Robert F. Kirsch

EMG-based prediction of shoulder and elbow kinematics in able-bodied and spinal cord injured individuals

We have evaluated the ability of a time-delayed artificial neural network (TDANN) to predict shoulder and elbow motions using only electromyographic (EMG) signals recorded from six shoulder and elbow muscles as inputs, both in able-bodied subjects and in subjects with tetraplegia arising from C5 spinal cord injury. For able-bodied subjects, all four joint angles (elbow flexion-extension and shoulder horizontal flexion-extension, elevation-depression, and internal-external rotation) were predicted with average root-mean-square (rms) errors of less than 20 degrees during movements of widely different complexities performed at different speeds and with different hand loads. The corresponding angular velocities and angular accelerations were predicted with even lower relative errors. For individuals with C5 tetraplegia, the absolute rms errors of the joint angles, velocities, and accelerations were actually smaller than for able-bodied subjects, but the relative errors were similar when the smaller movement ranges of the C5 subjects were taken into account. These results indicate that the EMG signals from shoulder and elbow muscles contain a significant amount of information about arm moVement kinematics that could be exploited to develop advanced control systems for augmenting or restoring shoulder and elbow movements to individuals with tetraplegia using functional neuromuscular stimulation of paralyzed muscles.

Effects of voluntary force generation on the elastic components of endpoint stiffness

Abstract. The goal of this work was to determine how force loads applied at the hand change the elastic mechanical properties of the arm. Endpoint stiffness, which characterizes the relationship between hand displacements and the forces required to effect those displacements, was estimated during the application of planar, stochastic displacement perturbations to the human arm. A nonparametric system identification algorithm was used to estimate endpoint stiffness from the measured force and displacement data. We found that changes in the elastic component of arm stiffness during isometric force regulation tasks were due primarily to the actions of the single-joint muscles spanning the shoulder and elbow. This was shown to result in a nearly posture-independent regulation of joint torque-stiffness relationships, suggesting a simplified strategy that is used to regulate arm mechanics during these tasks.

An elbow extension neuroprosthesis for individuals with tetraplegia

Functional electrical stimulation (FES) of the triceps to restore control of elbow extension was integrated into a portable hand grasp neuroprosthesis for use by people with cervical level spinal cord injury. An accelerometer mounted on the upper arm activated triceps stimulation when the arm was raised above a predetermined threshold angle. Elbow posture was controlled by the subjects voluntarily flexing to counteract the stimulated elbow extension. The elbow moments created by the stimulated triceps were at least 4 N.m, which was sufficient to extend the arm against gravity. Electrical stimulation of the triceps increased the range of locations and orientations in the workspace over which subjects could grasp and move objects. In addition, object acquisition speed was increased. Thus elbow extension enhances a persons ability to grasp and manipulate objects in an unstructured environment.

Toward the Restoration of Hand Use to a Paralyzed Monkey: Brain-Controlled Functional Electrical Stimulation of Forearm Muscles

Loss of hand use is considered by many spinal cord injury survivors to be the most devastating consequence of their injury. Functional electrical stimulation (FES) of forearm and hand muscles has been used to provide basic, voluntary hand grasp to hundreds of human patients. Current approaches typically grade pre-programmed patterns of muscle activation using simple control signals, such as those derived from residual movement or muscle activity. However, the use of such fixed stimulation patterns limits hand function to the few tasks programmed into the controller. In contrast, we are developing a system that uses neural signals recorded from a multi-electrode array implanted in the motor cortex; this system has the potential to provide independent control of multiple muscles over a broad range of functional tasks. Two monkeys were able to use this cortically controlled FES system to control the contraction of four forearm muscles despite temporary limb paralysis. The amount of wrist force the monkeys were able to produce in a one-dimensional force tracking task was significantly increased. Furthermore, the monkeys were able to control the magnitude and time course of the force with sufficient accuracy to track visually displayed force targets at speeds reduced by only one-third to one-half of normal. Although these results were achieved by controlling only four muscles, there is no fundamental reason why the same methods could not be scaled up to control a larger number of muscles. We believe these results provide an important proof of concept that brain-controlled FES prostheses could ultimately be of great benefit to paralyzed patients with injuries in the mid-cervical spinal cord.

