Stable, simultaneous and proportional 4-DoF prosthetic hand control via synergy-inspired linear interpolation: a case series.

BACKGROUND: Current commercial prosthetic hand controllers limit patients' ability to fully engage high Degree-of-Freedom (DoF) prosthetic hands. Available feedforward controllers rely on large training data sets for controller setup and a need for recalibration upon prosthesis donning. Recently, an intuitive, proportional, simultaneous, regression-based 3-DoF controller remained stable for several months without retraining by combining chronically implanted electromyography (ciEMG) electrodes with a K-Nearest-Neighbor (KNN) mapping technique. The training dataset requirements for simultaneous KNN controllers increase exponentially with DoF, limiting the realistic development of KNN controllers in more than three DoF. We hypothesize that a controller combining linear interpolation, the muscle synergy framework, and a sufficient number of ciEMG channels (at least two per DoF), can allow stable, high-DoF control. METHODS: Two trans-radial amputee subjects, S6 and S8, were implanted with percutaneously interfaced bipolar intramuscular electrodes. At the time of the study, S6 and S8 had 6 and 8 bipolar EMG electrodes, respectively. A Virtual Reality (VR) system guided users through single and paired training movements in one 3-DoF and four different 4-DoF cases. A linear model of user activity was built by partitioning EMG feature space into regions bounded by vectors of steady state movement EMG patterns. The controller evaluated online EMG signals by linearly interpolating the movement class labels for surrounding trained EMG movements. This yields a simultaneous, continuous, intuitive, and proportional controller. Controllers were evaluated in 3-DoF and 4-DoF through a target-matching task in which subjects controlled a virtual hand to match 80 targets spanning the available movement space. Match Percentage, Time-To-Target, and Path Efficiency were evaluated over a 10-month period based on subject availability. RESULTS AND CONCLUSIONS: In 3-DoF, S6 and S8 matched most targets and demonstrated stable control after 8 and 10 months, respectively. In 4-DoF, both subjects initially found two of four 4-DoF controllers usable, matching most targets. S8 4-DoF controllers were stable, and showed improving trends over 7-9 months without retraining or at-home practice. S6 4-DoF controllers were unstable after 7 months without retraining. These results indicate that the performance of the controller proposed in this study may remain stable, or even improve, provided initial viability and a sufficient number of EMG channels. Overall, this study demonstrates a controller capable of stable, simultaneous, proportional, intuitive, and continuous control in 3-DoF for up to ten months and in 4-DoF for up to nine months without retraining or at-home use with minimal training times.

The Reconnecting the Hand and Arm with Brain (ReHAB) Commentary on "An Integrated Brain-Machine Interface Platform With Thousands of Channels".

Intracortical brain-machine interfaces are a promising technology for allowing people with chronic and severe neurological disorders that resulted in loss of function to potentially regain those functions through neuroprosthetic devices. The penetrating microelectrode arrays used in almost all previous studies of intracortical brain-machine interfaces in people had a limited recording life (potentially due to issues with long-term biocompatibility), as well as a limited number of recording electrodes with limited distribution in the brain. Significant advances are required in this array interface to deal with the issues of long-term biocompatibility and lack of distributed recordings. The Musk and Neuralink manuscript proposes a novel and potentially disruptive approach to advancing the brain-electrode interface technology, with the potential of addressing many of these hurdles. Our commentary addresses the potential advantages of the proposed approach, as well as the remaining challenges to be addressed.

Stable, three degree-of-freedom myoelectric prosthetic control via chronic bipolar intramuscular electrodes: a case study.

