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Iterative Learning Control (ILC) is a promising method for adapting neuromuscular electrical stimulation to facilitate independent walking after upper motor neuron paralysis. However, assumptions made by conventional ILC methods, such as identical initial conditions for each iteration, are unsustainable in the case of human gait. In this study, we implement a musculoskeletal model of a single leg to analyze the consequences of variable initial conditions for data-driven ILC-based stimulation (DDILC) during swing phase of gait. We show that DDILC converges in all tested cases of initial hip angle variability, but that noise arises because of such variability. For the maximum variability case, the output with the largest noise (i.e., the terminal ankle angle) had a standard deviation of 2.1 degrees. Thus, the noise due to initial hip angle variability is shown to be comparable in magnitude to the inherent variability in gait. We also show that exploding gradients and instability eventually occur because of varying initial conditions, but these can be mitigated with established techniques.

Seated stability is a major concern of individuals with trunk paralysis. Trunk paralysis is commonly caused by spinal cord injuries (SCI) at or above the thoracic spine. Current methods to improve stability restrict the movement of the user by constraining their trunk to an upright position. Feedback control of functional neuromuscular stimulation (FNS) can help maintain seated stability while still allowing the user to perform movements to accomplish functional tasks. In this study, an individual with a SCI (C7, AIS B) and an implanted stimulator capable of recruiting trunk and hip musculature unilaterally moved a weighted jar on a countertop to and from three prescribed stations directly in front, laterally, and across midline. For comparison, the tasks were performed with constant baseline stimulation and with feedback modulated stimulation based on the tilt of the trunk obtained from an external accelerometer fed into two PID controllers; one for forward trunk pitch and the other for lateral roll. The trunk pitch and roll angles were obtained through motion capture cameras and various measures of postural sway (95% fitted ellipse area, root mean squared (RMS), path length) and the repeatability (coefficient of variation (CoV), variance ratio (VR)) were calculated. Feedback control significantly increased RMS of trunk movement along the major axis of the fitted ellipse, but decreased RMS values during bending along the minor axis of motion. As a result, the fitted ellipse area decreased when deploying the jar to one of the stations and increased with the other two. The CoV indicated reduced variation in the presence of feedback controlled stimulation for all stations, and VR showed higher repeatability in trunk pitch. Plots of the trunk pitch and roll revealed a faster return to upright motion due to feedback stimulation.Clinical relevance- Feedback control in combination with FNS is a viable method to improve seated stability while still allowing dynamic movements in individuals with a SCI, thus addressing a major concern of the population.

An untethered version of a stimulation-driven exoskeleton was evaluated for its ability to restore walking after paralysis from spinal cord injury. The hybrid neuroprosthesis (HNP) combined a passive variable-constraint exoskeleton for stability and support with functional neuromuscular stimulation (FNS) to contract the paralyzed muscles to drive limb movement. This self-contained HNP was operated by an onboard controller that sampled sensor signals, generated appropriate commands to both the exoskeletal constraints and integrated stimulator, and transmitted data wirelessly via Bluetooth to an off-board computer for real-time monitoring and recording for offline analysis. The subject selected the desired function (i.e. standing up, stepping, or sitting down) by means of a wireless finger switch that communicated with the onboard controller. Within the stepping function, a gait event detector supervisory controller transitioned between the different phases of gait such as double stance, swing, and weight acceptance based on signals from sensors incorporated into the exoskeleton. The different states of the control system governed the locking and unlocking of the exoskeletal hip and knee joints as well as the stimulation patterns activating hip and knee flexor or extensor muscles at the appropriate times and intensities to enable stepping. This study was one of our first successful implementations of the self-contained "muscle-first" HNP and successfully restored gait to an individual with motor complete mid-thoracic paraplegia.

This study describes a method for optimizing selective stimulus parameters for multi-contact peripheral electrodes. Overlap between pairs of contacts is quantified by the deviation in their combined response from linear addition of their individual responses. Mathematical models are fit to recruitment and overlap data, and a cost function is defined to maximize recruitment and minimize overlap between all contacts. Results are presented for two four-contact nerve-cuff electrodes stimulating bilateral femoral nerves of one human subject with spinal cord injury. Knee extension moments between 11.6 and 17.2 Nm are achieved through two contacts of each nerve-cuff with less than 10% overlap between each pair of contacts. These results suggest that optimization can provide an automated means of determining stimulus parameters to achieve strong, selective muscle contractions through multi-contact peripheral nerve electrodes.

This paper describes a method to efficiently sample EMG recruitment space over a wide range of pulse amplitude (PA) and pulse width (PW). A gradient based search method is developed to find high information areas of a recruitment surface. This search method is first examined in the context of simulated EMG recruitment data and its ability to sample and subsequently fit Gompertz-Function-inspired surfaces to it. The search method is then used to determine parameters when stimulating through an 8 contact flat interface nerve electrode (FINE). The recorded EMG recruitment data are then used to validate the Gompertz surface fitting method as well as the search method.

Proper ankle control is critical to both standing balance and efficient walking. This study hypothesized that a Flat Interface Nerve Electrode (FINE) placed around the sciatic nerve with a fixed number of contacts at predetermined locations and without a priori knowledge of the nerve's underlying neuroanatomy can selectively control each ankle motion. Models of the human sciatic nerve surrounded by a FINE of varying size were created and used to calculate the probability of selective activation of axons within any arbitrarily designated group of fascicles. Simulations suggest that currently available implantable technology cannot selectively recruit each target plantar flexor individually but can restore plantar flexion or dorsiflexion from a site on the sciatic nerve without spillover to antagonists. Successful activation of individual ankle muscles in 90% of the population can be achieved by utilizing bipolar stimulation and/or by increasing the number of contacts within the cuff.

A hybrid neuroprosthesis (HNP) combines lower extremity bracing with functional neuromuscular stimulation (FNS) to restore walking function and enhance the efficiency of ambulation. This report details the development of a novel HNP containing a variable impedance knee mechanism (VIKM) capable of supporting the knee against collapse while allowing controlled stance phase knee flexion. The design of a closed loop, finite state controller for coordination of VIKM activity with FNS-driven gait is presented. The controller is verified in testing during able bodied gait. The improved functionality provided by this system has the potential to delay the onset of fatigue and to expand FNS driven gait to allow walking over uneven terrains and down stairs.

We have tested the hypothesis that the Flat Interface Nerve Electrode (FINE) can selectively stimulate each muscle innervated by the common femoral nerve of the human, near the inguinal ligament in a series of intraoperative trials. During routine vascular surgeries, an 8-contact FINE was placed around the common femoral nerve between the inguinal ligament and the first branching point. The efficacy of the FINE to selectively recruit muscles innervated by the femoral nerve was determined from electromyograms (EMGs) recorded in response to electrical stimulation. At least four of the six muscles innervated by the femoral nerve were selectively recruited in all subjects. Of these, at least one muscle was a hip flexor and two muscles were knee extensors. Results from the intraoperative experiments were used to estimate the potential for the electrode to restore knee extension and hip flexion through Functional Electrical Stimulation (FES). Normalized EMGs and biomechanical simulations were used to estimate joint moments and functional efficacy. Estimated knee extension moments exceed the threshold required for the sit-to-stand transition.