Multijoint dynamics and postural stability of the human arm

The goal of this study was to examine how the mechanical properties of the human arm are modulated during isometric force regulation tasks. Specifically, we examined whether the dynamic stability of the limb remained nearly invariant across a range of voluntarily generated endpoint forces and limb postures. Previous single joint studies have demonstrated that dynamic joint stability, as quantified via estimates of the joint damping ratio, is nearly invariant during isometric torque regulation tasks. However, the relevance of these findings to the control of multijoint posture has not been investigated previously. A similar degree of invariance at the multijoint level could suggest a fundamental property of the motor system that could be incorporated into the planning and execution of multijoint tasks. In this work, limb mechanics were quantified using estimates of dynamic endpoint stiffness, which characterizes the relationship between imposed displacements of limb posture and the forces opposing those displacements. Endpoint stiffness was estimated using a two-link robot operating in the horizontal plane at the height of each subject’s glenohumeral joint. The robot was used to apply stochastic position perturbations to the arm and to measure the resulting forces. Endpoint stiffness dynamics were estimated nonparametrically and subsequently summarized using inertial, viscous and elastic parameters. We found that in the tasks studied, there was a differential modulation of endpoint elasticity and endpoint viscosity. Elasticity increased nearly linearly with increases in voluntary force generation while viscosity increased nonlinearly. This differential regulation resulted in limb dynamics that had a remarkably consistent damping ratio across all subjects and all tested conditions. These results emphasize the importance of considering the full dynamic response of a limb when investigating multijoint stability, and suggest that a minimal degree of limb stability is maintained over a wide range of force regulation tasks.

Multiple-input, multiple-output system identification for characterization of limb stiffness dynamics.

Abstract. This study presents time-domain and frequency-domain, multiple-input, multiple-output (MIMO) linear system identification techniques that can be used to estimate the dynamic endpoint stiffness of a multijoint limb. The stiffness of a joint or limb arises from a number of physiological mechanisms and is thought to play a fundamental role in the control of posture and movement. Estimates of endpoint stiffness can therefore be used to characterize its modulation during physiological tasks and may provide insight into how the nervous system normally controls motor behavior. Previous MIMO stiffness estimates have focused upon the static stiffness components only or assumed simple parametric models with elastic, viscous, and inertial components. The method presented here captures the full stiffness dynamics during a relatively short experimental trial while assuming only that the system is linear for small perturbations. Simulation studies were performed to investigate the performance of this approach under typical experimental conditions. It was found that a linear MIMO description of endpoint stiffness dynamics was sufficient to describe the displacement responses to small stochastic force perturbations. Distortion of these linear estimates by nonlinear centripetal and Coriolis forces was virtually undetectable for these perturbations. The system identification techniques were also found to be robust in the presence of significant output measurement noise and input coupling. These results indicate that the approach described here will allow the estimation of endpoint stiffness dynamics in an experimentally efficient manner with minimal assumptions about the specific form of these properties.

Stimulation Stability and Selectivity of Chronically Implanted Multicontact Nerve Cuff Electrodes in the Human Upper Extremity

Nine spiral nerve cuff electrodes were implanted in two human subjects for up to three years with no adverse functional effects. The objective of this study was to look at the long term nerve and muscle response to stimulation through nerve cuff electrodes. The nerve conduction velocity remained within the clinically accepted range for the entire testing period. The stimulation thresholds stabilized after approximately 20 weeks. The variability in the activation over time was not different from muscle-based electrodes used in implanted functional electrical stimulation systems. Three electrodes had multiple, independent contacts to evaluate selective recruitment of muscles. A single muscle could be selectively activated from each electrode using single-contact stimulation and the selectivity was increased with the use of field steering techniques. The selectivity after three years was consistent with selectivity measured during the implant surgery. Nerve cuff electrodes are effective for chronic muscle activation and multichannel functional electrical stimulation in humans.

