An Impedance Control of Human Ankle Joint Using Functional Electrical Stimulation

Moon

IEEE Trans. Neural Syst. Rehabil. Eng.

2021

Self Cite

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 cocontraction 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).

Section: B Antagonistic Muscle Co-contraction Allocatormentioning

confidence: 99%

mentioning

confidence: 99%

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

Moon

IEEE Trans. Neural Syst. Rehabil. Eng.

2021

Self Cite

“…14,15 Kirsch et al 15 applied feedback control techniques which usually eliminated tracking error by increasing stimulation amplitude or frequency. Kim and Kim 16 applied an impedance control to the ankle joint to show adjustability of the ankle joint impedance through the FES application. Due to nonlinear dynamics of the musculoskeletal system, 17 several nonlinear identification 18 and control strategies have been used for the FES therapy including compensated feedback, 19 sliding mode control, 20 and nonlinear model predictive control.…”

Section: Introductionmentioning

confidence: 99%

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

Haghpanah

Farrokhnia

Taghvaei

et al. 2021

Proc Inst Mech Eng H

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.

Anais Estendidos Do XIII Simpósio Brasileiro De Robótica E XVIII Simpósio Latino Americano De Robótica (SBR/LARS Estendido 2021

“…The interaction between humans and robots is a challenge in the field of robotic rehabilitation, since such interaction should ensure the safety of the patient, meet the therapy requirements for each specific subject and satisfy the assist-as-needed paradigm, predicting the intention of movement of the user. Several interaction controls have been studied in order to reduce the risks and ensure the treatment efficacy: EMG-driven adaptive impedance control [Peña 2017], control strategy based on kinetic motor primitives [Nunes et al 2018], performance-based adaptive assistance controller [Bayon et al 2018], motor intention decoding algorithm [Pastore et al 2018], Markovian robust compliance control [Jutinico et al 2018], impedance control using functional electrical stimulation [Kim and Kim 2018].…”

Section: Introductionmentioning

confidence: 99%

Interaction models between humans and lower-limbs exoskeletons applied to robotic neurorehabilitation

Mosconi

Siqueira

2021

Development of interaction controls applied to robots of robotic-assisted therapy is a challenge, as it requires physical contact between human and robots, in addition to demanding a high cost of time and resources. The purpose of this work was to develop a human-exoskeleton interaction model and a imulation algorithm for development, validation and testing of interaction controls applied in robotic rehabilitation of lower-limbs. Two simulations with different interaction models and controls were run, combining experimental and computational data. The results obtained proved that both the interaction model and the simulation algorithm are feasible, useful, improving flexibility and agility for developing of interaction controls.