Switched Tracking Control of the Lower Limb During Asynchronous Neuromuscular Electrical Stimulation: Theory and Experiments

Data-Based and Opportunistic Integral Concurrent Learning for Adaptive Trajectory Tracking During Switched FES-Induced Biceps Curls

Hybrid exoskeletons, which combine functional electrical stimulation (FES) with a motorized testbed, can potentially improve the rehabilitation of people with movement disorders. However, hybrid exoskeletons have inherently nonlinear and uncertain dynamics, including combinations of discrete modes that switch between different continuous dynamic subsystems, which complicate closed-loop control. A particular complication is the uncertain muscle control effectiveness associated with FES. In this work, adaptive integral concurrent learning (ICL) motor and FES controllers are developed for a hybrid biceps curl exoskeleton, which are designed to achieve opportunistic and data-based learning of the uncertain human and electromechanical testbed parameters. Global exponential trajectory tracking and parameter estimation errors are proven through a Lyapunov-based stability analysis. The motor effectiveness is assumed to be unknown, and, to help with fatigue reduction, FES is enabled to switch between multiple electrodes on the biceps brachii, further complicating the analysis. A consequence of switching between the different uncertain subsystems is that the parameters must be opportunistically learned for each subsystem (i.e. each electrode and the motor), while that subsystem is active. Experiments were performed to validate the developed ICL controllers on twelve healthy participants. The average (± standard deviation) position tracking errors across each participant were 1.44 ± 5.32 deg, -0.25 ± 2.85 deg, and -0.17 ± 2.66 deg across biceps Curls 1-3, 4-7, and 8-10, respectively, where the average across the entire experiment was 0.28 ± 3.53 deg.

C. Moreira M, D. M. Pinheiro L, R. Pereira T, G. Carmona G, P. D. Freire J, A. I. Bastos J, Padilha Lanari Bo A. User-centered design and spatially-distributed sequential electrical stimulation in cycling for individuals with paraplegia

Background

In this work, we share the enhancements made in our system to take part in the CYBATHLON 2020 Global Edition Functional Electrical Stimulation (FES) Bike Race. Among the main improvements, firstly an overhaul, an overhaul of the system and user interface developed with User-centered design principles with remote access to enable telerehabilitation. Secondly, the implementation and experimental comparison between the traditional single electrode stimulation (SES) and spatially distributed sequential stimulation (SDSS) applied for FES Cycling.

Methods

We report on the main aspects of the developed system. To evaluate the user perception of the system, we applied a System Usability Scale (SUS) questionnaire. In comparing SDSS and SES, we collected data from one subject in four sessions, each simulating one race in the CYBATHLON format.

Results

User perception measured with SUS indicates a positive outcome in the developed system. The SDSS trials were superior in absolute and average values to SES regarding total distance covered and velocity. We successfully competed in the CYBATHLON 2020 Global Edition, finishing in 6th position in the FES Bike Race category.

Conclusions

The CYBATHLON format induced us to put the end-user in the center of our system design principle, which was well perceived. However, further improvements are required if the intention is to progress to a commercial product. FES Cycling performance in SDSS trials was superior when compared to SES trials, indicating that this technique may enable faster and possibly longer FES cycling sessions for individuals with paraplegia. More extensive studies are required to assess these aspects.

A Generic Sequential Stimulation Adapter for Reducing Muscle Fatigue during Functional Electrical Stimulation

Background: Clinical applications of conventional functional electrical stimulation (FES) administered via a single electrode are limited by rapid onset neuromuscular fatigue. “Sequential” (SEQ) stimulation, involving the rotation of pulses between multiple active electrodes, has been shown to reduce fatigue compared to conventional FES. However, there has been limited adoption of SEQ in research and clinical settings. Methods: The SEQ adapter is a small, battery-powered device that transforms the output of any commercially available electrical stimulator into SEQ stimulation. We examined the output of the adaptor across a range of clinically relevant stimulation pulse parameters to verify the signal integrity preservation ability of the SEQ adapter. Pulse frequency, amplitude, and duration were varied across discrete states between 4 and 200 Hz, 10 and100 mA, and 50 and 2000 μs, respectively. Results: A total of 420 trials were conducted, with 80 stimulation pulses per trial. The SEQ adapter demonstrated excellent preservation of signal integrity, matching the pulse characteristics of the originating stimulator within 1% error. The SEQ adapter operates as expected at pulse frequencies up to 160 Hz, failing at a frequency of 200 Hz. Conclusion: The SEQ adapter represents an effective and low-cost solution to increase the utilization of SEQ in existing rehabilitation paradigms.

