Neural prostheses (NPs) are electronic stimulators that activate nerves to restore sensory or motor functions. Surface NPs are non-invasive and inexpensive, but are often poorly selective, activating non-targeted muscles and cutaneous sensory nerves that can cause pain or discomfort. Implanted NPs are highly selective, but invasive and costly. The stimulus router system (SRS) is a novel NP consisting of fully implanted leads that capture and route some of the current flowing between a pair of surface electrodes to the vicinity of a target nerve. One end of an SRS lead has a pick-up terminal that is implanted subcutaneously under the location of a surface electrode and the other end has a delivery terminal that is secured on or near the target nerve. The studies presented in this thesis address the development of the SRS from animal testing to its implementation as an upper extremity NP in a tetraplegic subject. Chapters 2 and 3 describe the SRSs basic properties, provide proof-of-principle of the system in animal studies and identify aspects that maximize its performance as a motor NP. The studies showed that selective and graded activation of deep-lying nerves can be achieved with the SRS over the full physiological range. Long term reliability of the system was demonstrated in chronic animal studies. The surface current needed to activate nerves with a SRS was found to depend on the proximity of the delivery terminal(s) to the target nerve, contact areas of the surface electrodes and implanted terminals, electrode configuration and the distances from the surface anode to the surface cathode and delivery terminal. Chapter 4 describes the first human proof-of-principle of the SRS during an intra-operative test. Finally, Chapter 5 describes the implementation of the SRS for restoration of hand function in a tetraplegic subject. Stimulation parameters and force elicited through the SRS, along with usage of the device were monitored up to 10 months after implantation. The system was found to be useful, reliable and robust. It is argued that the results of these studies indicate that the SRS provides the basis for a new family of NPs.

More than one million people are living with spinal cord injury (SCI) in North America alone. Restoring lost motor function can alleviate SCI-related health problems, as well as markedly increase the quality of life enjoyed by individuals with SCI. Functional electrical stimulation (FES) can replace motor function in individuals with SCI by using short electrical pulses to generate contractions in paralyzed muscles. A wide range of FES applications have been proposed, but few application are actually available for community use by SCI consumers. A major factor contributing to this shortage of real-world FES applications is the lack of a feasible closed-loop control algorithm. The purpose of this thesis is to develop a closed-loop control algorithm that is suitable for use in practical FES applications. This thesis consists of three separate studies. The first study examined existing closed-loop control algorithms for FES applications, and showed that a method of testing FES control algorithms under realistic conditions is needed to evaluate their likely real-world performance. The second study provided such a testing method by developing a non-idealities block that can be used to modify the nominal response of electrically stimulated muscle in simulations of FES applications. Fatigue, muscle spasm, and tremor non-idealities are included in the block, which allows the user to specify the severity level for each type of non-ideal behaviour. This nonidealities block was tested in a simulation of electrically induced knee extension against gravity, and showed that the nominal performance of the controllers was substantially better than their performance in the realistic case that included the non-idealities model. The third study concerned the development and testing of a novel observer-based sliding mode control (SMC) algorithm that is suitable for use in real-world FES applications. This algorithm incorporated a fatigue minimization objective as well as co-contraction of the antagonist muscle group to cause the joint stiffness to track a desired value. The SMC algorithm was tested in a simulation of FES-based quiet standing, and the non-idealities block was used to determine the probable performance of the controller in the real world. This novel controller performed very well in simulation, and would be suitable for use in selected practical FES applications. The work contained in this thesis can easily be extended to a wide range of FES applications. This work represents a significant step forward in closed-loop control for FES applications, and will facilitate the development of sophisticated new electrical stimulation systems for use by consumers in their homes and communities.

