PID Controller Design for FES Applied to Ankle Muscles in Neuroprosthesis for Standing Balance

Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs

Prior applications of the cerebellar adaptive filter model have included a range of tasks within simulated and robotic systems. However, this has been limited to systems driven by continuous signals. Here, the adaptive filter model of the cerebellum is applied to the control of a system driven by spiking inputs by considering the problem of controlling muscle force. The performance of the standard adaptive filter algorithm is compared with the algorithm with a modified learning rule that minimizes inputs and a simple proportional-integral-derivative (PID) controller. Control performance is evaluated in terms of the number of spikes, the accuracy of spike input locations, and the accuracy of muscle force output. Results show that the cerebellar adaptive filter model can be applied without change to the control of systems driven by spiking inputs. The cerebellar algorithm results in good agreement between input spikes and force outputs and significantly improves on a PID controller. Input minimization can be used to reduce the number of spike inputs, but at the expense of a decrease in accuracy of spike input location and force output. This work extends the applications of the cerebellar algorithm and demonstrates the potential of the adaptive filter model to be used to improve functional electrical stimulation muscle control.

Hybrid and adaptive control of functional electrical stimulation to correct hemiplegic gait for patients after stroke

Introduction: Gait, as a fundamental human movement, necessitates the coordination of muscles across swing and stance phases. Functional electrical stimulation (FES) of the tibialis anterior (TA) has been widely applied to foot drop correction for patients with post-stroke during the swing phase. Although the gastrocnemius (GAS) during the stance phase is also affected, the Functional electrical stimulation of the gastrocnemius received less attention. Methods: To address this limitation, a timing- and intensity-adaptive Functional electrical stimulation control strategy was developed for both the TA and GAS. Each channel incorporates a speed-adaptive (SA) module to control stimulation timing and an iterative learning control (ILC) module to regulate the stimulation intensity. These modules rely on real-time kinematic or kinetic data during the swing or stance phase, respectively. The orthotic effects of the system were evaluated on eight patients with post-stroke foot drop. Gait kinematics and kinetics were assessed under three conditions: no stimulation (NS), Functional electrical stimulation to the ankle dorsiflexor tibialis anterior (SA-ILC DS) and FES to the tibialis anterior and the ankle plantarflexor gastrocnemius (SA-ILC DPS). Results: The ankle plantarflexion angle, the knee flexion angle, and the anterior ground reaction force (AGRF) in the SA-ILC DPS condition were significantly larger than those in the NS and SA-ILC DS conditions (p < 0.05). The maximum dorsiflexion angle during the swing phase in the SA-ILC DPS condition was similar to that in the SA-ILC DS condition, with both being significantly larger than the angle observed in the NS condition (p < 0.05). Furthermore, the angle error and force error relative to the set targets were minimized in the SA-ILC DPS condition. Discussion: The observed improvements can be ascribed to the appropriate stimulation timing and intensity provided by the SA-ILC DPS strategy. This study demonstrates that the hybrid and adaptive control strategy of functional electrical stimulation system offers a significant orthotic effect, and has considerable potential for future clinical application.

Electrical Stimulation Intensity to Induce Sensory Reweighting Dynamics While Standing on Balance Board

