Technical developments of functional electrical stimulation to restore gait functions : sensing, control strategies, and current commercial systems

The work presents a review on the technological advancements of functional electrical stimulation (FES) neuroprostheses to restore gait walking over the last decades. The aim of an FES intervention is to functionally restore and rehabilitate individuals with motor disorders, such as stroke, spinal cord injury, multiple sclerosis, and others. The technique has been applied for widespread practical use for several years due to the rapid development of micro- and nano-technology. This technical review covers neuroprostheses developed within academia and currently available on the market. These systems are thoroughly analyzed and discussed with particular emphasis on the sensing techniques and control strategies. In the last part, a combination of FES technology and exoskeletons is presented as an emerging solution to overcome the drawbacks of current FES-based neuroprostheses, and recommendations on future research direction are suggeste

Tracking human upper-limb movements with sliding mode control type-II fuzzy logic

© 2016 IEEE. A knowledge of human upper-limb structure and its mechanical functions are important for developing an exoskeleton. The Sliding Mode Control with Fuzzy Type-II is proposed to control the movements of the human extremity joints. The Lagrange method is used to model the dynamics system of human upper-limb. The findings demonstrate the effectiveness of the proposed controller in tracking the desired motion and it is also able to eliminate the chattering problem as well as deal with uncertainties

Equilibrium-point control of human elbow-joint movement under isometric environment by using multichannel functional electrical stimulation

Functional electrical stimulation (FES) is considered an effective technique for aiding quadriplegic persons. However, the human musculoskeletal system has highly nonlinearity and redundancy. It is thus difficult to stably and accurately control limbs using FES. In this paper, we propose a simple FES method that is consistent with the motion-control mechanism observed in humans. We focus on joint motion by a pair of agonist-antagonist muscles of the musculoskeletal system, and define theelectrical agonist-antagonist muscle ratio (EAA ratio) and electrical agonist-antagonist muscle activity (EAA activity) in light of the agonist-antagonist muscle ratio and agonist-antagonist muscle activity, respectively, to extract the equilibrium point and joint stiffness from electromyography (EMG) signals. These notions, the agonist-antagonist muscle ratio and agonist-antagonist muscle activity, are based on the hypothesis that the equilibrium point and stiffness of the agonist-antagonist motion system are controlled by the central nervous system. We derived the transfer function between the input EAA ratio and force output of the end-point. We performed some experiments in an isometric environment using six subjects. This transfer-function model is expressed as a cascade-coupled dead time element and a second-order system. High-speed, high-precision, smooth control of the hand force were achieved through the agonist-antagonist muscle stimulation pattern determined by this transfer function model

Modelling and EMG based Control of Upper Limb Exoskeletons for Hand Impairments

Functional losses associated with hand impairments have led to the growing development of hand exoskeletons. The main challenges are to develop the exoskeletons that work according to the user’s motion intention, which can be done by utilizing the electromyogram signals generated by forearm muscles contributed from the movement and/or grasping abilities of the hand. In this research, modelling and EMG based control of hand exoskeletons with the aim to assist stroke survivors in regaining their hand strength and functionality, and improve their quality of life is presented