BACKGROUND: Modern prosthetic hands are typically controlled using skin surface electromyographic signals (EMG) from remaining muscles in the residual limb. However, surface electrode performance is limited by changes in skin impedance over time, day-to-day variations in electrode placement, and relative motion between the electrodes and underlying muscles during movement: these limitations require frequent retraining of controllers. In the presented study, we used chronically implanted intramuscular electrodes to minimize these effects and thus create a more robust prosthetic controller. METHODS: A study participant with a transradial amputation was chronically implanted with 8 intramuscular EMG electrodes. A K Nearest Neighbor (KNN) regression velocity controller was trained to predict intended joint movement direction using EMG data collected during a single training session. The resulting KNN was evaluated over 12 weeks and in multiple arm posture configurations, with the participant controlling a 3 Degree-of-Freedom (DOF) virtual reality (VR) hand to match target VR hand postures. The performance of this EMG-based controller was compared to a position-based controller that used movement measured from the participant's opposite (intact) hand. Surface EMG was also collected for signal quality comparisons. RESULTS: Signals from the implanted intramuscular electrodes exhibited less crosstalk between the various channels and had a higher Signal-to-Noise Ratio than surface electrode signals. The performance of the intramuscular EMG-based KNN controller in the VR control task showed no degradation over time, and was stable over the 6 different arm postures. Both the EMG-based KNN controller and the intact hand-based controller had 100% hand posture matching success rates, but the intact hand-based controller was slightly superior in regards to speed (trial time used) and directness of the VR hand control (path efficiency). CONCLUSIONS: Chronically implanted intramuscular electrodes provide negligible crosstalk, high SNR, and substantial VR control performance, including the ability to use a fixed controller over 12 weeks and under different arm positions. This approach can thus be a highly effective platform for advanced, multi-DOF prosthetic control.

Restoration of reaching and grasping movements through brain-controlled muscle stimulation in a person with tetraplegia: a proof-of-concept demonstration.

BACKGROUND: People with chronic tetraplegia, due to high-cervical spinal cord injury, can regain limb movements through coordinated electrical stimulation of peripheral muscles and nerves, known as functional electrical stimulation (FES). Users typically command FES systems through other preserved, but unrelated and limited in number, volitional movements (eg, facial muscle activity, head movements, shoulder shrugs). We report the findings of an individual with traumatic high-cervical spinal cord injury who coordinated reaching and grasping movements using his own paralysed arm and hand, reanimated through implanted FES, and commanded using his own cortical signals through an intracortical brain-computer interface (iBCI). METHODS: We recruited a participant into the BrainGate2 clinical trial, an ongoing study that obtains safety information regarding an intracortical neural interface device, and investigates the feasibility of people with tetraplegia controlling assistive devices using their cortical signals. Surgical procedures were performed at University Hospitals Cleveland Medical Center (Cleveland, OH, USA). Study procedures and data analyses were performed at Case Western Reserve University (Cleveland, OH, USA) and the US Department of Veterans Affairs, Louis Stokes Cleveland Veterans Affairs Medical Center (Cleveland, OH, USA). The study participant was a 53-year-old man with a spinal cord injury (cervical level 4, American Spinal Injury Association Impairment Scale category A). He received two intracortical microelectrode arrays in the hand area of his motor cortex, and 4 months and 9 months later received a total of 36 implanted percutaneous electrodes in his right upper and lower arm to electrically stimulate his hand, elbow, and shoulder muscles. The participant used a motorised mobile arm support for gravitational assistance and to provide humeral abduction and adduction under cortical control. We assessed the participant's ability to cortically command his paralysed arm to perform simple single-joint arm and hand movements and functionally meaningful multi-joint movements. We compared iBCI control of his paralysed arm with that of a virtual three-dimensional arm. This study is registered with ClinicalTrials.gov, number NCT00912041. FINDINGS: The intracortical implant occurred on Dec 1, 2014, and we are continuing to study the participant. The last session included in this report was Nov 7, 2016. The point-to-point target acquisition sessions began on Oct 8, 2015 (311 days after implant). The participant successfully cortically commanded single-joint and coordinated multi-joint arm movements for point-to-point target acquisitions (80-100% accuracy), using first a virtual arm and second his own arm animated by FES. Using his paralysed arm, the participant volitionally performed self-paced reaches to drink a mug of coffee (successfully completing 11 of 12 attempts within a single session 463 days after implant) and feed himself (717 days after implant). INTERPRETATION: To our knowledge, this is the first report of a combined implanted FES+iBCI neuroprosthesis for restoring both reaching and grasping movements to people with chronic tetraplegia due to spinal cord injury, and represents a major advance, with a clear translational path, for clinically viable neuroprostheses for restoration of reaching and grasping after paralysis. FUNDING: National Institutes of Health, Department of Veterans Affairs.

Evaluation of head orientation and neck muscle EMG signals as three-dimensional command sources.