A Tube-based Model Predictive Control Method to Regulate a Knee Joint with Functional Electrical Stimulation and Electric Motor Assist

A hybrid neuroprosthesis system is a promising rehabilitation technology to restore lower-limb function in persons with paraplegia. The technology combines functional electrical stimulation (FES) and a powered lower limb exoskeleton to produce movements for walking and standing. The main control challenge in the hybrid neuroprosthesis is to achieve an optimal coordination between FES and electric motors. Model-based optimal control methods have been suggested for the control of the hybrid neuroprosthesis. However, it is often difficult to effect robust control performance with model-based optimal control methods due to modeling uncertainties. A tube-based model predictive control (MPC) method is developed to obtain robust and optimal coordination between FES and an electric motor during a knee regulation task. An external feedback control is used to limit the error between the actual position and the MPC-computed nominal position. The tube-based MPC method is proven to have recursive feasibility, compliance to input constraints, and exponentially bounded stability. The experimental results obtained from an able-bodied participant and a participant with spinal cord injury validate the controller's ability to allocate control inputs to FES and the electric motor as well as method's robustness to modeling uncertainties.

Design of an FPGA-Based Fuzzy Feedback Controller for Closed-Loop FES in Knee Joint Model

Functional electrical stimulation (FES) device has been widely used by spinal cord injury (SCI) patients in their rehab exercises to restore motor function to their paralysed muscles. The major challenge of muscle contraction induced by FES is early muscle fatigue due to the open-loop stimulation strategy. To reduce the early muscle fatigue phenomenon, a closed-loop FES system is proposed to track the angle of the limb’s movement and provide an accurate amount of charge according to the desired reference angle. Among the existing feedback controllers, fuzzy logic controller (FLC) has been found to exhibit good control performance in handling complex non-linear systems without developing any complex mathematical model. Recently, there has been considerable interest in the implementation of FLC in hardware embedded systems. Therefore, in this paper, a digital fuzzy feedback controller (FFC) embedded in a field-programmable gate array (FPGA) board was proposed. The digital FFC mainly consists of an analog-to-digital converter (ADC) Data Acquisition and FLC sub-modules. The FFC was designed to monitor and control the progress of knee extension movement by regulating the stimulus pulse width duration to meet the target angle. The knee is expected to extend to a maximum reference angle setting (70°, 40° or 30°) from its normal position of 0° once the stimulus charge is applied to the muscle by the FES device. Initially, the FLC was modelled using MATLAB Simulink. Then, the FLC was hardcoded into digital logic using hardware description language (HDL) Verilog codes. Thereafter, the performance of the digital FLC was tested with a knee extension model using the HDL co-simulation technique in MATLAB Simulink. Finally, for real-time verification, the designed digital FFC was downloaded to the Intel FPGA (DE2-115) board. The digital FFC utilized only 4% of the total FPGA (Cyclone IV E) logic elements (LEs) and required 238 µs to regulate stimulus pulse width data, including 3 µs for the FLC computation. The high processing speed of the digital FFC enables the stimulus pulse width duration to be updated every stimulation cycle. Furthermore, the implemented digital FFC has demonstrated good control performance in accurately controlling the stimulus pulse width duration to reach the desired reference angle with very small overshoot (1.4°) and steady-state error (0.4°). These promising results are very useful for a real-world closed-loop FES application.

A Subvision System for Enhancing the Environmental Adaptability of the Powered Transfemoral Prosthesis

Visual information is indispensable to human locomotion in complex environments. Although amputees can perceive the environmental information by eyes, they cannot transmit the neural signals to prostheses directly. To augment human-prosthesis interaction, this article introduces a subvision system that can perceive environments actively, assist to control the powered prosthesis predictively, and accordingly reconstruct a complete vision-locomotion loop for transfemoral amputees. By using deep learning, the subvision system can classify common static terrains (e.g., level ground, stairs, and ramps) and estimate corresponding motion intents of amputees with high accuracy (98%). After applying the subvision system to the locomotion control system, the powered prosthesis can help amputees to achieve nonrhythmic locomotion naturally, including switching between different locomotion modes and crossing the obstacle. The subvision system can also recognize dynamic objects, such as an unexpected obstacle approaching the amputee, and assist in generating an agile obstacle-avoidance reflex movement. The experimental results demonstrate that the subvision system can cooperate with the powered prosthesis to reconstruct a complete vision-locomotion loop, which enhances the environmental adaptability of the amputees.

Comparing Spatially Distributed and Single Electrode Stimulation on Individuals with Spinal Cord Injury

It is still a challenge to delay the onset of fatigue on muscle contraction induced by Functional Electrical Stimulation (FES). We explored the use of two stimulation methods with the same total area, single electrode stimulation (SES), and spatially distributed electrical stimulation (SDSS) during isometric knee extension with spinal cord injured (SCI) volunteers. We applied stimulation on the left and right quadriceps of two SCI participants with both methods and recorded isometric force and evoked electromyography (eEMG). We calculated the force-time integral (FTI) and eEMG-time integral (eTI) for each stimulation series and used a linear regression as a measure of decay ratio. Moreover, we also estimated the contribution from each channel from eEMG.

