Toward higher-performance bionic limbs for wider clinical use.

Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by the user as belonging to their own body. Robotic limbs can convey information about the environment with higher precision than biological limbs, but their actual performance is substantially limited by current technologies for the interfacing of the robotic devices with the body and for transferring motor and sensory information bidirectionally between the prosthesis and the user. In this Perspective, we argue that direct skeletal attachment of bionic devices via osseointegration, the amplification of neural signals by targeted muscle innervation, improved prosthesis control via implanted muscle sensors and advanced algorithms, and the provision of sensory feedback by means of electrodes implanted in peripheral nerves, should all be leveraged towards the creation of a new generation of high-performance bionic limbs. These technologies have been clinically tested in humans, and alongside mechanical redesigns and adequate rehabilitation training should facilitate the wider clinical use of bionic limbs.

Energy Recuperation at the Hip Joint for Paraplegic Walking: Interaction Between Patient and Supportive Device.

For patients with lower limb paralysis, wearable robotic systems are becoming increasingly important for regaining mobility. The actuation of these systems is challenging because of the necessity to deliver high power within very limited space. However, not all patients need full support, as many patients have residual muscle function that can be applied for locomotion. This work introduces a microprocessor-controlled leg (hip-knee-ankle-foot) orthosis (mpLeg) with energy recuperation capabilities at the hip joint. The system redistributes motion energy generated by the patient during walking. In stance phase of walking, energy is stored in an elastic element at the hip joint. This energy can be released by computer control later in the gait phase, to support swing phase motion. This work aims at investigating the influence of the elastic element in the orthotic hip joint on a patient's motion. Experiments conducted with a patient suffering from incomplete paraplegia demonstrated that the motion pattern during walking improved with activated energy recuperation. This observation was made over a wide range of system parameters. The patient used the energy recuperation capabilities of the mpLeg with up to 4.1 J recuperated energy per step, which resulted in a more natural swing phase motion during walking. Therefore energy recuperation at the hip joint is a feasible technology for future supportive devices.

A Novel Method to Generate Amplitude-Frequency Modulated Vibrotactile Stimulation.

The natural interaction of humans with their environment involves the harmonious coordination of the body, for which multi-modal feedback including vision, proprioception, and tactile perception is essential. Most human-machine interfaces, however, rely on the visual feedback only, and this can lead to considerable cognitive burden. Additional haptic feedback can increase the intuitiveness of the man-machine interaction. Therefore, we propose here a new device able to generate complex vibrotactile stimulation by simultaneously modulating the amplitude and frequency of vibration. Physical measurements were first performed in eight healthy subjects to assess the capability of the device to generate vibrations. The results indicated that the vibration frequency and amplitude can be independently modulated and that the device response to the full-range step-change in the amplitude/frequency commands is almost instantaneous and symmetric. In addition, psychophysical assessments were conducted in four healthy subjects using a standard psychophysical procedure (SIAM). The outcomes indicated that the proposed device can produce approximately 400 vixels (discriminable stimuli), which allow for the generation of a high diversity of vibrotactile patterns. The proposed method allows producing different kinds of stimulation patterns using motor types that are suited for specific applications, with adjustable trade-off between vibration intensity, size, and power consumption.

Long-term decoding of movement force and direction with a wireless myoelectric implant.

OBJECTIVE: The ease of use and number of degrees of freedom of current myoelectric hand prostheses is limited by the information content and reliability of the surface electromyography (sEMG) signals used to control them. For example, cross-talk limits the capacity to pick up signals from small or deep muscles, such as the forearm muscles for distal arm amputations, or sites of targeted muscle reinnervation (TMR) for proximal amputations. Here we test if signals recorded from the fully implanted, induction-powered wireless Myoplant system allow long-term decoding of continuous as well as discrete movement parameters with better reliability than equivalent sEMG recordings. The Myoplant system uses a centralized implant to transmit broadband EMG activity from four distributed bipolar epimysial electrodes. APPROACH: Two Rhesus macaques received implants in their backs, while electrodes were placed in their upper arm. One of the monkeys was trained to do a cursor task via a haptic robot, allowing us to control the forces exerted by the animal during arm movements. The second animal was trained to perform a center-out reaching task on a touchscreen. We compared the implanted system with concurrent sEMG recordings by evaluating our ability to decode time-varying force in one animal and discrete reach directions in the other from multiple features extracted from the raw EMG signals. MAIN RESULTS: In both cases, data from the implant allowed a decoder trained with data from a single day to maintain an accurate decoding performance during the following months, which was not the case for concurrent surface EMG recordings conducted simultaneously over the same muscles. SIGNIFICANCE: These results show that a fully implantable, centralized wireless EMG system is particularly suited for long-term stable decoding of dynamic movements in demanding applications such as advanced forelimb prosthetics in a wide range of configurations (distal amputations, TMR).

