Christine Azevedo-Coste

Comparative analysis of transverse intrafascicular multichannel, longitudinal intrafascicular and multipolar cuff electrodes for the selective stimulation of nerve fascicles

The selection of a suitable nerve electrode for neuroprosthetic applications implies a trade-off between invasiveness and selectivity, wherein the ultimate goal is achieving the highest selectivity for a high number of nerve fascicles by the least invasiveness and potential damage to the nerve. The transverse intrafascicular multichannel electrode (TIME) is intended to be transversally inserted into the peripheral nerve and to be useful to selectively activate subsets of axons in different fascicles within the same nerve. We present a comparative study of TIME, LIFE and multipolar cuff electrodes for the selective stimulation of small nerves. The electrodes were implanted on the rat sciatic nerve, and the activation of gastrocnemius, plantar and tibialis anterior muscles was recorded by EMG signals. Thus, the study allowed us to ascertain the selectivity of stimulation at the interfascicular and also at the intrafascicular level. The results of this study indicate that (1) intrafascicular electrodes (LIFE and TIME) provide excitation circumscribed to the implanted fascicle, whereas extraneural electrodes (cuffs) predominantly excite nerve fascicles located superficially; (2) the minimum threshold for muscle activation with TIME and LIFE was significantly lower than with cuff electrodes; (3) TIME allowed us to selectively activate the three tested muscles when stimulating through different active sites of one device, both at inter- and intrafascicular levels, whereas selective activation using multipolar cuff (with a longitudinal tripolar stimulation configuration) was only possible for two muscles, at the interfascicular level, and LIFE did not activate selectively more than one muscle in the implanted nerve fascicle.

Evoked Electromyography-Based Closed-Loop Torque Control in Functional Electrical Stimulation

This paper proposed a closed-loop torque control strategy of functional electrical stimulation (FES) with the aim of obtaining an accurate, safe, and robust FES system. Generally, FES control systems are faced with the challenge of how to deal with time-variant muscle dynamics due to physiological and biochemical factors (such as fatigue). The degraded muscle force needs to be compensated in order to ensure the accuracy of the motion restored by FES. Another challenge concerns the fact that implantable sensors are unavailable to feedback torque information for FES in humans. As FES-evoked electromyography (EMG) represents the activity of stimulated muscles, and also enables joint torque prediction as presented in our previous studies, here we propose an EMG-feedback predictive controller of FES to control joint torque adaptively. EMG feedback contributes to taking the activated muscle state in the FES torque control system into account. The nature of the predictive controller facilitates prediction of the muscle mechanical response and the system can therefore control joint torque from EMG feedback and also respond to time-variant muscle state changes. The control performance, fatigue compensation and aggressive control suppression capabilities of the proposed controller were evaluated and discussed through experimental and simulation studies.

Nonlinear model predictive control of joint ankle by electrical stimulation for drop foot correction

In this paper we investigate the use of optimal control techniques to improve Functional Electrical Stimulation (FES) for drop foot correction on hemiplegic patients. A model of the foot and the tibialis anterior muscle, the contraction of which is controlled by electrical stimulation has been established and is used in the optimal control problem. The novelty in this work is the use of the ankle accelerations and shank orientations (so-called external states) in the model, which have been measured on hemiplegic patients in a previous experiment using Inertial Measurement Units (IMUs). The optimal control problem minimizes the square of muscle excitations which serves the overall goal of reducing energy consumption in the muscle. In a first step, an offline optimal control problem is solved for test purposes and shows the efficiency of the FES optimal control for drop foot correction. In a second step, a Nonlinear Model Predictive Control (NMPC) problem - or online optimal control problem, is solved in a simulated environment. While the ulitmate goal is to use NMPC on the real system, i.e. directly on the patient, this test in simulation was meant to show the feasibility of NMPC for online drop foot correction. In the optimization problem, a set of fixed constraints of foot orientation was applied. Then, an original adaptive constraint taking into account the current ankle height, was introduced and tested. Comparisons between results under fixed and adaptive constraints highlight the advantage of the adaptive constraints in terms of energy consumption, where its quadratic sum of controls, obtained by NMPC, was three times lower than with the fixed constraint. This feasibility study was a first step in application of NMPC on real hemiplegic patients for online FES-based drop foot correction. The adaptive constraints method presents a new and efficient approach in terms of muscular energy consumption minimization.

Multiscale modeling of skeletal muscle properties and experimental validations in isometric conditions

In this article, we describe an approach to model the electromechanical behavior of the skeletal muscle based on the Huxley formulation. We propose a model that complies with a well established macroscopic behavior of striated muscles where force-length, force–velocity, and Mirsky–Parmley properties are taken into account. These properties are introduced at the microscopic scale and related to a tentative explanation of the phenomena. The method used integrates behavior ranging from the microscopic to the macroscopic scale, and allows the computation of the dynamics of the output force and stiffness controlled by EMG or stimulation parameters. The model can thus be used to simulate and carry out research to develop control strategies using electrical stimulation in the context of rehabilitation. Finally, through animal experiments, we estimated model parameters using a Sigma Point Kalman Filtering technique and dedicated experimental protocols in isometric conditions and demonstrated that the model can accurately simulate individual variations and thus take into account subject dependent behavior.

