Electromechanical delay during functional electrical stimulation induced cycling is a function of lower limb position.

INTRODUCTION: Functional electrical stimulation (FES) induced cycling has been shown to be an effective rehabilitation for those with lower limb movement disorders. However, a consequence of FES is an electromechanical delay (EMD) existing between the stimulation input and the onset of muscle force. The objective of this study is to determine if the cycle crank angle has an effect on the EMD. METHODS: Experiments were performed on 10 participants, five healthy and five with neurological conditions resulting in movement disorders. A motor fixed the crank arm of a FES-cycle in 10° increments and at each angle stimulation was applied in a random sequence to a combination of the quadriceps femoris and gluteal muscle groups. The EMD was examined by considering the contraction delay (CD) and the residual delay (RD), where the CD (RD) is the time latency between the start (end) of stimulation and the onset (cessation) of torque. Two different measurements were used to examine the CD and RD. Further, two multiple linear regressions were performed on each measurement, one for the left and one for the right muscle groups. RESULTS: The crank angle was determined to be statistically relevant for both the CD and RD. CONCLUSIONS: Since the crank angle has a significant effect on both the CD and RD, the angle has a significant effect on the EMD. Therefore, future efforts should consider the importance of the crank angle when modelling or estimating the EMD to improve control designs and ultimately improve rehabilitative treatments.Implications for rehabilitationNew model predicts the delayed response of muscle torque production to electrical stimulation as a function of limb position during FES cycling.The model can inform closed-loop electrical stimulation induced rehabilitative cycling.

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.

Characterization of the Time-Varying Nature of Electromechanical Delay During FES-Cycling.

Functional electrical stimulation (FES) induced cycling is a common rehabilitative technique for people with neuromuscular disorders. A challenge for closed-loop FES control is that there exists a potentially destabilizing time-varying input delay, termed electromechanical delay (EMD), between the application of the electric field and the corresponding muscle contraction. In this article, the FES-induced torque production and EMD are quantified on an FES-cycle for the quadriceps femoris and gluteal muscle groups. Experiments were performed on five able-bodied individuals and five individuals with neurological conditions. Closed-loop FES-cycling was applied to induce fatigue and torque and EMD measurements were made during isometric conditions before and after each minute of cycling to quantify the effect of fatigue on EMD and torque production. A multiple linear regression and other descriptive statistics were performed to establish a range of expected EMD values and bounds on the rate of change of the EMD across a diverse population. The results from these experiments can be used to assist in the development of closed-loop controllers for FES-cycling that are robust to time-varying EMD and changes in torque production.

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.

Controlling the Cadence and Admittance of a Functional Electrical Stimulation Cycle.

For an individual suffering from a neurological condition, such as spinal cord injury, traumatic brain injury, or stroke, motorized functional electrical stimulation (FES) cycling is a rehabilitation strategy, which offers numerous health benefits. Motorized FES cycling is an example of physical human-robot interaction in which both systems must be controlled; the human is actuated by applying neuromuscular electrical stimulation to the large leg muscle groups, and the cycle is actuated through its onboard electric motor. While the rider is stimulated using a robust sliding-mode controller, the cycle utilizes an admittance controller to preserve rider safety. The admittance controller is shown to be passive with respect to the rider, and the cadence controller is shown to be globally exponentially stable through a Lyapunov-like switched systems stability analysis. Experiments are conducted on three able-bodied participants and four participants with neurological conditions (NCs) to demonstrate the efficacy of the developed controller and investigate the effect of manipulating individual admittance parameters. Results demonstrate an average admittance cadence error of -0.06±1.47 RPM for able-bodied participants and -0.02 ± 0.93 RPM for participants with NCs.

Position and torque control via rehabilitation robot and functional electrical stimulation.

Two common rehabilitation therapies for individuals possessing neurological conditions are functional electrical stimulation (FES) and robotic assistance. This paper focuses on combining the two rehabilitation strategies for use on the biceps brachii muscle group. FES is used to elicit muscle contractions to actuate the forearm and a rehabilitation robot is used to challenge the muscle group in its efforts. Two controllers were developed and implemented to accomplish the multifaceted objective, both of which achieve global exponential stability for position and torque tracking as proven through a Lyapunov stability analysis. Experiments performed on one able bodied individual demonstrate an average RMS error of 5.8 degrees for position tracking and 0.40 Newton-meters for torque tracking.

Identification-Based Closed-Loop NMES Limb Tracking With Amplitude-Modulated Control Input.