BACKGROUND: High cervical spinal cord injuries result in significant functional impairments and affect both the injured individual as well as their family and care givers. To help restore function to these individuals, multiple user interfaces are available to enable command and control of external devices. However, little work has been performed to assess the 3D performance of these interfaces. METHODS: We investigated the performance of eight human subjects in using three user interfaces (head orientation, EMG from muscles of the head and neck, and a three-axis joystick) to command the endpoint position of a multi-axis robotic arm within a 3D workspace to perform a novel out-to-center 3D Fitts' Law style task. Two of these interfaces (head orientation, EMG from muscles of the head and neck) could realistically be used by individuals with high tetraplegia, while the joystick was evaluated as a standard of high performance. Performance metrics were developed to assess the aspects of command source performance. Data were analyzed using a mixed model design ANOVA. Fixed effects were investigated between sources as well as for interactions between index of difficulty, command source, and the five performance measures used. A 5% threshold for statistical significance was used in the analysis. RESULTS: The performances of the three command interfaces were rather similar, though significant differences between command sources were observed. The apparent similarity is due in large part to the sequential command strategy (i.e., one dimension of movement at a time) typically adopted by the subjects. EMG-based commands were particularly pulsatile in nature. The use of sequential commands had a significant impact on each command source's performance for movements in two or three dimensions. CONCLUSIONS: While the sequential nature of the commands produced by the user did not fit with Fitts' Law, the other performance measures used were able to illustrate the properties of each command source. Though pulsatile, given the overall similarity between head orientation and the EMG interface, (which also could be readily included in a future implanted neuroprosthesis) the use of EMG as a command source for controlling an arm in 3D space is an attractive choice.

Implanted neuroprosthesis for restoring arm and hand function in people with high level tetraplegia.

OBJECTIVE: To develop and apply an implanted neuroprosthesis to restore arm and hand function to individuals with high level tetraplegia. DESIGN: Case study. SETTING: Clinical research laboratory. PARTICIPANTS: Individuals with spinal cord injuries (N=2) at or above the C4 motor level. INTERVENTIONS: The individuals were each implanted with 2 stimulators (24 stimulation channels and 4 myoelectric recording channels total). Stimulating electrodes were placed in the shoulder and arm, being, to our knowledge, the first long-term application of spiral nerve cuff electrodes to activate a human limb. Myoelectric recording electrodes were placed in the head and neck areas. MAIN OUTCOME MEASURES: Successful installation and operation of the neuroprosthesis and electrode performance, range of motion, grasp strength, joint moments, and performance in activities of daily living. RESULTS: The neuroprosthesis system was successfully implanted in both individuals. Spiral nerve cuff electrodes were placed around upper extremity nerves and activated the intended muscles. In both individuals, the neuroprosthesis has functioned properly for at least 2.5 years postimplant. Hand, wrist, forearm, elbow, and shoulder movements were achieved. A mobile arm support was needed to support the mass of the arm during functional activities. One individual was able to perform several activities of daily living with some limitations as a result of spasticity. The second individual was able to partially complete 2 activities of daily living. CONCLUSIONS: Functional electrical stimulation is a feasible intervention for restoring arm and hand functions to individuals with high tetraplegia. Forces and movements were generated at the hand, wrist, elbow, and shoulder that allowed the performance of activities of daily living, with some limitations requiring the use of a mobile arm support to assist the stimulated shoulder forces.

A fully implanted intramuscular bipolar myoelectric signal recording electrode.

OBJECTIVES: The objective of this study is to develop a fully implanted, intramuscular, bipolar, myoelectric signal (IM-MES) recording electrode for functional electrical stimulation (FES), prosthetic myoelectric control, and other permanently implantable systems. MATERIALS AND METHODS: An existing fully implanted intramuscular stimulating electrode was modified at each end to allow bipolar recording. The design change also required a modification of the implantation method. Mechanical and in vivo testing was performed on the novel components of the electrode. The first clinical application also is described. RESULTS: The electrode design modifications did not create any areas of excess mechanical strain on the wires at the distal end where the leads were wound into electrode surfaces. In vivo testing showed that the IM-MES electrode recorded myoelectric signals that were equivalent to an existing epimysial MES electrode. The modified implantation method was simple to implement. The IM-MES electrode was used in an upper extremity FES system in an individual with a spinal cord injury and provided signals that were suitable for a command signal. CONCLUSIONS: A fully implanted, bipolar intramuscular recording electrode (IM-MES) was developed. Implantation of the IM-MES is straightforward, and almost any muscle can be targeted. Testing has been performed to demonstrate the suitability of the IM-MES electrode for clinical use. Initial clinical applications were successful.