In human postural control, maladaptation of sensory reweighting to sudden environmental changes is one of the main causes of postural instability. Providing sensory cues for body motion by means of stimulation could induce the sensory reweighting dynamics. In this paper, we aimed to investigate the intensity level of electrical stimulation to induce sensory reweighting dynamics while standing on a balance board under three conditions: no stimulation (control), electrotactile stimulation (ETS) at a low-intensity level, and electrical muscle stimulation (EMS) at a high-intensity level. A total of 30 participants (ten for each condition) controlled their posture to keep the board horizontal in a balance-board task, which included a pre-test without stimulation, a stimulation test, and a post-test without stimulation. The EMS and ETS groups received electrical stimulation to the tibialis anterior or soleus muscles based on the board tilt. Before and after the balance-board task, participants performed static standing with their eyes open and also with their eyes closed to evaluate the visual reweighting. In the EMS group, the visual reweighting showed a strong negative correlation with the balance-board sway ratio between the pre- and stimulation tests, indicating that EMS induced a tendency that requires visual up-weighting to improve postural balance. However, there were no significant correlations between either parameter in the control and ETS groups. These results suggest that high-intensity electrical stimulation at the level of directly contracting muscles may be effective in reliably inducing sensory reweighting dynamics, while low-intensity electrical stimulation may be insufficient.Clinical relevance- These findings will be helpful for designing stimulus conditions to reliably induce the reweighting during balance training, and for establishing a new balance training method utilizing EMS to induce visual up-weighting.

Induced effects of electrical muscle stimulation and visual stimulation on visual sensory reweighting dynamics during standing on a balance board

Providing instruction cues on body motions using stimulations has the potential to induce sensory reweighting dynamics. However, there are currently very few quantitative investigations on the difference in the induced effects on the sensory reweighting dynamics between stimulation methods. We therefore investigated the difference in the induced effects of electrical muscle stimulation (EMS) and visual sensory augmentation (visual SA) on sensory reweighting dynamics during standing on a balance board. Twenty healthy participants controlled their posture to maintain the board horizontally in the balance-board task, which included a pre-test without stimulation, a stimulation test, and a post-test without stimulation. The EMS group (n = 10) received EMS to the tibialis anterior or soleus muscle based on the board tilt. The visual SA group (n = 10) received visual stimuli via a front monitor based on the board tilt. We measured the height of the board marker and calculated the board sway. Before and after the balance-board task, the participants performed static standing with their eyes open and closed. We measured postural sway and calculated the visual reweighting. The visual reweighting showed a strong negative correlation with the balance board sway ratio between the pre- and stimulation tests in the EMS group and a strong positive correlation with that in the visual SA group. Moreover, for those who reduced the balance board sway in the stimulation test, the visual reweighting was significantly different between the stimulation methods, demonstrating that the induced effect on sensory reweighting dynamics is quantitatively different depending on which method is used. Our findings suggest that there is an appropriate stimulation method to change to the targeted sensory weights. Future investigations on the relationship between sensory reweighting dynamics and stimulation methods could contribute to the proposal and implementation of new training methods for learning to control the target weights.

Deep brain-machine interfaces: sensing and modulating the human deep brain

Different from conventional brain-machine interfaces that focus more on decoding the cerebral cortex, deep brain-machine interfaces enable interactions between external machines and deep brain structures. They sense and modulate deep brain neural activities, aiming at function restoration, device control and therapeutic improvements. In this article, we provide an overview of multiple deep brain recording and stimulation techniques that can serve as deep brain-machine interfaces. We highlight two widely used interface technologies, namely deep brain stimulation and stereotactic electroencephalography, for technical trends, clinical applications and brain connectivity research. We discuss the potential to develop closed-loop deep brain-machine interfaces and achieve more effective and applicable systems for the treatment of neurological and psychiatric disorders.

Closed-loop transcranial ultrasound stimulation with a fuzzy controller for modulation of motor response and neural activity of mice

Objective. We propose a closed-loop transcranial ultrasound stimulation (TUS) with a fuzzy controller to realize real-time and precise control of the motor response and neural activity of mice.Approach. The mean absolute value (MAV) of the electromyogram (EMG) and peak value (PV) of the local field potential (LFP) were measured under different ultrasound intensities. A model comprising the characteristics of the MAV of the EMG, PV of the LFP, and ultrasound intensity was built using a neural network, and a fuzzy controller, proportional-integral-derivative (PID) controller, and immune feedback controller were proposed to adjust the ultrasound intensity using the feedback of the EMG MAV and the LFP PV.Main results. In simulation, the quantitative calculation indicated that the maximum relative errors between the simulated EMG MAV and the expected values were 17% (fuzzy controller), 110% (PID control), 66% (immune feedback control); furthermore, the corresponding values of the LFP PV were 12% (fuzzy controller), 53% (PID control), 55% (immune feedback control). The average relative errors of fuzzy controller, PID control, immune feedback control were 4.97%, 13.15%, 11.52%, in the EMG closed-loop experiment and 7.76%, 11.84%, 13.56%, in the LFP closed-loop experiment.Significance. The simulation and experimental results demonstrate that the closed-loop TUS with a fuzzy controller can realize the tracking control of the motor response and neural activity of mice.