More than one million people are living with spinal cord injury (SCI) in North America alone. Restoring lost motor function can alleviate SCI-related health problems, as well as markedly increase the quality of life enjoyed by individuals with SCI. Functional electrical stimulation (FES) can replace motor function in individuals with SCI by using short electrical pulses to generate contractions in paralyzed muscles. A wide range of FES applications have been proposed, but few application are actually available for community use by SCI consumers. A major factor contributing to this shortage of real-world FES applications is the lack of a feasible closed-loop control algorithm. The purpose of this thesis is to develop a closed-loop control algorithm that is suitable for use in practical FES applications. This thesis consists of three separate studies. The first study examined existing closed-loop control algorithms for FES applications, and showed that a method of testing FES control algorithms under realistic conditions is needed to evaluate their likely real-world performance. The second study provided such a testing method by developing a non-idealities block that can be used to modify the nominal response of electrically stimulated muscle in simulations of FES applications. Fatigue, muscle spasm, and tremor non-idealities are included in the block, which allows the user to specify the severity level for each type of non-ideal behaviour. This nonidealities block was tested in a simulation of electrically induced knee extension against gravity, and showed that the nominal performance of the controllers was substantially better than their performance in the realistic case that included the non-idealities model. The third study concerned the development and testing of a novel observer-based sliding mode control (SMC) algorithm that is suitable for use in real-world FES applications. This algorithm incorporated a fatigue minimization objective as well as co-contraction of the antagonist muscle group to cause the joint stiffness to track a desired value. The SMC algorithm was tested in a simulation of FES-based quiet standing, and the non-idealities block was used to determine the probable performance of the controller in the real world. This novel controller performed very well in simulation, and would be suitable for use in selected practical FES applications. The work contained in this thesis can easily be extended to a wide range of FES applications. This work represents a significant step forward in closed-loop control for FES applications, and will facilitate the development of sophisticated new electrical stimulation systems for use by consumers in their homes and communities.

A forward dynamic model was developed to predict the performance of Spinal Cord Injured (SCI) individuals cycling an isokinetic ergometer using Neuromuscular Electrical Stimulation (NMES) to elicit contractions of the quadriceps, hamstring and gluteal muscles. Computer simulations were performed using three inter-connected models: a kinematic model of segmental linkages, a muscle model predicting forces in response to stimulation, and a kinetic model predicting ergometer pedal forces resulting from muscle stimulation. Specific model parameters for SCI individuals were determined through measurements from isometric and isokinetic contractions of the quadriceps muscles elicited using surface stimulation. The muscle model was fitted to data resulting from these isolated experiments in order to tailor the model's parameters to characteristics of muscles from SCI individuals. Isometric data from a range of knee angles were used to fit tendon slack lengths to the rectus femoris and vastus muscles. Adjustments to the quadriceps moment arm function were not able to improve the match between measured and modelled knee extension torques beyond those using moment arms taken from available literature. Similarly, literature values for constants from the muscle force - velocity relationship provided a satisfactory fit to the decline in torque with angular velocity, and parameter fitting did not improve this fit. Passive visco-elastic resistance remained constant for all velocities of extension except the highest (240 deg/s). Since knee angular velocities this high were not experienced during cycling, a visco-elastic dampener was not included within the present cycling model. The rise and fall in torque following NMES onset and cessation were used to fit constants to match the rate of change in torque. Constants for the rise in torque following NMES onset were significantly altered by changes in knee angle, with more extended angles taking longer for torque to rise. This effect was small, however, within the range of angles used during cycling, and consequently was not included within the cycling model. The decline in torque after NMES cessation was not affected by knee angle. A period of five minutes cyclical isometric activity of the quadriceps resulted in torque declining by more than 75% from rested levels. The activation time constants were largely unaffected by this fatigue, however, with only a small increase in the time for torque to decline, and no change in rise time or the delay between stimulation changes and resulting torque changes. The cycling model, therefore, did not incorporate any effect for changes in activation timing with fatigue. Performance of the full model was evaluated through measurements taken from SCI individuals cycling a constant velocity ergometer using NMES elicited contractions of the quadriceps, hamstring and gluteal muscles. Pedal transducers measured forces applied to the pedals for comparison between measured and modelled values. A five minute period of continuous cycling using just the quadriceps muscles produced similar results to those found for isolated knee extension. External power output dropped by 50% over the