Peripheral nerve blocks of wrist and finger flexors can increase hand opening in chronic hemiparetic stroke.

Introduction: Hand opening is reduced by abnormal wrist and finger flexor activity in many individuals with stroke. This flexor activity also limits hand opening produced by functional electrical stimulation (FES) of finger and wrist extensor muscles. Recent advances in electrical nerve block technologies have the potential to mitigate this abnormal flexor behavior, but the actual impact of nerve block on hand opening in stroke has not yet been investigated. Methods: In this study, we applied the local anesthetic ropivacaine to the median and ulnar nerve to induce a complete motor block in 9 individuals with stroke and observed the impact of this block on hand opening as measured by hand pentagonal area. Volitional hand opening and FES-driven hand opening were measured, both while the arm was fully supported on a haptic table (Unloaded) and while lifting against gravity (Loaded). Linear mixed effect regression (LMER) modeling was used to determine the effect of Block. Results: The ropivacaine block allowed increased hand opening, both volitional and FES-driven, and for both unloaded and loaded conditions. Notably, only the FES-driven and Loaded condition's improvement in hand opening with the block was statistically significant. Hand opening in the FES and Loaded condition improved following nerve block by nearly 20%. Conclusion: Our results suggest that many individuals with stroke would see improved hand-opening with wrist and finger flexor activity curtailed by nerve block, especially when FES is used to drive the typically paretic finger and wrist extensor muscles. Such a nerve block (potentially produced by aforementioned emerging electrical nerve block technologies) could thus significantly address prior observed shortcomings of FES interventions for individuals with stroke.

Reconnecting the Hand and Arm to the Brain: Efficacy of Neural Interfaces for Sensorimotor Restoration After Tetraplegia.

BACKGROUND AND OBJECTIVES: Paralysis after spinal cord injury involves damage to pathways that connect neurons in the brain to peripheral nerves in the limbs. Re-establishing this communication using neural interfaces has the potential to bridge the gap and restore upper extremity function to people with high tetraplegia. We report a novel approach for restoring upper extremity function using selective peripheral nerve stimulation controlled by intracortical microelectrode recordings from sensorimotor networks, along with restoration of tactile sensation of the hand using intracortical microstimulation. METHODS: A 27-year-old right-handed man with AIS-B (motor-complete, sensory-incomplete) C3-C4 tetraplegia was enrolled into the clinical trial. Six 64-channel intracortical microelectrode arrays were implanted into left hemisphere regions involved in upper extremity function, including primary motor and sensory cortices, inferior frontal gyrus, and anterior intraparietal area. Nine 16-channel extraneural peripheral nerve electrodes were implanted to allow targeted stimulation of right median, ulnar (2), radial, axillary, musculocutaneous, suprascapular, lateral pectoral, and long thoracic nerves, to produce selective muscle contractions on demand. Proof-of-concept studies were performed to demonstrate feasibility of using a brain-machine interface to read from and write to the brain for restoring motor and sensory functions of the participant's own arm and hand. RESULTS: Multiunit neural activity that correlated with intended motor action was successfully recorded from intracortical arrays. Microstimulation of electrodes in somatosensory cortex produced repeatable sensory percepts of individual fingers for restoration of touch sensation. Selective electrical activation of peripheral nerves produced antigravity muscle contractions, resulting in functional movements that the participant was able to command under brain control to perform virtual and actual arm and hand movements. The system was well tolerated with no operative complications. CONCLUSION: The combination of implanted cortical electrodes and nerve cuff electrodes has the potential to create bidirectional restoration of motor and sensory functions of the arm and hand after neurological injury.

Grand Challenges at the Interface of Engineering and Medicine.