Ultra-High-Frame-Rate Ultrasound Monitoring of Muscle Contractility Changes Due to Neuromuscular Electrical Stimulation

The quick onset of muscle fatigue is a critical issue when applying neuromuscular electrical stimulation (NMES) to generate muscle contractions for functional limb movements, which were lost/impaired due to a neurological disorder or an injury. For in situ assessment of the effect of NMES-induced muscle fatigue, a novel noninvasive sensor modality that can quantify the degraded contractility of a targeted muscle is required. In this study, instantaneous strain maps of a contracting muscle were derived from ultra-high-frame-rate (2 kHz) ultrasound images to quantify the contractility. A correlation between strain maps and isometric contraction force values was investigated. When the muscle reached its maximum contraction, the maximum and the mean values of the strain map were correlated with the force values and were further used to stage the contractility change. During the muscle activation period, a novel methodology based on the principal component regression (PCR) was proposed to explore the strain-force correlation. The quadriceps muscle of 3 able-bodied human participants was investigated during NMES-elicited isometric knee extension experiments. Strong to very strong correlation results were obtained and indicate that the proposed measurements from ultrasound images are promising to quantify the muscle contractility changes during NMES.

Distributed Repetitive Learning Control for Cooperative Cadence Tracking in Functional Electrical Stimulation Cycling

Closed-loop control of functional electrical stimulation coupled with motorized assistance to induce cycling is a rehabilitative strategy that can improve the mobility of people with neurological conditions (NCs). However, robust control methods, which are currently pervasive in the cycling literature, have limited effectiveness due to the use of high stimulation intensity leading to accelerated fatigue during cycling protocols. This paper examines the design of a distributed repetitive learning controller (RLC) that commands an independent learning feedforward term to each of the six stimulated lower-limb muscle groups and an electric motor during the tracking of a periodic cadence trajectory. The switched controller activates lower limb muscles during kinematic efficient regions of the crank cycle and provides motorized assistance only when most needed (i.e., during the portions of the crank cycle where muscles evoke a low torque output). The controller exploits the periodicity of the desired cadence trajectory to learn from previous control inputs for each muscle group and electric motor. A Lyapunov-based stability analysis guarantees asymptotic tracking via an invariance-like corollary for nonsmooth systems. The switched distributed RLC was evaluated in experiments with seven able-bodied individuals and five participants with NCs. A mean root-mean-squared cadence error of 3.58 ± 0.43 revolutions per minute (RPM) (0.07 ± 7.35% average error) and 4.26 ± 0.84 RPM (0.1 ± 8.99% average error) was obtained for the healthy and neurologically impaired populations, respectively.

Control of Functional Electrical Stimulation Systems Using Simultaneous Pulse Width, Amplitude, and Frequency Modulations

BACKGROUND

One significant challenge of developing a controller for functional electrical stimulation systems is the time-variant nonlinear dynamics of the neuromusculoskeletal system. In the conventional methods, the stimulation intensity is adjusted by a controller; however, the stimulation frequency is always constant. The previous studies have shown that the stimulation frequency is effective in fatigue formation.

OBJECTIVES

A simultaneous modulation of the stimulation intensity and frequency is proposed to improve the joint controllability and muscle endurance. The presented control method determines pulse width (PW), amplitude, and frequency of the electrical stimulation signal, synchronously. Three different modulations are applied for control of the knee joint to show the superiority of the proposed modulation.

METHODS

The stimulation intensity is controlled by the PW and pulse amplitude of the electrical signal using an adaptive fuzzy terminal sliding mode controller and a fuzzy logic controller, respectively. Also, a fuzzy logic controller is applied to adjust the stimulation frequency. The proposed method is utilized to control the knee joint movement using quadriceps femoris muscles for ten paraplegic subjects.

RESULTS

Two different test protocols are defined to evaluate the presented method: A protocol for testing the controllability and another protocol for evaluating the produced muscle endurance. The average value of the root mean square of the tracking error was 6.4° for the proposed method which is 5.1° and 9.6° less than PW modulation and synchronous PW and amplitude modulation, respectively. The average time duration of the knee full extension was 96 sec for the proposed method which is 17 and 26 sec more than PW modulation and synchronous PW and amplitude modulation, respectively.

CONCLUSIONS

The experimental results show that control performance and tracking ability of the joint reference trajectory are improved by using the simultaneous modulation of PW, amplitude, and frequency.

