Concept: Artificial limb
A major challenge since the invention of implantable devices has been a reliable and long-term stable transcutaneous communication. In the case of prosthetic limbs, existing neuromuscular interfaces have been unable to address this challenge and provide direct and intuitive neural control. Although prosthetic hardware and decoding algorithms are readily available, there is still a lack of appropriate and stable physiological signals for controlling the devices. We developed a percutaneous osseointegrated (bone-anchored) interface that allows for permanent and unlimited bidirectional communication with the human body. With this interface, an artificial limb can be chronically driven by implanted electrodes in the peripheral nerves and muscles of an amputee, outside of controlled environments and during activities of daily living, thus reducing disability and improving quality of life. We demonstrate in one subject, for more than 1 year, that implanted electrodes provide a more precise and reliable control than surface electrodes, regardless of limb position and environmental conditions, and with less effort. Furthermore, long-term stable myoelectric pattern recognition and appropriate sensory feedback elicited via neurostimulation was demonstrated. The opportunity to chronically record and stimulate the neuromuscular system allows for the implementation of intuitive control and naturally perceived sensory feedback, as well as opportunities for the prediction of complex limb motions and better understanding of sensory perception. The permanent bidirectional interface presented here is a critical step toward more natural limb replacement, by combining stable attachment with permanent and reliable human-machine communication.
The human brain contains multiple hand-selective areas, in both the sensorimotor and visual systems. Could our brain repurpose neural resources, originally developed for supporting hand function, to represent and control artificial limbs? We studied individuals with congenital or acquired hand-loss (hereafter one-handers) using functional MRI. We show that the more one-handers use an artificial limb (prosthesis) in their everyday life, the stronger visual hand-selective areas in the lateral occipitotemporal cortex respond to prosthesis images. This was found even when one-handers were presented with images of active prostheses that share the functionality of the hand but not necessarily its visual features (e.g. a ‘hook’ prosthesis). Further, we show that daily prosthesis usage determines large-scale inter-network communication across hand-selective areas. This was demonstrated by increased resting state functional connectivity between visual and sensorimotor hand-selective areas, proportional to the intensiveness of everyday prosthesis usage. Further analysis revealed a 3-fold coupling between prosthesis activity, visuomotor connectivity and usage, suggesting a possible role for the motor system in shaping use-dependent representation in visual hand-selective areas, and/or vice versa. Moreover, able-bodied control participants who routinely observe prosthesis usage (albeit less intensively than the prosthesis users) showed significantly weaker associations between degree of prosthesis observation and visual cortex activity or connectivity. Together, our findings suggest that altered daily motor behaviour facilitates prosthesis-related visual processing and shapes communication across hand-selective areas. This neurophysiological substrate for prosthesis embodiment may inspire rehabilitation approaches to improve usage of existing substitutionary devices and aid implementation of future assistive and augmentative technologies.
Neural prostheses translate neural activity from the brain into control signals for guiding prosthetic devices, such as computer cursors and robotic limbs, and thus offer individuals with disabilities greater interaction with the world. However, relatively low performance remains a critical barrier to successful clinical translation; current neural prostheses are considerably slower, with less accurate control, than the native arm. Here we present a new control algorithm, the recalibrated feedback intention-trained Kalman filter (ReFIT-KF) that incorporates assumptions about the nature of closed-loop neural prosthetic control. When tested in rhesus monkeys implanted with motor cortical electrode arrays, the ReFIT-KF algorithm outperformed existing neural prosthetic algorithms in all measured domains and halved target acquisition time. This control algorithm permits sustained, uninterrupted use for hours and generalizes to more challenging tasks without retraining. Using this algorithm, we demonstrate repeatable high performance for years after implantation in two monkeys, thereby increasing the clinical viability of neural prostheses.
Computer vision-based assistive technology solutions can revolutionise the quality of care for people with sensorimotor disorders. The goal of this work was to enable trans-radial amputees to use a simple, yet efficient, computer vision system to grasp and move common household objects with a two-channel myoelectric prosthetic hand.
- Proceedings. Biological sciences / The Royal Society
- Published about 8 years ago
Over time, leg prostheses have improved in design, but have been incapable of actively adapting to different walking velocities in a manner comparable to a biological limb. People with a leg amputation using such commercially available passive-elastic prostheses require significantly more metabolic energy to walk at the same velocities, prefer to walk slower and have abnormal biomechanics compared with non-amputees. A bionic prosthesis has been developed that emulates the function of a biological ankle during level-ground walking, specifically providing the net positive work required for a range of walking velocities. We compared metabolic energy costs, preferred velocities and biomechanical patterns of seven people with a unilateral transtibial amputation using the bionic prosthesis and using their own passive-elastic prosthesis to those of seven non-amputees during level-ground walking. Compared with using a passive-elastic prosthesis, using the bionic prosthesis decreased metabolic cost by 8 per cent, increased trailing prosthetic leg mechanical work by 57 per cent and decreased the leading biological leg mechanical work by 10 per cent, on average, across walking velocities of 0.75-1.75 m s(-1) and increased preferred walking velocity by 23 per cent. Using the bionic prosthesis resulted in metabolic energy costs, preferred walking velocities and biomechanical patterns that were not significantly different from people without an amputation.