Continuous neuronal ensemble control of simulated arm reaching by a human with tetraplegia

Functional electrical stimulation (FES), the coordinated electrical activation of multiple muscles, has been used to restore arm and hand function in people with paralysis. User interfaces for such systems typically derive commands from mechanically unrelated parts of the body with retained volitional control, and are unnatural and unable to simultaneously command the various joints of the arm. Neural interface systems, based on spiking intracortical signals recorded from the arm area of motor cortex, have shown the ability to control computer cursors, robotic arms and individual muscles in intact non-human primates. Such neural interface systems may thus offer a more natural source of commands for restoring dexterous movements via FES. However, the ability to use decoded neural signals to control the complex mechanical dynamics of a reanimated human limb, rather than the kinematics of a computer mouse, has not been demonstrated. This study demonstrates the ability of an individual with long-standing tetraplegia to use cortical neuron recordings to command the real-time movements of a simulated dynamic arm. This virtual arm replicates the dynamics associated with arm mass and muscle contractile properties, as well as those of an FES feedback controller that converts user commands into the required muscle activation patterns. An individual with long-standing tetraplegia was thus able to control a virtual, two-joint, dynamic arm in real time using commands derived from an existing human intracortical interface technology. These results show the feasibility of combining such an intracortical interface with existing FES systems to provide a high-performance, natural system for restoring arm and hand function in individuals with extensive paralysis.

Combined feedforward and feedback control of a redundant, nonlinear, dynamic musculoskeletal system

A functional electrical stimulation controller is presented that uses a combination of feedforward and feedback for arm control in high-level injury. The feedforward controller generates the muscle activations nominally required for desired movements, and the feedback controller corrects for errors caused by muscle fatigue and external disturbances. The feedforward controller is an artificial neural network (ANN) which approximates the inverse dynamics of the arm. The feedback loop includes a PID controller in series with a second ANN representing the nonlinear properties and biomechanical interactions of muscles and joints. The controller was designed and tested using a two-joint musculoskeletal model of the arm that includes four mono-articular and two bi-articular muscles. Its performance during goal-oriented movements of varying amplitudes and durations showed a tracking error of less than 4° in ideal conditions, and less than 10° even in the case of considerable fatigue and external disturbances.

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

SUMMARY Background People with chronic tetraplegia due to high cervical spinal cord injury (SCI) 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 limited and unrelated, volitional movements (e.g. facial muscle activity, head movements). We demonstrate an individual with traumatic high cervical SCI performing coordinated reaching and grasping movements using his own paralyzed arm and hand, reanimated through FES, and commanded using his own cortical signals through an intracortical brain-computer-interface (iBCI). Methods The study participant (53 years old, C4, ASIA A) received two intracortical microelectrode arrays in the hand area of motor cortex, and 36 percutaneous electrodes for electrically stimulating hand, elbow, and shoulder muscles. The participant used a motorized mobile arm support for gravitational assistance and to provide humeral ab/adduction under cortical control. We assessed the participant’s ability to cortically command his paralyzed arm to perform simple single-joint arm/hand movements and functionally meaningful multi-joint movements. We compared iBCI control of his paralyzed arm to that of a virtual 3D arm. This study is registered with ClinicalTrials.gov, NCT00912041. Findings 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 paralyzed arm, the participant volitionally performed self-paced reaches to drink a mug of coffee (successfully completing 11 of 12 attempts within a single session) and feed himself. Interpretation This is the first demonstration of a combined FES+iBCI neuroprosthesis for both reaching and grasping for people with SCI resulting in chronic tetraplegia, and represents a major advance, with a clear translational path, for clinically viable neuroprostheses for restoring reaching and grasping post-paralysis.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 participants 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.