Over the past two decades Biomedical Engineering has emerged as a major discipline that bridges societal needs of human health care with the development of novel technologies. Every medical institution is now equipped at varying degrees of sophistication with the ability to monitor human health in both non-invasive and invasive modes. The multiple scales at which human physiology can be interrogated provide a profound perspective on health and disease. We are at the nexus of creating "avatars" (herein defined as an extension of "digital twins") of human patho/physiology to serve as paradigms for interrogation and potential intervention. Motivated by the emergence of these new capabilities, the IEEE Engineering in Medicine and Biology Society, the Departments of Biomedical Engineering at Johns Hopkins University and Bioengineering at University of California at San Diego sponsored an interdisciplinary workshop to define the grand challenges that face biomedical engineering and the mechanisms to address these challenges. The Workshop identified five grand challenges with cross-cutting themes and provided a roadmap for new technologies, identified new training needs, and defined the types of interdisciplinary teams needed for addressing these challenges. The themes presented in this paper include: 1) accumedicine through creation of avatars of cells, tissues, organs and whole human; 2) development of smart and responsive devices for human function augmentation; 3) exocortical technologies to understand brain function and treat neuropathologies; 4) the development of approaches to harness the human immune system for health and wellness; and 5) new strategies to engineer genomes and cells.

The Impact of Hill-Type Actuator Components on the Performance of Reinforcement Learning Controllers to Reverse Upper-Limb Paralysis.

Functional electrical stimulation (FES) may allow people who are paralyzed due to spinal cord injuries (SCIs) to regain the ability to move. Deep neural networks (DNNs) trained with reinforcement learning (RL) have been recently explored as a promising methodology to control FES systems to restore upper-limb movements. However, previous studies suggested that large asymmetries in antagonistic upper-limb muscle strengths could impair RL controller performance. In this work, we investigated the underlying causes of asymmetry-associated decreases in controller performance by comparing different Hill-type models of muscle atrophy, and by characterizing RL controller sensitivity to passive mechanical properties of the arm. Simulations indicated that RL controller performance is relatively insensitive to moderate (up to 50%) changes in tendon stiffness and in flexor muscle stiffness. However, the viable workspace for RL control was substantially affected by flexor muscle weakness and by extensor muscle stiffness. Furthermore, we uncovered that RL controller performance issues previously attributed to asymmetrical antagonistic muscle strength resulted from flexor muscle active forces that were insufficient to counteract extensor muscle passive resistance. The simulations supported the adoption of rehabilitation protocols for reaching tasks that prioritize decreasing muscle passive resistance, and counteracting passive resistance with increased antagonistic muscle strength.

Implanted Electrodes for Functional Electrical Stimulation to Restore Upper and Lower Extremity Function: History and Future Directions.

Functional electrical stimulation (FES) to activate nerves and muscles in paralyzed extremities has considerable promise to improve outcome after neurological disease or injury, especially in individuals who have upper motor nerve dysfunction due to central nervous system pathology. Because technology has improved, a wide variety of methods for providing electrical stimulation to create functional movements have been developed, including muscle stimulating electrodes, nerve stimulating electrodes, and hybrid constructs. However, in spite of decades of success in experimental settings with clear functional improvements for individuals with paralysis, the technology has not yet reached widespread clinical translation. In this review, we outline the history of FES techniques and approaches and describe future directions in evolution of the technology.

Reconnecting the Hand and Arm to the Brain: Efficacy of Neural Interfaces for Sensorimotor Restoration after Tetraplegia.

Background: Paralysis after spinal cord injury involves damage to pathways that connect neurons in the brain to peripheral nerves in the limbs. Re-establishing this communication using neural interfaces has the potential to bridge the gap and restore upper extremity function to people with high tetraplegia. Objective: We report a novel approach for restoring upper extremity function using selective peripheral nerve stimulation controlled by intracortical microelectrode recordings from sensorimotor networks, along with restoration of tactile sensation of the hand using intracortical microstimulation. Methods: A right-handed man with motor-complete C3-C4 tetraplegia was enrolled into the clinical trial. Six 64-channel intracortical microelectrode arrays were implanted into left hemisphere regions involved in upper extremity function, including primary motor and sensory cortices, inferior frontal gyrus, and anterior intraparietal area. Nine 16-channel extraneural peripheral nerve electrodes were implanted to allow targeted stimulation of right median, ulnar (2), radial, axillary, musculocutaneous, suprascapular, lateral pectoral, and long thoracic nerves, to produce selective muscle contractions on demand. Proof-of-concept studies were performed to demonstrate feasibility of a bidirectional brain-machine interface to restore function of the participant's own arm and hand. Results: Multi-unit neural activity that correlated with intended motor action was successfully recorded from intracortical arrays. Microstimulation of electrodes in somatosensory cortex produced repeatable sensory percepts of individual fingers for restoration of touch sensation. Selective electrical activation of peripheral nerves produced antigravity muscle contractions. The system was well tolerated with no operative complications. Conclusion: The combination of implanted cortical electrodes and nerve cuff electrodes has the potential to allow restoration of motor and sensory functions of the arm and hand after neurological injury.