Objective. In a previous study we demonstrated continuous translation, orientation and one-dimensional grasping control of a prosthetic limb (seven degrees of freedom) by a human subject with tetraplegia using a brain-machine interface (BMI). The current study, in the same subject, immediately followed the previous work and expanded the scope of the control signal by also extracting hand-shape commands from the two 96-channel intracortical electrode arrays implanted in the subject’s left motor cortex. Approach. Four new control signals, dictating prosthetic hand shape, replaced the one-dimensional grasping in the previous study, allowing the subject to control the prosthetic limb with ten degrees of freedom (three-dimensional (3D) translation, 3D orientation, four-dimensional hand shaping) simultaneously. Main results. Robust neural tuning to hand shaping was found, leading to ten-dimensional (10D) performance well above chance levels in all tests. Neural unit preferred directions were broadly distributed through the 10D space, with the majority of units significantly tuned to all ten dimensions, instead of being restricted to isolated domains (e.g. translation, orientation or hand shape). The addition of hand shaping emphasized object-interaction behavior. A fundamental component of BMIs is the calibration used to associate neural activity to intended movement. We found that the presence of an object during calibration enhanced successful shaping of the prosthetic hand as it closed around the object during grasping. Significance. Our results show that individual motor cortical neurons encode many parameters of movement, that object interaction is an important factor when extracting these signals, and that high-dimensional operation of prosthetic devices can be achieved with simple decoding algorithms. ClinicalTrials.gov Identifier: NCT01364480.
Typically impedance control parameters (e.g., stiffness and damping) in powered lower limb prostheses are fine-tuned by human experts (HMEs), which is time and resource intensive. Automated tuning procedures would make powered prostheses more practical for clinical use. In this study, we developed a novel cyber expert system (CES) that encoded HME tuning decisions as computer rules to auto-tune control parameters for a powered knee (passive ankle) prosthesis. The tuning performance of CES was preliminarily quantified on two able-bodied subjects and two transfemoral amputees. After CES and HME tuning, we observed normative prosthetic knee kinematics and improved or slightly improved gait symmetry and step width within each subject. Compared to HME, the CES tuning procedure required less time and no human intervention. Hence, using CES for auto-tuning prosthesis control was a sound concept, promising to enhance the practical value of powered prosthetic legs. However, the tuning goals of CES might not fully capture those of the HME. This was because we observed that HME tuning reduced trunk sway, while CES sometimes led to slightly increased trunk motion. Additional research is still needed to identify more appropriate tuning objectives for powered prosthetic legs to improve amputees' walking function.
OBJECTIVE Global brachial plexus lesions with multiple root avulsions are among the most severe nerve injuries, leading to lifelong disability. Fortunately, in most cases primary and secondary reconstructions provide a stable shoulder and restore sufficient arm function. Restoration of biological hand function, however, remains a reconstructive goal that is difficult to reach. The recently introduced concept of bionic reconstruction overcomes biological limitations of classic reconstructive surgery to restore hand function by combining selective nerve and muscle transfers with elective amputation of the functionless hand and its replacement with a prosthetic device. The authors present their treatment algorithm for bionic hand reconstruction and report on the management and long-term functional outcomes of patients with global brachial plexopathies who have undergone this innovative treatment. METHODS Thirty-four patients with posttraumatic global brachial plexopathies leading to loss of hand function consulted the Center for Advanced Restoration of Extremity Function between 2011 and 2015. Of these patients, 16 (47%) qualified for bionic reconstruction due to lack of treatment alternatives. The treatment algorithm included progressive steps with the intent of improving the biotechnological interface to allow optimal prosthetic hand replacement. In 5 patients, final functional outcome measurements were obtained with the Action Arm Research Test (ARAT), the Southampton Hand Assessment Procedure (SHAP), and the Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire. RESULTS In all 5 patients who completed functional assessments, partial hand function was restored with bionic reconstruction. ARAT scores improved from 3.4 ± 4.3 to 25.4 ± 12.7 (p = 0.043; mean ± SD) and SHAP scores improved from 10.0 ± 1.6 to 55 ± 19.7 (p = 0.042). DASH scores decreased from 57.9 ± 20.6 to 32 ± 28.6 (p = 0.042), indicating decreased disability. CONCLUSIONS The authors present an algorithm for bionic reconstruction leading to useful hand function in patients who lack biological treatment alternatives for a stiff, functionless, and insensate hand resulting from global brachial plexopathies.
Robotic lower limb prostheses can improve the quality of life for amputees. Development of such devices, currently dominated by long prototyping periods, could be sped up by predictive simulations. In contrast to some amputee simulations which track experimentally determined non-amputee walking kinematics, here, we explicitly model the human-prosthesis interaction to produce a prediction of the user’s walking kinematics. We obtain simulations of an amputee using an ankle-foot prosthesis by simultaneously optimizing human movements and prosthesis actuation, minimizing a weighted sum of human metabolic and prosthesis costs. The resulting Pareto optimal solutions predict that increasing prosthesis energy cost, decreasing prosthesis mass, and allowing asymmetric gaits all decrease human metabolic rate for a given speed and alter human kinematics. The metabolic rates increase monotonically with speed. Remarkably, by performing an analogous optimization for a non-amputee human, we predict that an amputee walking with an appropriately optimized robotic prosthesis can have a lower metabolic cost - even lower than assuming that the non-amputee’s ankle torques are cost-free.
One of the earliest written references to prosthetics is found in a book published in France in 1579. That year, French surgeon Ambroise Paré (1510-1590) published his complete works, part of which described some of the artificial limbs he fitted on his amputees. As a military surgeon, Paré had removed many a soldier’s shattered arm or leg, and he eventually began designing and building artificial limbs to help the men who had been maimed.