Speed-adaptive control of functional electrical stimulation for dropfoot correction

A new modular neuroprosthesis suitable for hybrid FES-robot applications and tailored assistance

BACKGROUND

To overcome the application limitations of functional electrical stimulation (FES), such as fatigue or nonlinear muscle response, the combination of neuroprosthetic systems with robotic devices has been evaluated, resulting in hybrid systems that have promising potential. However, current technology shows a lack of flexibility to adapt to the needs of any application, context or individual. The main objective of this study is the development of a new modular neuroprosthetic system suitable for hybrid FES-robot applications to meet these needs.

METHODS

In this study, we conducted an analysis of the requirements for developing hybrid FES-robot systems and reviewed existing literature on similar systems. Building upon these insights, we developed a novel modular neuroprosthetic system tailored for hybrid applications. The system was specifically adapted for gait assistance, and a technological personalization process based on clinical criteria was devised. This process was used to generate different system configurations adjusted to four individuals with spinal cord injury or stroke. The effect of each system configuration on gait kinematic metrics was analyzed by using repeated measures ANOVA or Friedman's test.

RESULTS

A modular NP system has been developed that is distinguished by its flexibility, scalability and personalization capabilities. With excellent connection characteristics, it can be effectively integrated with robotic devices. Its 3D design facilitates fitting both as a stand-alone system and in combination with other robotic devices. In addition, it meets rigorous requirements for safe use by incorporating appropriate safety protocols, and features appropriate battery autonomy, weight and dimensions. Different technological configurations adapted to the needs of each patient were obtained, which demonstrated an impact on the kinematic gait pattern comparable to that of other devices reported in the literature.

CONCLUSIONS

The system met the identified technical requirements, showcasing advancements compared to systems reported in the literature. In addition, it demonstrated its versatility and capacity to be combined with robotic devices forming hybrids, adapting well to the gait application. Moreover, the personalization procedure proved to be useful in obtaining various system configurations tailored to the diverse needs of individuals.

Biomimetic Peripheral Nerve Stimulation Promotes the Rat Hindlimb Motion Modulation in Stepping: An Experimental Analysis

Peripheral nerve stimulation is an effective neuromodulation method in patients with lower extremity movement disorders caused by stroke, spinal cord injury, or other diseases. However, most current studies on rehabilitation using sciatic nerve stimulation focus solely on ankle motor regulation through stimulation of common peroneal and tibial nerves. Using the electrical nerve stimulation method, we here achieved muscle control via different sciatic nerve branches to facilitate the regulation of lower limb movements during stepping and standing. A map of relationships between muscles and nerve segments was established to artificially activate specific nerve fibers with the biomimetic stimulation waveform. Then, characteristic curves depicting the relationship between neural electrical stimulation intensity and joint control were established. Finally, by testing the selected stimulation parameters in anesthetized rats, we confirmed that single-cathode extraneural electrical stimulation could activate combined movements to promote lower limb movements. Thus, this method is effective and reliable for use in treatment for improving and rehabilitating lower limb motor dysfunction.

Effects of Functional Electrical Stimulation on Gait Characteristics in Healthy Individuals: A Systematic Review

BACKGROUND

This systematic review aimed to provide a comprehensive overview of the effects of functional electrical stimulation (FES) on gait characteristics in healthy individuals.

METHODS

Six electronic databases (PubMed, Embase, Epistemonikos, PEDro, COCHRANE Library, and Scopus) were searched for studies evaluating the effects of FES on spatiotemporal, kinematic, and kinetic gait parameters in healthy individuals. Two examiners evaluated the eligibility and quality of the included studies using the PEDro scale.

RESULTS

A total of 15 studies met the inclusion criteria. The findings from the literature reveal that FES can be used to modify lower-limb joint kinematics, i.e., to increase or reduce the range of motion of the hip, knee, and ankle joints. In addition, FES can be used to alter kinetics parameters, including ground reaction forces, center of pressure trajectory, or knee joint reaction force. As a consequence of these kinetics and kinematics changes, FES can lead to changes in spatiotemporal gait parameters, such as gait speed, step cadence, and stance duration.

CONCLUSIONS

The findings of this review improve our understanding of the effects of FES on gait biomechanics in healthy individuals and highlight the potential of this technology as a training or assistive solution for improving gait performance in this population.

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.

An adaptive reflexive control strategy for walking assistance system based on functional electrical stimulation

Functional electrical stimulation (FES) neuroprostheses have been regarded as an effective approach for gait rehabilitation and assisting patients with stroke or spinal cord injuries. A multiple-channel FES system was developed to improve the assistance and restoration of lower limbs. However, most neuroprostheses need to be manually adjusted and cannot adapt to individual needs. This study aimed to integrate the purely reflexive FES controller with an iterative learning algorithm while a multiple-channel FES walking assistance system based on an adaptive reflexive control strategy has been established. A real-time gait phase detection system was developed for accurate gait phase detection and stimulation feedback. The reflexive controller generated stimulation sequences induced by the gait events. These stimulation sequences were updated for the next gait cycle through the difference between the current and previous five gait cycles. Ten healthy young adults were enrolled to validate the multiple-channel FES system by comparing participants' gait performance to those with no FES controller and purely reflexive controller. The results showed that the proposed adaptive FES controller enabled the adaption to generate fitted stimulation sequences for each participant during various treadmill walking speeds. The maximum, minimum, and range of motion (ROM) of the hip, knee, and ankle joints were furtherly improved for most participants, especially for the hip and knee flexion and ankle dorsiflexion compared with the purely reflexive FES control strategy. The presented system has the potential to enhance motor relearning and promote neural plasticity.