five-minute period, however there was no change in the pattern of torque production with fatigue. Cycling experiments were conducted using single muscle groups across a range of NMES firing angles. Experimental protocols were designed to seek the firing angles for each muscle that maximised power output by that group. Changes in power output in response to firing angle changes were not large, however, in comparison to the effects of cumulative fatigue and inconsistent power output between trials. This lead to large uncertainties in the determination of those firing angles that maximised power output by each muscle. Results suggest that NMES firing angles to maximise power output by the quadriceps muscles were relatively similar for each subject. For the hamstring muscles, however, substantial differences were observed in the range of firing angles that maximised power output. Results for the gluteal muscles were variable, with some subjects not applying any measurable torque to the cranks, even with maximal stimulation applied. The model produced a good match to experimental data for the quadriceps muscles, both in the shape of pedal force curves and the firing angles that maximised external power output. The individual variability in hamstring responses was not, however, predicted by the model. Modification of the relative size of the hamstrings' moment arms about the hip and knee substantially improved the match between measured and modelled data. Analysis of results suggests that individual variability in the relative size of these moment arms is a major cause of variation in individual's response to hamstring stimulation. There were apparent limitations in the model's ability to predict the shape of crank torques resulting from stimulation of the gluteus maximus muscle. It is suggested that further research be conducted to enable modelling of this muscle using a range of fibre lengths and moment arms.

BACKGROUND: Accurate prediction of electromyographic (EMG) signals associated with a variety of motor behaviors could, in theory, serve as activity templates needed to evoke movements in paralyzed individuals using functional electrical stimulation. Such predictions should encompass complex multi-joint movements and include interactions with objects in the environment. METHODS: Here we tested the ability of different artificial neural networks (ANNs) to predict EMG activities of 12 arm muscles while human subjects made free movements of the arm or grasped and moved objects of different weights and dimensions. Inputs to the trained ANNs included hand position, hand orientation, and thumb grip force. RESULTS: The ability of ANNs to predict EMG was equally as good for tasks involving interactions with external loads as for unloaded movements. The ANN that yielded the best predictions was a feed-forward network consisting of a single hidden layer of 30 neural elements. For this network, the average coefficient of determination (R2 value) between predicted and actual EMG signals across all nine subjects and 12 muscles during movements that involved episodes of moving objects was 0.43. CONCLUSION: This reasonable accuracy suggests that ANNs could be used to provide an initial estimate of the complex patterns of muscle stimulation needed to produce a wide array of movements, including those involving object interaction, in paralyzed individuals.

Individuals with stroke often demonstrate impaired ankle-foot function, commonly termed dropped foot that affects their ability to walk safely at home and within their community. While interventions are available to improve gait function, they have inconsistency demonstrated positive effects due to the lack of evidence-based practice guidelines and a limited understanding of the mechanisms leading to dropped foot. The aim of this dissertation was to 1) determine the relationship between dropped foot gait deviations and impaired sensorimotor control, 2) compare gait biomechanics between stroke survivors with and without dropped foot impairment, and 3) evaluate the immediate effects of an ankle-foot orthotic (AFO) and functional electrical stimulation (FES) device among stroke survivors with dropped foot impairment. Our evaluation combined standardized clinical measures of ankle-foot function (i.e. sensorimotor control, strength, spasticity and range of motion) and gait analysis using advanced laboratory techniques (i.e. electromyography and electrical goniometers) to quantify mechanisms of dropped foot impairment. Fifty-five stroke survivors completed the assessment prior to discharge from inpatient rehabilitation. Individuals with poor generation of isometric dorsiflexor force and reduced passive ankle range of motion were likely to demonstrate greater plantarflexion in swing and limited stance phase ankle joint excursion, respectively. Results from the gait analysis revealed a delayed onset and reduced activation time of the ankle dorsiflexors, and decreased co-activation time in the stance phase as possible mechanisms leading to dropped foot. A detailed case series was performed with four stroke survivors with dropped foot currently using an AFO. Application of an AFO immediately improved peak dorsiflexion in the swing phase and limited ankle range of motion during stance. When walking with the FES device, individuals with moderate dorsiflexor muscle weakness improved their ankle position at initial contact and increased peak dorsiflexion during stance, while no significant changes were observed among individuals with greater impairment. Overall, the results highlighted individual differences in response to interventions aimed at improving dropped foot gait deviations. These findings contribute to a greater understanding of gait dysfunction post stroke, and may lead to the development of a more effective clinical assessment and intervention strategies to improve dropped foot impairment.

