controlling an artificial hand and invites further studies in which inexpensive, noninvasive technology could be used in clever ways to provide physiologically appropriate sensory feedback in upper limb prosthetics with much lower band-width requirements than with traditional solutions.

Transcutaneous Magnet Localizer for a Self-Contained Myokinetic Prosthetic Hand.

OBJECTIVE: The search for a physiologically appropriate interface for the control of dexterous hand prostheses is an ongoing challenge in bioengineering. In this context, we proposed an interface, named myokinetic control interface, based on the localization of magnets implanted in the residual limb muscles, to monitor their contractions and send appropriate commands to the artificial hand. As part of such concept, this interface requires a transcutaneous magnet localizer that can be integrated in a self-contained limb prosthesis, a feature yet to be realized within the current state of the art. METHODS: In an attempt to cover this gap, here we present a modular embedded system consisting of a computation unit able to acquire synchronized samples captured by up to eight acquisition units, so to localize multiple magnets. RESULTS: The system exhibits short computation times (<60ms) and power consumption (0.6-1.2W) which are suitable for use in a clinically viable prosthetic arm. The system proved able to localize magnets while moving at speeds in the range of physiological movements (<0.24m/s), with high accuracy (<1mm) and precision (<0.5mm). CONCLUSION: We demonstrated a system suitable for the implementation of a self-contained myokinetic prosthetic hand. SIGNIFICANCE: These results pave the way towards the clinical implementation of the myokinetic interface, with amputees controlling an artificial arm by means of implanted magnets.

Time-independent relationship between digits closure velocity and hand transport acceleration during reach-to-grasp movements.

Prehension movements in primates have been extensively studied for decades, and hand transport and hand grip adjustment are usually considered as the main components of any object reach-to-grasp action. Evident temporal patterns were found for the velocity of the hand during the transport phase and for the digits kinematics during pre-shaping and enclosing phases. However, such kinematics were always analysed separately in regard to time, and never studied in terms of dependence one from another. Nevertheless, if a reliable one-to-one relationship is proven, it would allow reconstructing the digit velocity (and position) simply by knowing the hand acceleration during reaching motions towards the target object, ceasing the usual dependence seen in literature from time of movement and distance from the target. In this study, the aim was precisely to analyse reach-to-grasp motions to explore if such relationship exists and how it can be formulated. Offline and real-time results not only seem to suggest the existence of a time-independent, one-to-one relationship between hand transport and hand grip adjustment, but also that such relationship is quite resilient to the different intrinsic and extrinsic properties of the target objects such as size, shape and position.

An Instrumented Glove for Restoring Sensorimotor Function of the Hand Through Augmented Sensory Feedback.

The loss of sensitivity of the upper limb due to neurological injuries severely limits the ability to manipulate objects, hindering personal independence. Non-invasive augmented sensory feedback techniques are used to promote neural plasticity hence to restore the grasping function. This work presents a wearable device for restoring sensorimotor hand functions based on Discrete Event-driven Sensory Control policy. It consists of an instrumented glove that, relying on piezoelectric sensors, delivers short-lasting vibrotactile stimuli synchronously with the relevant mechanical events (i.e., contact and release) of the manipulation. We first performed a feasibility study on healthy participants (20) that showed overall good performances of the device, with touch-event detection accuracy of 96.2% and a response delay of 22 ms. Later, we pilot tested it on two participants with limited sensorimotor functions. When using the device, they improved their hand motor coordination while performing tests for hand motor coordination assessment (i.e., pick and place test, pick and lift test). In particular, they exhibited more coordinated temporal correlations between grip force and load force profiles and enhanced performances when transferring objects, quantitatively proving the effectiveness of the device.

Restoration of grasping in an upper limb amputee using the myokinetic prosthesis with implanted magnets.

The loss of a hand disrupts the sophisticated neural pathways between the brain and the hand, severely affecting the level of independence of the patient and the ability to carry out daily work and social activities. Recent years have witnessed a rapid evolution of surgical techniques and technologies aimed at restoring dexterous motor functions akin to those of the human hand through bionic solutions, mainly relying on probing of electrical signals from the residual nerves and muscles. Here, we report the clinical implementation of an interface aimed at achieving this goal by exploiting muscle deformation, sensed through passive magnetic implants: the myokinetic interface. One participant with a transradial amputation received an implantation of six permanent magnets in three muscles of the residual limb. A truly self-contained myokinetic prosthetic arm embedding all hardware components and the battery within the prosthetic socket was developed. By retrieving muscle deformation caused by voluntary contraction through magnet localization, we were able to control in real time a dexterous robotic hand following both a direct control strategy and a pattern recognition approach. In just 6 weeks, the participant successfully completed a series of functional tests, achieving scores similar to those achieved when using myoelectric controllers, a standard-of-care solution, with comparable physical and mental workloads. This experience raised conceptual and technical limits of the interface, which nevertheless pave the way for further investigations in a partially unexplored field. This study also demonstrates a viable possibility for intuitively interfacing humans with robotic technologies.

Cutting Edge Bionics in Highly Impaired Individuals: A Case of Challenges and Opportunities.

Highly impaired individuals stand to benefit greatly from cutting-edge bionic technology, however concurrent functional deficits may complicate the adaptation of such technology. Here, we present a case in which a visually impaired individual with bilateral burn injury amputation was provided with a novel transradial neuromusculoskeletal prosthesis comprising skeletal attachment via osseointegration and implanted electrodes in nerves and muscles for control and sensory feedback. Difficulties maintaining implant hygiene and donning and doffing the prosthesis arose due to his contralateral amputation, ipsilateral eye loss, and contralateral impaired vision necessitating continuous adaptations to the electromechanical interface. Despite these setbacks, the participant still demonstrated improvements in functional outcomes and the ability to control the prosthesis in various limb positions using the implanted electrodes. Our results demonstrate the importance of a multidisciplinary, iterative, and patient-centered approach to making cutting-edge technology accessible to patients with high levels of impairment.