Improving the signal-to-noise ratio in recordings with thin-film longitudinal intra-fascicular electrodes using shielding cuffs

An elegant solution to the problem of instrumenting paralyzed limbs with artificial sensors for use with closed-loop FES systems is to use natural sensors, such as muscle afferent activity as feedback for the artificial controller. Longitudinal intra-fascicular electrodes (LIFEs) are electrodes that have shown promise in this application. As a peripheral nerve interface, they are designed to be placed inside the peripheral nerve, but near potentially active muscles and the stimulating electrode. Artefacts from EMG and stimulation remain limiting factors in signal acquisition. Here, we present a technique for improving the signal-to-noise ratio which consists of wrapping a shield around the implant site of the recording electrode. Preliminary results obtained during in-vivo experiments suggest that the shielding increases the level of the neural signal in the recordings.

Dual predictive control of electrically stimulated muscle using biofeedback for drop foot correction

Electrical stimulation (ES) is one of the solutions for drop foot correction. Conventional ES systems deliver predefined stimulation pattern to the affected muscles. However, time-variant muscle response may influence the gait performance as they are difficult to be taken into account in advance. Therefore, closed-loop ES control is important to obtain desired gait in presence of muscle response variation. In this work, a dual predictive control, which consists of two nonlinear generalized predictive controllers, is proposed to track desired torque. The stimulated muscle dynamics are modeled by Hammerstein cascades, with one representing stimulation to activation, the other representing activation to torque. Ankle dorsiflexion torque and ES-evoked EMG of tibialis anterior were recorded experimentally for model identification. The control scheme is validated by following desired torque trajectories with the identified model. The results show that the stimulation pattern obtained from the dual predictive control can produce good torque tracking according to the current muscle condition.

Interpretation of Muscle Spindle Afferent Nerve Response to Passive Muscle Stretch Recorded With Thin-Film Longitudinal Intrafascicular Electrodes

In this study, we explored the feasibility of estimating muscle length in passive conditions by interpreting nerve responses from muscle spindle afferents recorded with thin-film longitudinal intrafascicular electrodes. Afferent muscle spindle response to passive stretch was recorded in ten acute rabbit experiments. A newly proposed first-order model of muscle spindle response to passive sinusoidal muscle stretch manages to capture the relationship between afferent neural firing rate and muscle length. We demonstrate that the model can be used to track random motion trajectories with bandwidth from 0.1 to 1 Hz over a range of 4 mm with a muscle length estimation error of 0.3 mm (1.4deg of joint angle). When estimation is performed using four-channel ENG there is a 50% reduction in estimate variation, compared to using single-channel recordings.

On the Use of Fixed‐Intensity Functional Electrical Stimulation for Attenuating Essential Tremor

A great proportion of essential tremor (ET) patients have not so far been able to receive functional benefits from traditional therapies. In this regard, the use of functional electrical stimulation (FES) has been proposed for reducing tremor amplitude by stimulating muscles in antiphase with respect to the trembling motion. Although some studies have reported success in terms of tremor attenuation, drawbacks still exist that prevent the method from being used in real-life applications. In this article, we explore an alternative approach: a strategy based on the hypothesis that FES-induced constant muscle contraction may provide functional benefit for tremor patients. To evaluate the proposed strategy, experiments were conducted in which stimulation was intermittently turned on and off while the subjects performed a static motor task. The results of the proposed experimental protocol indicate that tremor attenuation using this strategy is feasible, as consistent tremor attenuation levels were obtained in eight out of 10 ET patients. Nonetheless, tremor reduction was not instantaneous for all successful trials, indicating that prior training with FES may improve the overall response. Furthermore, although simpler assistive devices may potentially be designed based on this technique, some experimental difficulties still exist, which suggests that further studies are necessary.

Spike sorting of muscle spindle afferent nerve activity recorded with thin-film intrafascicular electrodes

Afferent muscle spindle activity in response to passive muscle stretch was recorded in vivo using thin-film longitudinal intrafascicular electrodes. A neural spike detection and classification scheme was developed for the purpose of separating activity of primary and secondary muscle spindle afferents. The algorithm is based on the multiscale continuous wavelet transform using complex wavelets. The detection scheme outperforms the commonly used threshold detection, especially with recordings having low signal-to-noise ratio. Results of classification of units indicate that the developed classifier is able to isolate activity having linear relationship with muscle length, which is a step towards online model-based estimation of muscle length that can be used in a closed-loop functional electrical stimulation system with natural sensory feedback.

Treating drop-foot in hemiplegics: the role of matrix electrode

We present advantages of the “intelligent matrix electrode” for providing selective correction of drop-foot in hemiplegic individuals. The matrix electrode which integrates stimulating and sensing parts could allow the emulation of the appropriate electrode shape and size; thereby, provision of selective stimulation that leads to functional movement and online adaptation of the electrode during the application. The need for selective stimulation follows recent findings about therapeutic effects of electrical stimulation in neurorehabilitation. The matrix electrode comprises small fields that can be made conductive and a controller that allows computerized selection of the fields being conductive. Here we present results from a study in nine hemiplegics. The matrix electrode was positioned over the peroneal nerve and primary dorsiflexor muscles and we estimated the movement of the foot by measuring the ankle joint angle. We found that the branched tree type shape and size of the electrode vary substantially when stimulating over the dorsiflexor muscles individuals in the study. We confirmed very high sensitivity to the position of small electrode when stimulating over the nerve.