An upper motor neuron lesion (UMNL) can be caused by various neurological disorders or trauma and leads to disabilities. Neuromuscular electrical stimulation (NMES) is a technique that is widely used for rehabilitation and restoration of motor function for people suffering from UMNL. Typically, stability analysis for closed-loop NMES ignores the modulated implementation of NMES. However, electrical stimulation must be applied to muscle as a modulated series of pulses. In this paper, a muscle activation model with an amplitude modulated control input is developed to capture the discontinuous nature of muscle activation, and an identification-based closed-loop NMES controller is designed and analyzed for the uncertain amplitude modulated muscle activation model. Semi-global uniformly ultimately bounded tracking is guaranteed. The stability of the closed-loop system is analyzed with Lyapunov-based methods, and a pulse frequency related gain condition is obtained. Experiments are performed with five able-bodied subjects to demonstrate the interplay between the control gains and the pulse frequency, and results are provided which indicate that control gains should be increased to maintain stability if the stimulation pulse frequency is decreased to mitigate muscle fatigue. For the first time, this paper brings together an analysis of the controller and modulation scheme.

Switched Control of Cadence During Stationary Cycling Induced by Functional Electrical Stimulation.

Functional electrical stimulation (FES) can be used to activate the dysfunctional lower limb muscles of individuals with neurological disorders to produce cycling as a means of rehabilitation. However, previous literature suggests that poor muscle control and nonphysiological muscle fiber recruitment during FES-cycling causes lower efficiency and power output at the cycle crank than able-bodied cycling, thus motivating the investigation of improved control methods for FES-cycling. In this paper, a stimulation pattern is designed based on the kinematic effectiveness of the rider's hip and knee joints to produce a forward torque about the cycle crank. A robust controller is designed for the uncertain, nonlinear cycle-rider system with autonomous, state-dependent switching. Provided sufficient conditions are satisfied, the switched controller yields ultimately bounded tracking of a desired cadence. Experimental results on four able-bodied subjects demonstrate cadence tracking errors of 0.05 ±1.59 and 5.27 ±2.14 revolutions per minute during volitional and FES-induced cycling, respectively. To establish feasibility of FES-assisted cycling in subjects with Parkinson's disease, experimental results with one subject demonstrate tracking errors of 0.43 ± 4.06 and 0.17 ±3.11 revolutions per minute during volitional and FES-induced cycling, respectively.

Comparing the force ripple during asynchronous and conventional stimulation.

INTRODUCTION: Asynchronous stimulation has been shown to reduce fatigue during electrical stimulation; however, it may also exhibit a force ripple. We quantified the ripple during asynchronous and conventional single-channel transcutaneous stimulation across a range of stimulation frequencies. METHODS: The ripple was measured during 5 asynchronous stimulation protocols, 2 conventional stimulation protocols, and 3 volitional contractions in 12 healthy individuals. RESULTS: Conventional 40 Hz and asynchronous 16 Hz stimulation were found to induce contractions that were as smooth as volitional contractions. Asynchronous 8, 10, and 12 Hz stimulation induced contractions with significant ripple. CONCLUSIONS: Lower stimulation frequencies can reduce fatigue; however, they may also lead to increased ripple. Future efforts should study the relationship between force ripple and the smoothness of the evoked movements in addition to the relationship between stimulation frequency and NMES-induced fatigue to elucidate an optimal stimulation frequency for asynchronous stimulation.

Adaptive Inverse optimal neuromuscular electrical stimulation.

Neuromuscular electrical stimulation (NMES) is a prescribed treatment for various neuromuscular disorders, where an electrical stimulus is provided to elicit a muscle contraction. Barriers to the development of NMES controllers exist because the muscle response to an electrical stimulation is nonlinear and the muscle model is uncertain. Efforts in this paper focus on the development of an adaptive inverse optimal NMES controller. The controller yields desired limb trajectory tracking while simultaneously minimizing a cost functional that is positive in the error states and stimulation input. The development of this framework allows tradeoffs to be made between tracking performance and control effort by putting different penalties on error states and control input, depending on the clinical goal or functional task. The controller is examined through a Lyapunov-based analysis. Experiments on able-bodied individuals are provided to demonstrate the performance of the developed controller.

A novel modulation strategy to increase stimulation duration in neuromuscular electrical stimulation.

INTRODUCTION: Neuromuscular electrical stimulation (NMES) has been shown to be an effective treatment for muscular dysfunction. Yet, a fundamental barrier to NMES treatments is the rapid onset of muscle fatigue. The purpose of this study is to examine the effect of feedback-based frequency modulation on the closed-loop performance of the quadriceps during repeated dynamic contractions. METHODS: In the first experiment, subjects completed four different frequency modulation NMES protocols utilizing the same amplitude modulation control to compare the successful run times (SRTs). A second experiment was performed to determine the change in muscle response to high- and low-frequency stimulation. RESULTS: Compared with constant-frequency stimulation, results indicate that using an error-driven strategy to vary the stimulation frequency during amplitude modulation increases the number of successful contractions during non-isometric conditions. CONCLUSION: Simultaneous frequency and amplitude modulation increases the SRT during closed-loop NMES control.