A Pilot Study of Synergy-Based FES for Upper-Extremity Poststroke Rehabilitation

A previous study indicated that synergy-based functional electrical stimulation (FES) may improve instantaneous upper-limb motor performance for stroke survivors. However, it remains unclear whether the improvements will sustain over time to achieve functional gains associated with a task-oriented training (TOT). This pilot study was designed to investigate whether there is any promising sign of functional benefits. A TOT protocol with repeated forward and lateral reaching movements assisted by synergy-based FES was conducted in 16 patients (9 FES, 7 Sham) with post-stroke hemiparesis. FES stimuli were applied to 7 upper-extremity muscles of elbow and shoulder during patient movements. Envelopes of stimuli were individualized by re-composing the muscle synergies extracted from a healthy subject. After a five-day training for one hour each day, synergy-based FES induced higher increases in Fugl-Meyer scores (6.67±5.20) than did the Sham (2.00±2.38, p<0.05). Peak velocity of forward reaching movements increased with a slope 73% steeper in FES group than Sham. In lateral reaching movements, the change in synergy similarity correlated with the change in elbow flexion for the FES group, but not the Sham group. Our results indicate that synergy-based FES therapy induced clinically traceable signs of improvements in poststroke motor performance. The muscle activation in patients also showed promising sign of alteration by FES. Results suggest that a larger scale clinical trial of synergy-based FES may be feasible towards an individualized therapeutic regimen.

Tracking ankle joint movements during gait cycle via control of functional electrical stimulation

Functional electrical stimulation (FES) is an effective method to induce muscle contraction and to improve movements in individuals with injured central nervous system. In order to develop the FES systems for an individual with gait impairment, an appropriate control strategy must be designed to accurate tracking performance. The goal of this study is to present a method for designing proportional-derivative (PD) and sliding mode controllers (SMC) for the FES applied to the musculoskeletal model of an ankle joint to track the desired movements obtained by experiments on two healthy individuals during the gait cycle. Simulation results of the developed controller on musculoskeletal model of the ankle joint illustrated that the SMC is able to track the desired movements more accurately than the PD controller and prevents oscillating patterns around the experimentally measured data. Therefore, the sliding mode as the nonlinear method is more robust in face to unmodeled dynamics and model errors and track the desired path smoothly. Also, the required control effort is smoother in SMC with respect to the PD controller because of the nonlinearity.

Impedance Control of Human Ankle Joint With Electrically Stimulated Antagonistic Muscle Co-Contraction

Functional electrical stimulation (FES) is often used, typically in an open-loop manner, to restore paralyzed motor function for daily living activities. Several feedback control strategies have been developed to improve the performance and usability of FES-evoked movement. However, most of them have been position controllers, while the control strategy for human movement has been known as impedance modulation. Moreover, few studies have attempted to use antagonistic co-contraction for FES feedback control despite its expected benefits, such as enhanced stability and performance and better rehabilitation outcome. In this paper, we propose a robust impedance controller for FES that can adjust the intrinsic joint stiffness using co-contraction. It consists of an impedance control law based on time-delay estimation to compensate for the nonlinear uncertain joint dynamics and an antagonistic muscle co-contraction allocator to address the intrinsic joint stiffness caused by the co-contraction. The proposed controller was implemented on the ankle joints of five healthy subjects to simulate a standing balance situation. The results verified that the proposed controller can achieve desired impedance accurately by adjusting the intrinsic stiffness that stems from the change in the amount of co-contraction (up to 48.4% better impedance achievement with high desired stiffness).