Prosthesis Control with an Implantable Multichannel Wireless Electromyography System for High-Level Amputees: A Large-Animal Study.

BACKGROUND: Myoelectric prostheses lack a strong human-machine interface, leading to high abandonment rates in upper limb amputees. Implantable wireless electromyography systems improve control by recording signals directly from muscle, compared with surface electromyography. These devices do not exist for high amputation levels. In this article, the authors present an implantable wireless electromyography system for these scenarios tested in Merino sheep for 4 months. METHODS: In a pilot trial, the electrodes were implanted in the hind limbs of 24 Sprague-Dawley rats. After 8 or 12 weeks, impedance and histocompatibility were assessed. In the main trial, the system was tested in four Merino sheep for 4 months. Impedance of the electrodes was analyzed in two animals. Electromyographic data were analyzed in two freely moving animals repeatedly during forward and backward gait. RESULTS: Device implantation was successful in all 28 animals. Histologic evaluation showed a tight encapsulation after 8 weeks of 78.2 ± 26.5 µm subcutaneously and 92.9 ± 31.3 µm on the muscular side. Electromyographic recordings show a distinct activation pattern of the triceps, brachialis, and latissimus dorsi muscles, with a low signal-to-noise ratio, representing specific patterns of agonist and antagonist activation. Average electrode impedance decreased over the whole frequency range, indicating an improved electrode-tissue interface during the implantation. All measurements taken over the 4 months of observation used identical settings and showed similar recordings despite changing environmental factors. CONCLUSION: This study shows the implantation of this electromyography device as a promising alternative to surface electromyography, providing a potentially powerful wireless interface for high-level amputees.

Closed-loop control of grasping with a myoelectric hand prosthesis: which are the relevant feedback variables for force control?

In closed-loop control of grasping by hand prostheses, the feedback information sent to the user is usually the actual controlled variable, i.e., the grasp force. Although this choice is intuitive and logical, the force production is only the last step in the process of grasping. Therefore, this study evaluated the performance in controlling grasp strength using a hand prosthesis operated through a complete grasping sequence while varying the feedback variables (e.g., closing velocity, grasping force), which were provided to the user visually or through vibrotactile stimulation. The experiments were conducted on 13 volunteers who controlled the Otto Bock Sensor Hand Speed prosthesis. Results showed that vibrotactile patterns were able to replace the visual feedback. Interestingly, the experiments demonstrated that direct force feedback was not essential for the control of grasping force. The subjects were indeed able to control the grip strength, predictively, by estimating the grasping force from the prosthesis velocity of closing. Therefore, grasping without explicit force feedback is not completely blind, contrary to what is usually assumed. In our study we analyzed grasping with a specific prosthetic device, but the outcomes are also applicable for other devices, with one or more degrees-of-freedom. The necessary condition is that the electromyography (EMG) signal directly and proportionally controls the velocity/grasp force of the hand, which is a common approach among EMG controlled prosthetic devices. The results provide important indications on the design of closed-loop EMG controlled prosthetic systems.

The extraction of neural information from the surface EMG for the control of upper-limb prostheses: emerging avenues and challenges.

Despite not recording directly from neural cells, the surface electromyogram (EMG) signal contains information on the neural drive to muscles, i.e., the spike trains of motor neurons. Using this property, myoelectric control consists of the recording of EMG signals for extracting control signals to command external devices, such as hand prostheses. In commercial control systems, the intensity of muscle activity is extracted from the EMG and used for single degrees of freedom activation (direct control). Over the past 60 years, academic research has progressed to more sophisticated approaches but, surprisingly, none of these academic achievements has been implemented in commercial systems so far. We provide an overview of both commercial and academic myoelectric control systems and we analyze their performance with respect to the characteristics of the ideal myocontroller. Classic and relatively novel academic methods are described, including techniques for simultaneous and proportional control of multiple degrees of freedom and the use of individual motor neuron spike trains for direct control. The conclusion is that the gap between industry and academia is due to the relatively small functional improvement in daily situations that academic systems offer, despite the promising laboratory results, at the expense of a substantial reduction in robustness. None of the systems so far proposed in the literature fulfills all the important criteria needed for widespread acceptance by the patients, i.e. intuitive, closed-loop, adaptive, and robust real-time ( 200 ms delay) control, minimal number of recording electrodes with low sensitivity to repositioning, minimal training, limited complexity and low consumption. Nonetheless, in recent years, important efforts have been invested in matching these criteria, with relevant steps forwards.