Interim Safety Profile From the Feasibility Study of the BrainGate Neural Interface System.

BACKGROUND AND OBJECTIVES: Brain-computer interfaces (BCIs) are being developed to restore mobility, communication, and functional independence to people with paralysis. Though supported by decades of preclinical data, the safety of chronically implanted microelectrode array BCIs in humans is unknown. We report safety results from the prospective, open-label, nonrandomized BrainGate feasibility study (NCT00912041), the largest and longest-running clinical trial of an implanted BCI. METHODS: Adults aged 18-75 years with quadriparesis from spinal cord injury, brainstem stroke, or motor neuron disease were enrolled through 7 clinical sites in the United States. Participants underwent surgical implantation of 1 or 2 microelectrode arrays in the motor cortex of the dominant cerebral hemisphere. The primary safety outcome was device-related serious adverse events (SAEs) requiring device explantation or resulting in death or permanently increased disability during the 1-year postimplant evaluation period. The secondary outcomes included the type and frequency of other adverse events and the feasibility of the BrainGate system for controlling a computer or other assistive technologies. RESULTS: From 2004 to 2021, 14 adults enrolled in the BrainGate trial had devices surgically implanted. The average duration of device implantation was 872 days, yielding 12,203 days of safety experience. There were 68 device-related adverse events, including 6 device-related SAEs. The most common device-related adverse event was skin irritation around the percutaneous pedestal. There were no safety events that required device explantation, no unanticipated adverse device events, no intracranial infections, and no participant deaths or adverse events resulting in permanently increased disability related to the investigational device. DISCUSSION: The BrainGate Neural Interface system has a safety record comparable with other chronically implanted medical devices. Given rapid recent advances in this technology and continued performance gains, these data suggest a favorable risk/benefit ratio in appropriately selected individuals to support ongoing research and development. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov Identifier: NCT00912041. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that the neurosurgically placed BrainGate Neural Interface system is associated with a low rate of SAEs defined as those requiring device explantation, resulting in death, or resulting in permanently increased disability during the 1-year postimplant period.

Tessellation of artificial touch via microstimulation of human somatosensory cortex.

When we interact with objects, we rely on signals from the hand that convey information about the object and our interaction with it. A basic feature of these interactions, the locations of contacts between the hand and object, is often only available via the sense of touch. Information about locations of contact between a brain-controlled bionic hand and an object can be signaled via intracortical microstimulation (ICMS) of somatosensory cortex (S1), which evokes touch sensations that are localized to a specific patch of skin. To provide intuitive location information, tactile sensors on the robotic hand drive ICMS through electrodes that evoke sensations at skin locations matching sensor locations. This approach requires that ICMS-evoked sensations be focal, stable, and distributed over the hand. To systematically investigate the localization of ICMS-evoked sensations, we analyzed the projected fields (PFs) of ICMS-evoked sensations - their location and spatial extent - from reports obtained over multiple years from three participants implanted with microelectrode arrays in S1. First, we found that PFs vary widely in their size across electrodes, are highly stable within electrode, are distributed over large swaths of each participant's hand, and increase in size as the amplitude or frequency of ICMS increases. Second, while PF locations match the locations of the receptive fields (RFs) of the neurons near the stimulating electrode, PFs tend to be subsumed by the corresponding RFs. Third, multi-channel stimulation gives rise to a PF that reflects the conjunction of the PFs of the component channels. By stimulating through electrodes with largely overlapping PFs, then, we can evoke a sensation that is experienced primarily at the intersection of the component PFs. To assess the functional consequence of this phenomenon, we implemented multichannel ICMS-based feedback in a bionic hand and demonstrated that the resulting sensations are more localizable than are those evoked via single-channel ICMS.

Trunk acceleration for neuroprosthetic control of standing: a pilot study.