Online Tuning of PID Controller Using a Multilayer Fuzzy Neural Network Design for Quadcopter Attitude Tracking Control

This study presents an online tuning proportional-integral-derivative (PID) controller using a multilayer fuzzy neural network design for quadcopter attitude control. PID controllers are simple but effective control methods. However, finding the suitable gain of a model-based controller is relatively complicated and time-consuming because it depends on external disturbances and the dynamic modeling of plants. Therefore, the development of a method for online tuning of quadcopter PID parameters may save time and effort, and better control performance can be achieved. In our controller design, a multilayer structure was provided to improve the learning ability and flexibility of a fuzzy neural network. Adaptation laws to update network parameters online were derived using the gradient descent method. Also, a Lyapunov analysis was provided to guarantee system stability. Finally, simulations concerning quadcopter attitude control were performed using a Gazebo robotics simulator in addition to a robot operating system (ROS), and their results were demonstrated.

Effect of the application of somatosensory and excitomotor electrical stimulation during quiet upright standing balance

Somatosensory (which activates sensory neurons only) and excitomotor (which activates both motoneurons and sensory neurons) electrical stimulations applied on the musculature of the lower-limb are likely to facilitate and disturb balance control respectively. The aim of this study was to compare the possible balance control modifications induced by somatosensory (SS) and excitomotor (EX) electrical stimulations applied on the quadriceps femoris in quiet standing condition. Kinetics and kinematics parameters were recorded with a force platform (displacements of center of foot pressure) and a 3D analysis system (hip, knee and ankle angles) respectively during a postural task. Twenty healthy young male participants carried out a monopedal postural task (i.e., unilateral stance) in three conditions: SS stimulation (1ms; 10Hz; 7±2 mA i.e., twice the intensity corresponding to the sensory threshold), EX stimulation (400 µs; 50 Hz; 20 ± 5 mA i.e., twice the intensity corresponding to the motor threshold), and a control (CONT) condition without stimulation. The results showed no significant differences between the three conditions except for the knee' angle which was higher in the EX condition (167.3±11.6 vs 164.3±5.8 and 163.9±8) (p < 0.005) than in the two other conditions (SS stimulation and CONT). This means that the EX stimulation induced a postural position change (i.e., a slight knee extension) during the monopedal postural task without altering balance control. Overall, on the basis of the stimulation parameters used in the present work, neither the SS stimulation, nor the EX stimulation facilitated or disturbed postural balance.

Advances in neuroprosthetic management of foot drop: a review

This paper reviews the technological advances and clinical results obtained in the neuroprosthetic management of foot drop. Functional electrical stimulation has been widely applied owing to its corrective abilities in patients suffering from a stroke, multiple sclerosis, or spinal cord injury among other pathologies. This review aims at identifying the progress made in this area over the last two decades, addressing two main questions: What is the status of neuroprosthetic technology in terms of architecture, sensorization, and control algorithms?. What is the current evidence on its functional and clinical efficacy? The results reveal the importance of systems capable of self-adjustment and the need for closed-loop control systems to adequately modulate assistance in individual conditions. Other advanced strategies, such as combining variable and constant frequency pulses, could also play an important role in reducing fatigue and obtaining better therapeutic results. The field not only would benefit from a deeper understanding of the kinematic, kinetic and neuromuscular implications and effects of more promising assistance strategies, but also there is a clear lack of long-term clinical studies addressing the therapeutic potential of these systems. This review paper provides an overview of current system design and control architectures choices with regard to their clinical effectiveness. Shortcomings and recommendations for future directions are identified.