To What Extent Implanting Single vs Pairs of Magnets Per Muscle Affect the Localization Accuracy of the Myokinetic Control Interface? Evidence From a Simulated Environment.

OBJECTIVE: We recently proposed a new concept of human-machine interface to control hand prostheses which we dubbed the myokinetic control interface. Such interface detects muscle displacement during contraction by localizing permanent magnets implanted in the residual muscles. So far, we evaluated the feasibility of implanting one magnet per muscle and monitoring its displacement relative to its initial position. However, multiple magnets could actually be implanted in each muscle, as using their relative distance as a measure of muscle contraction could improve the system robustness against environmental disturbances. METHODS: Here, we simulated the implant of pairs of magnets in each muscle and we compared the localization accuracy of such system with the one magnet per muscle approach, considering first a planar and then an anatomically appropriate configuration. Such comparison was also performed when simulating different grades of mechanical disturbances applied to the system (i.e., shift of the sensor grid). RESULTS: We found that implanting one magnet per muscle always led to lower localization errors under ideal conditions (i.e., no external disturbances). Differently, when mechanical disturbances were applied, magnet pairs outperformed the single magnet approach, confirming that differential measurements are able to reject common mode disturbances. CONCLUSION: We identified important factors affecting the choice of the number of magnets to implant in a muscle. SIGNIFICANCE: Our results provide important guidelines for the design of disturbance rejection strategies and for the development of the myokinetic control interface, as well as for a whole range of biomedical applications involving magnetic tracking.

Decoding of Multiple Wrist and Hand Movements Using a Transient EMG Classifier.

The design of prosthetic controllers by means of neurophysiological signals still poses a crucial challenge to bioengineers. State of the art of electromyographic (EMG) continuous pattern recognition controllers rely on the questionable assumption that repeated muscular contractions produce repeatable patterns of steady-state EMG signals. Conversely, we propose an algorithm that decodes wrist and hand movements by processing the signals that immediately follow the onset of contraction (i.e., the transient EMG). We collected EMG data from the forearms of 14 non-amputee and 5 transradial amputee participants while they performed wrist flexion/extension, pronation/supination, and four hand grasps (power, lateral, bi-digital, open). We firstly identified the combination of wrist and hand movements that yielded the best control performance for the same participant (intra-subject classification). Then, we assessed the ability of our algorithm to classify participant data that were not included in the training set (cross-subject classification). Our controller achieved a median accuracy of ~96% with non-amputees, while it achieved heterogeneous outcomes with amputees, with a median accuracy of ~89%. Importantly, for each amputee, it produced at least one acceptable combination of wrist-hand movements (i.e., with accuracy >85%). Regarding the cross-subject classifier, while our algorithm obtained promising results with non-amputees (accuracy up to ~80%), they were not as good with amputees (accuracy up to ~35%), possibly suggesting further assessments with domain-adaptation strategies. In general, our offline outcomes, together with a preliminary online assessment, support the hypothesis that the transient EMG decoding could represent a viable pattern recognition strategy, encouraging further online assessments.

HANDdata - first-person dataset including proximity and kinematics measurements from reach-to-grasp actions.

HANDdata is a dataset designed to provide hand kinematics and proximity vision data during reach to grasp actions of non-virtual objects, specifically tailored for autonomous grasping of a robotic hand, and with particular attention to the reaching phase. Thus, we sought to capture target object characteristics from radar and time-of-flight proximity sensors, as well as details of the reach-to-grasp action by looking at wrist and fingers kinematics, and at hand-object interaction main events. We structured the data collection as a sequence of static and grasping tasks, organized by increasing levels of complexity. HANDdata is a first-person, reach-to-grasp dataset that includes almost 6000 human-object interactions from 29 healthy adults, with 10 standardized objects of 5 different shapes and 2 kinds of materials. We believe that such data collection can be of value for researchers interested in autonomous grasping robots for healthcare and industrial applications, as well as for those interested in radar-based computer vision and in basic aspects of sensorimotor control and manipulation.

A highly integrated bionic hand with neural control and feedback for use in daily life.

Restoration of sensorimotor function after amputation has remained challenging because of the lack of human-machine interfaces that provide reliable control, feedback, and attachment. Here, we present the clinical implementation of a transradial neuromusculoskeletal prosthesis-a bionic hand connected directly to the user's nervous and skeletal systems. In one person with unilateral below-elbow amputation, titanium implants were placed intramedullary in the radius and ulna bones, and electromuscular constructs were created surgically by transferring the severed nerves to free muscle grafts. The native muscles, free muscle grafts, and ulnar nerve were implanted with electrodes. Percutaneous extensions from the titanium implants provided direct skeletal attachment and bidirectional communication between the implanted electrodes and a prosthetic hand. Operation of the bionic hand in daily life resulted in improved prosthetic function, reduced postamputation, and increased quality of life. Sensations elicited via direct neural stimulation were consistently perceived on the phantom hand throughout the study. To date, the patient continues using the prosthesis in daily life. The functionality of conventional artificial limbs is hindered by discomfort and limited and unreliable control. Neuromusculoskeletal interfaces can overcome these hurdles and provide the means for the everyday use of a prosthesis with reliable neural control fixated into the skeleton.