Gait Biomechanics for Fall Prevention among Older Adults

In our currently ageing society, fall prevention is important for better healthy life expectancy and sustainable healthcare systems. While active outdoor walking is recommended as adequate exercise for the senior population, falls due to tripping and slipping exist as the primary causes of severe injuries. Minimum foot clearance (MFC) is the lowest vertical height of the foot during the mid-swing phase and indicates the risk of tripping. In contrast, coefficient of friction (COF) factors determine the occurrence of falls from slipping. Optimisation of the MFC and the COF for every step cycle prevents tripping and slipping, respectively. Even after the initiation of hazardous balance loss (i.e., tripping and slipping), falls can still be prevented as long as the requirements for balance are restored. Biomechanically, dynamic balance is defined by the bodily centre of mass and by the base of support: spatially—margin of stability and temporally—available response time. Fall prevention strategies should, therefore, target controlling the MFC, the COF and dynamic balance. Practical intervention strategies include footwear modification (i.e., shoe-insole geometry and slip-resistant outsoles), exercise (i.e., ankle dorsiflexors and core stabilisers) and technological rehabilitation (i.e., electrical stimulators and active exoskeletons). Biomechanical concepts can be practically applied to various everyday settings for fall prevention among the older population.

Modeling Ankle Torque and Stiffness Induced by Functional Electrical Stimulation

Functional electrical stimulation (FES) is commonly used for individuals with neuromuscular impairments to generate muscle contractions. Both joint torque and stiffness play important roles in maintaining stable posture and resisting external disturbance. However, most previous studies only focused on the modulation of joint torque using FES while ignoring the joint stiffness. A model that can simultaneously modulate both ankle torque and stiffness induced by FES was investigated in this study. This model was composed of four subparts including an FES-to-activation model, a musculoskeletal geometry model, a Hill-based muscle-tendon model, and a joint stiffness model. The model was calibrated by the maximum voluntary contraction test of the tibialis anterior (TA) and gastrocnemius medial (GAS) muscles. To validate the model, the estimated torque and stiffness by the model were compared with the measured torque and stiffness induced by FES, respectively. The results showed that the proposed model can estimate torque and stiffness with electrically stimulated TA or/and GAS, which was significantly correlated to the measured torque and stiffness. The proposed model can modulate both joint torque and stiffness induced by FES in the isometric condition, which can be potentially extended to modulate the joint torque and stiffness during FES-assisted walking.

Iterative Adjustment of Stimulation Timing and Intensity During FES-Assisted Treadmill Walking for Patients After Stroke

Functional electric stimulation (FES) is a common intervention to correct foot drop for patients after stroke. Due to the disturbances from internal time-varying muscle characteristics under electrical stimulation and external environmental uncertainties, most of the existing FES system used pre-set stimulation parameters and cannot achieve good gait performances during FES-assisted walking. Therefore, an adaptive FES control system, which used the iterative learning control to adjust the stimulation intensity based on kinematic data and a linear model to modulate the stimulation timing based on walking speed during FES-assisted treadmill walking, was designed and tested on ten patients with foot drop after stroke. In order to examine its orthotic effects, the kinematic data of the patients using the proposed control strategy were collected and compared with the data of the same patients walking using other three FES control strategies, including (1) constant pre-set stimulation intensity and timing, (2) constant pre-set stimulation intensity with speed-adaptive stimulation timing and (3) walking without FES intervention. The error between the maximum ankle dorsiflexion angle during swing phase and the target angle using the proposed control strategy was the smallest among the four conditions. Moreover, there was no significant difference in the ankle plantar flexion angle at the toe-off event and the maximum knee flexion angle during swing phase between the proposed control strategy and walking without FES. In summary, the proposed control strategy can improve FES-assisted walking performances through adaptive modulation of stimulation timing and intensity when coping with variation, and may have good potential in clinic.

Flatness of musculoskeletal systems under functional electrical stimulation

Control of musculoskeletal yy system through functional electrical stimulation (FES) still remains a complex and a challenging process. Indeed, the used musculoskeletal models are often complex and highly nonlinear, which makes their control and inversion (getting appropriate inputs from a desired outputs) very difficult. On the other hand, the system flatness has been proved to be an efficient method for nonlinear system control, since in this technique, the nonlinear system can be controlled more easily through its flat outputs. Therefore, it is very promising to apply this control technique on the musculoskeletal system, to overcome its problems, which has never been explored so far. The aim of this work is to explore the flatness technique and its feasibility on the knee joint musculoskeletal system in dynamic condition, controlled by electrically stimulated quadriceps muscle. A mathematical proof developed in the current work highlights that the two-input musculoskeletal system is flat, where two flat outputs are the muscle stiffness and the knee joint angle. It also shows that the single-input musculoskeletal system is not flat. These results are crucial for flatness-based control of musculoskeletal systems, since this model in literature deals with a single input. Simulation results in open-loop control of two-input system highlight the consistency of the mathematical proof, and the applicability of this technique on the musculoskeletal system, where its simulated outputs fit perfectly with the desired ones if the model is considered perfect. When, one parameter of the system is not well estimated (10% of error), simulations show limits of open-loop control, with a joint angle rms deviation of 4%; hence, the closed-loop control should be considered. Graphical Abstract Flatness Study and control of Musculoskeletal systems.