Experimental Implementation of Automatic Control of Posture-Dependent Stimulation in an Implanted Standing Neuroprosthesis

Knowledge of the upper extremity (UE) effort exerted under real-world conditions is important for understanding how persons with motor or sensory disorders perform the postural shifts necessary to complete many activities of daily living while standing. To this end, a feedback controller, named the “Posture Follower Controller”, was developed to aid in task-dependent posture shifting by individuals with spinal cord injury standing with functional neuromuscular stimulation. In this experimental feasibility study, the controller modulated activation to the paralyzed lower extremity muscles as a function of the position of overall center of pressure (CoP), which was prescribed to move in a straight line in forward and diagonal directions. Posture-dependent control of stimulation enabled leaning movements that translated the CoP up to 48 mm away from the nominal position during quiet standing. The mean 95% prediction ellipse area, a measure of the CoP dispersion in the forward, forward-right, and forward-left directions, was 951.0 ± 341.1 mm², 1095.9 ± 251.2 mm², and 1364.5 ± 688.2 mm², respectively. The average width of the prediction ellipses across the three directions was 15.1 mm, indicating that the CoP deviated from the prescribed path as task-dependent postures were assumed. The average maximal UE effort required to adjust posture across all leaning directions was 24.1% body weight, which is only slightly more than twice of what is required to maintain balance in an erect standing posture. These preliminary findings suggest that stimulation can be modulated to effectively assume user-specified, task-dependent leaning postures characterized by the CoP shifts that deviate away from the nominal position and which require moderate UE effort to execute.

A rodent brain-machine interface paradigm to study the impact of paraplegia on BMI performance

BACKGROUND

Most brain machine interfaces (BMI) focus on upper body function in non-injured animals, not addressing the lower limb functional needs of those with paraplegia. A need exists for a novel BMI task that engages the lower body and takes advantage of well-established rodent spinal cord injury (SCI) models to study methods to improve BMI performance.

NEW METHOD

A tilt BMI task was designed that randomly applies different types of tilts to a platform, decodes the tilt type applied and rights the platform if the decoder correctly classifies the tilt type. The task was tested on female rats and is relatively natural such that it does not require the animal to learn a new skill. It is self-rewarding such that there is no need for additional rewards, eliminating food or water restriction, which can be especially hard on spinalized rats. Finally, task difficulty can be adjusted by making the tilt parameters.

RESULTS

This novel BMI task bilaterally engages the cortex without visual feedback regarding limb position in space and animals learn to improve their performance both pre and post-SCI.Comparison with Existing Methods: Most BMI tasks primarily engage one hemisphere, are upper-body, rely heavily on visual feedback, do not perform investigations in animal models of SCI, and require nonnaturalistic extrinsic motivation such as water rewarding for performance improvement. Our task addresses these gaps.

CONCLUSIONS

The BMI paradigm presented here will enable researchers to investigate the interaction of plasticity after SCI and plasticity during BMI training on performance.

Intensity- and Duration-Adaptive Functional Electrical Stimulation Using Fuzzy Logic Control and a Linear Model for Dropfoot Correction

Functional electrical stimulation (FES) is important in gait rehabilitation for patients with dropfoot. Since there are time-varying velocities during FES-assisted walking, it is difficult to achieve a good movement performance during walking. To account for the time-varying walking velocities, seven poststroke subjects were recruited and fuzzy logic control and a linear model were applied in FES-assisted walking to enable intensity- and duration-adaptive stimulation (IDAS) for poststroke subjects with dropfoot. In this study, the performance of IDAS was evaluated using kinematic data, and was compared with the performance under no stimulation (NS), FES-assisted walking triggered by heel-off stimulation (HOS), and speed-adaptive stimulation. A larger maximum ankle dorsiflexion angle in the IDAS condition than those in other conditions was observed. The ankle plantar flexion angle in the IDAS condition was similar to that of normal walking. Improvement in the maximum ankle dorsiflexion and plantar flexion angles in the IDAS condition could be attributed to having the appropriate stimulation intensity and duration. In summary, the intensity- and duration-adaptive controller can attain better movement performance and may have great potential in future clinical applications.