Fatigue and Discomfort During Spatially Distributed Sequential Stimulation of Tibialis Anterior

Neuromuscular electrical stimulation is conventionally applied through a single pair of electrodes over the muscle belly, denominated single electrode stimulation (SES). SES is limited by discomfort and incomplete motor-unit recruitment, restricting electrically-evoked torque and promoting premature fatigue-induced torque-decline. Sequential stimulation involving rotation of pulses between multiple pairs of electrodes has been proposed as an alternative, denominated spatially distributed sequential stimulation (SDSS). The present aim was to compare discomfort, maximal-tolerated torque, and fatigue-related outcomes between SES and SDSS of tibialis anterior. Ten healthy participants completed two experimental sessions. The self-reported discomfort at sub-maximal torque, the maximal-tolerated torque, fatigue-induced torque-decline during, and doublet-twitch torque at 10- and 100-Hz before and after, 300 intermittent (0.6-s-ON-0.6-s-OFF) isokinetic contractions were compared between SES and SDSS. SDSS stimulation improved fatigue-related outcomes, whereas increased discomfort and reduced maximal-tolerated torque. SDSS holds promise for reducing fatigue. However, limited torque production and associated discomfort may limit its utility for rehabilitation/training.

Quantitative Assessment of Changes in Muscle Contractility Due to Fatigue During NMES: An Ultrasound Imaging Approach

OBJECTIVE

This paper investigates an ultrasound imaging-based non-invasive methodology to quantitatively assess changes in muscle contractility due to the fatigue induced by neuromuscular electrical stimulation (NMES).

METHODS

Knee extension experiments on human participants were conducted to record synchronized isometric knee force data and ultrasound images of the electrically stimulated quadriceps muscle. The data were first collected in a pre-fatigue stage and then in a post-fatigue stage. Ultrasound images were processed using a contraction rate adaptive speckle tracking algorithm. A two-dimensional strain measure field was constructed based on the muscle displacement tracking results to quantify muscle contractility.

RESULTS

Analysis of the strain images showed that, between the pre-fatigue and post-fatigue stages, there was a reduction in the strain peaks, a change in the strain peak distribution, and a decrease in an area occupied by the large positive strain.

CONCLUSION

The results indicate changes in muscle contractility due to the NMES-induced muscle fatigue.

SIGNIFICANCE

Ultrasound imaging with the proposed methodology is a promising tool for a direct NMES-induced fatigue assessment and facilitates new strategies to alleviate the effects of the NMES-induced fatigue.

A Modified Dynamic Surface Controller for Delayed Neuromuscular Electrical Stimulation

A widely accepted model of muscle force generation during neuromuscular electrical stimulation (NMES) is a second-order nonlinear musculoskeletal dynamics cascaded to a delayed first-order muscle activation dynamics. However, most nonlinear NMES control methods have either neglected the muscle activation dynamics or used an ad hoc strategies to tackle the muscle activation dynamics, which may not guarantee control stability. We hypothesized that a nonlinear control design that includes muscle activation dynamics can improve the control performance. In this paper, a dynamic surface control (DSC) approach was used to design a PID-based NMES controller that compensates for EMD in the activation dynamics. Because the muscle activation is unmeasurable, a model based estimator was used to estimate the muscle activation in realtime. The Lyapunov stability analysis confirmed that the newly developed controller achieves semi-global uniformly ultimately bounded (SGUUB) tracking for the musculoskeletal system. Experiments were performed on two able-bodied subjects and one spinal cord injury subject using a modified leg extension machine. These experiments illustrate the performance of the new controller and compare it to a previous PID-DC controller that did not consider muscle activation dynamics in the control design. These experiments support our hypothesis that a control design that includes muscle activation improves the NMES control performance.

The Time-Varying Nature of Electromechanical Delay and Muscle Control Effectiveness in Response to Stimulation-Induced Fatigue

Neuromuscular electrical stimulation (NMES) and Functional Electrical Stimulation (FES) are commonly prescribed rehabilitative therapies. Closed-loop NMES holds the promise to yield more accurate limb control, which could enable new rehabilitative procedures. However, NMES/FES can rapidly fatigue muscle, which limits potential treatments and presents several control challenges. Specifically, the stimulation intensity-force relation changes as the muscle fatigues. Additionally, the delayed response between the application of stimulation and muscle force production, termed electromechanical delay (EMD), may increase with fatigue. This paper quantifies these effects. Specifically, open-loop fatiguing protocols were applied to the quadriceps femoris muscle group of able-bodied individuals under isometric conditions, and the resulting torque was recorded. Short pulse trains were used to measure EMD with a thresholding method while long duration pulse trains were used to induce fatigue, measure EMD with a cross-correlation method, and construct recruitment curves. EMD was found to increase significantly with fatigue, and the control effectiveness (i.e., the linear slope of the recruitment curve) decreased with fatigue. Outcomes of these experiments indicate an opportunity for improved closed-loop NMES/FES control development by considering EMD to be time-varying and by considering the muscle recruitment curve to be a nonlinear, time-varying function of the stimulation input.