This pilot study investigated the potential of using trunk acceleration feedback control of center of pressure (COP) against postural disturbances with a standing neuroprosthesis following paralysis. Artificial neural networks (ANNs) were trained to use three-dimensional trunk acceleration as input to predict changes in COP for able-bodied subjects undergoing perturbations during bipedal stance. Correlation coefficients between ANN predictions and actual COP ranged from 0.67 to 0.77. An ANN trained across all subject-normalized data was used to drive feedback control of ankle muscle excitation levels for a computer model representing a standing neuroprosthesis user. Feedback control reduced average upper-body loading during perturbation onset and recovery by 42% and peak loading by 29% compared with optimal, constant excitation.

Improving the Learning Rate, Accuracy, and Workspace of Reinforcement Learning Controllers for a Musculoskeletal Model of the Human Arm.

Cervical spinal cord injuries frequently cause paralysis of all four limbs - a medical condition known as tetraplegia. Functional electrical stimulation (FES), when combined with an appropriate controller, can be used to restore motor function by electrically stimulating the neuromuscular system. Previous works have demonstrated that reinforcement learning can be used to successfully train FES controllers. Here, we demonstrate that transfer learning and curriculum learning can be used to improve the learning rates, accuracies, and workspaces of FES controllers that are trained using reinforcement learning.

Deep Reinforcement Learning for Control of Time-Varying Musculoskeletal Systems With High Fatigability: A Feasibility Study.

Functional electrical stimulation (FES) can be used to restore motor function to people with paralysis caused by spinal cord injuries (SCIs). However, chronically-paralyzed FES-stimulated muscles can fatigue quickly, which may decrease FES controller performance. In this work, we explored the feasibility of using deep neural network (DNN) controllers trained with reinforcement learning (RL) to control FES of upper-limb muscles after SCI. We developed upper-limb biomechanical models that exhibited increased muscle fatigability, decreased muscle recovery, and decreased muscle strength, as observed in people with chronic SCIs. Simulations confirmed that controller training time and controller performance are impaired to varying degrees by muscle fatigability. Also, the simulations showed that large muscle strength asymmetries between opposing muscles can substantially impair controller performance. However, the results of this study suggest that controller performance for highly-fatigable musculoskeletal systems can be preserved by allowing for rest between movements. Overall, the results suggest that RL can be used to successfully train FES controllers, even for highly-fatigable musculoskeletal systems.

Virtual reality environment for simulating tasks with a myoelectric prosthesis: an assessment and training tool.

Intuitively and efficiently controlling multiple degrees of freedom is a major hurdle in the field of upper limb prosthetics. A virtual reality myoelectric transhumeral prosthesis simulator has been developed for cost-effectively testing novel control algorithms and devices. The system acquires EMG commands and residual limb kinematics, simulates the prosthesis dynamics, and displays the combined residual limb and prosthesis movements in a virtual reality environment that includes force-based interactions with virtual objects. A virtual Box and Block Test is demonstrated. Three normally-limbed subjects performed the simulated test using a sequential and a synchronous control method. With the sequential method, subjects moved on average 6.7±1.9 blocks in 120 seconds, similar to the number of blocks transhumeral amputees are able to move with their physical prostheses during clinical evaluation. With the synchronous method, subjects moved 6.7±2.2 blocks. The virtual reality prosthesis simulator is thus a promising tool for developing and evaluating control methods, prototyping novel prostheses, and training amputees.

Hindsight Experience Replay Improves Reinforcement Learning for Control of a MIMO Musculoskeletal Model of the Human Arm.

High-level spinal cord injuries often result in paralysis of all four limbs, leading to decreased patient independence and quality of life. Coordinated functional electrical stimulation (FES) of paralyzed muscles can be used to restore some motor function in the upper extremity. To coordinate functional movements, FES controllers should be developed to exploit the complex characteristics of human movement and produce the intended movement kinematics and/or kinetics. Here, we demonstrate the ability of a controller trained using reinforcement learning to generate desired movements of a horizontal planar musculoskeletal model of the human arm with 2 degrees of freedom and 6 actuators. The controller is given information about the kinematics of the arm, but not the internal state of the actuators. In particular, we demonstrate that a technique called "hindsight experience replay" can improve controller performance while also decreasing controller training time.