Suite à une lésion (ex: blessure médullaire, accident vasculaire cérébral) ou une maladie neurodégénérative (ex: maladie de Parkinson), le système nerveux central humain peut être sujet à de multiples déficiences sensori-motrices menant à des handicaps plus ou moins lourds au cours du temps.Face aux méthodes thérapeutiques classiques, la stimulation électrique fonctionnelle (SEF) des muscles préservés permet de restaurer le mouvement et de fournir une assistance afin d’améliorer la condition des personnes atteintes et de faciliter leur réadaptation fonctionnelle.De nombreuses problématiques intrinsèques à la complexité du système musculo-squelettique et aux contraintes technologiques rendent néanmoins difficile la démocratisation de solutions de stimulation électro-fonctionnelle en dépit d’avancées majeures dans le domaine.Visant à favoriser l’utilisabilité et l’adaptabilité de telles solutions, cette thèse s’appuie sur un réseau de capteurs/actionneurs génériques embarqués sur le sujet, afin d’utiliser la connaissance issue de l’observation et l’analyse du mouvement pathologique des membres inférieurs pour étudier et valider expérimentalement de nouvelles solutions de commande de la SEF à travers une approche orientée-patient. / The human central nervous system (CNS) can be subject to multiple dysfunctions. Potentially due to physical lesions (e.g.: spinal cord injuries, hemorrhagic or ischemic stroke) or to neurodegenerative disorders (e.g.: Parkinson’s disease), these deficiencies often result in major functional impairments throughout the years.As an alternative to usual therapeutic approaches, functional electrical stimulation (FES) of preserved muscles enables to assist individuals in executing functional movements in order to improve their daily life condition or to help enhancing rehabilitation process.Despite major technological advances in rehabilitation engineering, the complexity of the musculoskeletal system and the technological constraints associated have led to a very slow acceptance of neurorehabilitation technologies.To promote usability and adaptability, several approaches and algorithms were studied through this thesis and were experimentally validated in different clinical and pathological contexts, using low-cost wearable sensors combined to programmable stimulators to assess and control motion through a patient-centered approach.

