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Ehsan Jafari |
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People
Director Researchers Ph.D. Candidate Students Alumni
 Ehsan Jafari was born in Khorram Abad, Iran in 1993. He received the B.Sc. degree in Electrical Engineering (Control) from the Shiraz University, Shiraz, Iran in 2015 and the M.Sc. degree in Biomedical Engineering-Bioelectric from the Iran University of Science and Technology (IUST), Tehran, Iran, in 2019. He was a Research Assistant at the Iran Neural Technology Research Centre (INTRC) from 2015 to 2020 where he was working on the national project of Paracycle which provides functional electrical stimulation (FES) cycling therapy for spinal cord injury (SCI) patients. His research interests include functional electrical stimulation (FES), neuromusculoskeletal modeling, nonlinear control theory, human-machine interface, and biomedical signal processing.
Research Activity
Functional electrical stimulation (FES) with a history of more than 50 years, is one of the most commonly used techniques for therapy, restoration and maintenance of vital functions in persons with upper motor neuron disease and intact lower motor neurons. By applying low-level electrical pulses to paralyzed muscles and generating artificial contractions, FES can restore movements like standing, walking, and cycling in lower limbs of spinal cord injury (SCI) patients. FES-cycling exercise has provided various physiological and psychological benefits for SCI patients. Improvements were reported in cardiovascular and pulmonary functions, peripheral circulation, muscle bulk and strength, gas exchange kinetics and aerobic metabolism, immune system function, and patients’ satisfaction and independency in daily life activities. In spite of the beneficial effects of FES-cycling exercise, this technique suffers from several issues. One of the major challenges facing the FES-cycling is the control issue. The previous methods for FES-cycling are based on the system modeling and require pre-adjustment of the control parameters which are based on the model parameters. In this work, a distributed cooperative control framework, which is based on cooperative adaptive higher-order sliding mode (HOSM) controllers, is proposed for simultaneous control of torque and cadence in FES-cycling. The adaptive HOSM is a robust free-model method which does not require any pre-adjustment of the control parameters and does not need the boundary of the disturbance to be known. Another major issue in FES-cycling is the stimulation pattern (i.e., the ranges of crank angle over which each muscle group is activated). In this work, an automatic pattern generator is proposed which is capable of providing not only the regions of the crank angle in which each muscle group should be stimulated but also a specific gain for each muscle group. The results of the simulation studies on a virtual patient and experiments on three paraplegic subjects shows that the proposed control strategy could achieve good simultaneous cadence and torque tracking performance and is robust against muscle fatigue and external disturbances during FES-induced pedaling. The proposed method significantly increases the efficiency and tracking accuracy of motor-assisted FES-cycling in paraplegic patients and decreases the power consumption.
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