Closed-Loop Functional Electrical Stimulation for Gait Training for Patients with Paraplegia

Bouri, Mohamed; Selfslagh, Aurelic; Campos, Debora S. F.; Yonamine, Seidi; Donati, Ana R. C.; Shokur, Solaiman

doi:10.1109/robio.2018.8665270

Cited by 3 publications

(3 citation statements)

References 27 publications

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“…The electrical stimulation was conducted using the ISTim Modular Stimulation System [26,27], which delivers biphasic squared electrical pulses. The electrical pulse parameters range between 0-50 V, 0-503 µs, and 0-200 Hz, for pulse amplitude, width, and frequency, respectively [33].…”

Section: Functional Electrical Stimulationmentioning

confidence: 99%

“…Despite major contributions regarding the use of recurrent neural networks, further exploration of FES control strategies using user-specific muscle models in human subjects is still needed towards achieving assisted-as-needed FES. Trajectory tracking control strategies, ranging from using single feedback controllers [17,20,21] to single feedforward models [17] or feedforward models combined with feedback controllers [22][23][24][25][26]. Müller et al [27] proposed the ILC strategy in a learning full-leg supporting neuroprosthesis to control the antagonistic muscle pairs for knee flexion and extension and for ankle joint dorsi-and plantarflexion during all gait phases.…”

Section: Introductionmentioning

confidence: 99%

“…The ILC presented promising results in improving the gait of incomplete spinal cord injury subjects; however, the automatic ILC gain tuning could not find adequate parameters for all subjects, demanding manual configuration. Bouri et al [26] proposed a feedforward and feedback control strategy for tracking the knee angle trajectory in paraplegic patients, demonstrating the importance of using a single feedforward component (predefined muscle activation patterns) to effectively reduce time delay. The works developed by Ferrarin et al [24] and Ferrante et al [25] relied on the use of goniometers to accurately track the knee extension trajectory by determining the stimulation pulse width.…”

Section: Introductionmentioning

confidence: 99%

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Functional Electrical Stimulation System for Drop Foot Correction Using a Dynamic NARX Neural Network

et al. 2021

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Neurological diseases may reduce Tibialis Anterior (TA) muscle recruitment capacity causing gait disorders, such as drop foot (DF). The majority of DF patients still retain excitable nerves and muscles which makes Functional Electrical Stimulation (FES) an adequate technique to restore lost mobility. Recent studies suggest the need for developing personalized and assist-as-needed control strategies for wearable FES in order to promote natural and functional movements while reducing the early onset of fatigue. This study contributes to a real-time implementation of a trajectory tracking FES control strategy for personalized DF correction. This strategy combines a feedforward Non-Linear Autoregressive Neural Network with Exogenous inputs (NARXNN) with a feedback PD controller. This control strategy advances with a user-specific TA muscle model achieved by the NARXNN’s ability to model dynamic systems relying on the foot angle and angular velocity as inputs. A closed-loop, fully wearable stimulation system was achieved using an ISTim stimulator and wearable inertial sensor for electrical stimulation and user’s kinematic gait sensing, respectively. Results showed that the NARXNN architecture with 2 hidden layers and 10 neurons provided the highest performance for modelling the kinematic behaviour of the TA muscle. The proposed trajectory tracking control revealed a low discrepancy between real and reference foot trajectories (goodness of fit = 77.87%) and time-effectiveness for correctly stimulating the TA muscle towards a natural gait and DF correction.

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Section: Functional Electrical Stimulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Functional Electrical Stimulation System for Drop Foot Correction Using a Dynamic NARX Neural Network

et al. 2021

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Wearable Lower Limb Neuroprosthesis: System Architecture and Control Tuning

Carvalho

Figueiredo

Santos

2022

Robotics in Natural Settings

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Transcutaneous Functional Electrical Stimulation Controlled by a System of Sensors for the Lower Limbs: A Systematic Review

Chaikho

Clark²,

Raison

2022

Sensors

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In the field of transcutaneous functional electrical stimulation (FES), open-loop and closed-loop control strategies have been developed to restore functions of the lower limbs: walking, standing up, maintaining posture, and cycling. These strategies require sensors that provide feedback information on muscle activity or biomechanics of movement. Since muscle response induced by transcutaneous FES is nonlinear, time-varying, and dependent on muscle fatigue evolution, the choice of sensor type and control strategy becomes critical. The main objective of this review is to provide state-of-the-art, emerging, current, and previous solutions in terms of control strategies. Focus is given on transcutaneous FES systems for the lower limbs. Using Compendex and Inspec databases, a total of 135 review and conference articles were included in this review. Recent studies mainly use inertial sensors, although the use of electromyograms for lower limbs has become more frequent. Currently, several researchers are opting for nonlinear controllers to overcome the nonlinear and time-varying effects of FES. More development is needed in the field of systems using inertial sensors for nonlinear control. Further studies are needed to validate nonlinear control systems in patients with neuromuscular disorders.

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Closed-Loop Functional Electrical Stimulation for Gait Training for Patients with Paraplegia

Cited by 3 publications

References 27 publications

Functional Electrical Stimulation System for Drop Foot Correction Using a Dynamic NARX Neural Network

Functional Electrical Stimulation System for Drop Foot Correction Using a Dynamic NARX Neural Network

Wearable Lower Limb Neuroprosthesis: System Architecture and Control Tuning

Transcutaneous Functional Electrical Stimulation Controlled by a System of Sensors for the Lower Limbs: A Systematic Review

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