La stimulation électrique fonctionnelle (FES) est présente depuis des décennies dans les centres de rééducation. Le principe de cette technique est de créer une dépolarisation de la membrane (potentiel d’action) des cellules excitables (axones ou myocytes) entrainant une contraction musculaire. Employée dans la plupart des cas pour le renforcement musculaire et la prévention des atrophies musculaires faisant suite à une lésion de la moelle épinière, la FES peut également être utilisée pour diminuer la spasticité et restaurer des mouvements des membres. Ainsi, certains dispositifs (neuroprothèses) utilisant la FES sont utilisés depuis plus de 25 ans, pour permettre à certains patients atteints de paralysies des membres supérieurs de pouvoir effectuer des préhensions. Les patients gagnent alors en autonomie dans les activités de la vie quotidienne ce qui limite leurs recours aux aides humaines. Cependant, bien que ce type de neuroprothèse se présente comme l’une des techniques les plus prometteuses pour le rétablissement de la fonction de préhension chez des sujets atteints d’une lésion de la moelle épinière, son utilisation reste limitée. En effet, les dispositifs de stimulation externe provoque des mouvements peu précis et les modes de pilote de cette stimulation, peu ergonomiques, ne sont pas accessibles à la plupart des patients lésés médullaires. Ces difficultés sont atténuées lorsque la stimulation est implantée et le mode de contrôle adapté à la pathologie. Parmi les dispositifs implantées, tous utilisent la stimulation des points moteurs pour rétablir des mouvements de main ce qui nécessite l’implantation de nombreuses électrodes et donc une opération chirurgicale lourde. Des complications liées aux matériels implantés peuvent apparaître au cours du temps. Ce travail de thèse propose une approche originale basée sur (i) la stimulation sélective nerveuse (à l’aide d’une électrode gouttière multi contact) pour rétablir des mouvements de préhension chez des patients tétraplégiques et (ii) l’utilisation de signaux émanant de muscles supra lésionnels pour le contrôle de cette stimulation. Des expérimentations humaines et animales réalisées en conditions aiguës ont démontré la faisabilité de notre approche. Ainsi, la stimulation du nerf sciatique par notre électrode gouttière a permis d’activer sélectivement plusieurs muscles antagonistes chez les 5 animaux de l’étude inclus dans l’étude. Une sélectivité intra fasciculaire est retrouvée chez 3 des 5 animaux. La stimulation du nerf médian chez un patient tétraplégique a permis d’activer sélectivement les muscles palmaris longuset flexor carpi radialis. Concernant le contrôle de la neuroprothèse, nous avons mis en évidence chez les 5 sujets tétraplégiques ayant participé aux expérimentations, une combinaison de muscles pouvant être utilisée pour piloter facilement un dispositif. Des contractions continues ou gradées de ces muscles peuvent être maintenues et ce, sans aucun apprentissage ou entrainement préalable. Les modalités de contrôle et les muscles préférentiels sont patient-dépendant. / Functional electrical stimulation (FES) is used for decades in rehabilitation centers. The principle of this technique is to create a membrane depolarization (action potential) of excitable cells (myocytes or axons) to cause a muscle contraction. Used in most cases for muscle strengthening and prevention of muscle atrophy following a spinal cord injury, FES can also be used to reduce spasticity and restore limb movement. For example, some devices (neuroprostheses) using FES are used for over 25 years, to allow some patients with paralysis of the upper limbs to perform hand movements. Patients then becoming more independent in activities of daily living which limits their use of human aid. However, although this type of neuroprosthesis stands as one of the most promising techniques for the recovery of the gripping function in subjects with spinal cord injury, its use is limited. Indeed, external stimulation devices cause imprecise movements and modes of control modes, not very ergonomic, are not accessible to most spinal cord injured patients. These difficulties are alleviated when the stimulation is implanted and control mode adapted to the pathology. Among the implanted devices all use the stimulation of motor pointsto restore hand movements which requires the implantation of many electrodes and therefore a major surgery. Complications related to the implanted materials can occur over time. This thesis proposes an original approach based on (i) selective nerve stimulation (using a multi contact cuff electrode) to restore gripping motion in tetraplegic patients and (ii) use of signals from supra lesional muscles to control this stimulation. Human and animal experimentations performed in acute conditions have demonstrated the feasibility of our approach. Thus, stimulation of the sciatic nerve by our cuff electrode allowed to selectively activate several antagonistic muscles in the 5 animals included in the study. Intra fascicular selectivity was found in 3 of 5 animals. The stimulation of the median nerve of a tetraplegic patient allowed to selectively activate the palmaris longus and flexor carpi radialis muscles. For the control of neuroprosthesis we demonstrated in the 5 tetraplegics subjects who participated in the experiments, a combination of muscles that can be used to easily control a device. Continuous or graded contractions of these muscles can be maintained, without any prior learning or training. The control modalities and preferential muscles are patient-dependent.