A hybrid active force control of a lower limb exoskeleton for gait rehabilitation

Taha, Zahari; Majeed, Anwar P. P. Abdul; Abidin, Amar Faiz Zainal; Ali, Mohammed A. H.; Khairuddin, Ismail Mohd; Deboucha, Abdelhakim; Tze, Mohd Yashim Wong Paul

doi:10.1515/bmt-2016-0039

Cited by 16 publications

(9 citation statements)

References 26 publications

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“…Based on the above considerations, in the present paper we report a comprehensive dataset of kinematic, kinetic and EMG individual data measured on 50 healthy subjects of different ages (young, adult and elderly) during the following conditions: level walking at different velocities, toe- and heel-walking, and stairs ascending and descending. Possible applications of the data here reported are: providing age- and speed-matched normative reference for the analysis of altered gait in individual patients, developing/optimizing lower limb prostheses 19 , developing/testing simulation models of bipedal locomotion 20 , and developing control algorithms for bipedal robots 21 , active exoskeletons 22,23 or model-based Functional Electrical Stimulation systems 24 for motor rehabilitation.…”

Section: Background and Summarymentioning

confidence: 99%

Human kinematic, kinetic and EMG data during different walking and stair ascending and descending tasks

et al. 2019

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This paper reports the kinematic, kinetic and electromyographic (EMG) dataset of human locomotion during level walking at different velocities, toe- and heel-walking, stairs ascending and descending. A sample of 50 healthy subjects, with an age between 6 and 72 years, is included. For each task, both raw data and computed variables are reported including: the 3D coordinates of external markers, the joint angles of lower limb in the sagittal, transversal and horizontal anatomical planes, the ground reaction forces and torques, the center of pressure, the lower limb joint mechanical moments and power, the displacement of the whole body center of mass, and the surface EMG signals of the main lower limb muscles. The data reported in the present study, acquired from subjects with different ages, represents a valuable dataset useful for future studies on locomotor function in humans, particularly as normative reference to analyze pathological gait, to test the performance of simulation models of bipedal locomotion, and to develop control algorithms for bipedal robots or active lower limb exoskeletons for rehabilitation.

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Section: Background and Summarymentioning

confidence: 99%

Human kinematic, kinetic and EMG data during different walking and stair ascending and descending tasks

et al. 2019

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“…The main purpose of their use is to increase strength, speed, and performance. They are mainly used in the military, industry, and medicine, and their main application is carrying heavy loads [6,7]. They provide greater load carrying mobility with less load and allow the coverage of greater distances than present conditions allow in the field (infantry).…”

Section: Introductionmentioning

confidence: 99%

“…They make it possible to steer movements in the correct trajectories and help patients to relearn the correct movement patterns. They give the ability to walk to patients with a total or partial loss of gait control [6]. Hydraulic, pneumatic, or electric systems are used as exoskeleton actuators [8,9].…”

Section: Introductionmentioning

confidence: 99%

“…Hydraulic, pneumatic, or electric systems are used as exoskeleton actuators [8,9]. The advantages and disadvantages of each system are described in detail in Reference [6]. Typical examples of lower limb exoskeletons are ReWalk (Marlborough, MA, USA) and HAL (The Hybrid Assistive Limb, Gauken-Minami, Tsukuba, Ibaraki Prefecture, Japan) [10].…”

Section: Introductionmentioning

confidence: 99%

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A Kinematic Model of a Humanoid Lower Limb Exoskeleton with Hydraulic Actuators

Głowiński

Krzyżyński

Bryndal

et al. 2020

Sensors

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Although it is well-established that exoskeletons as robots attached to the extremities of the human body increase their strength, limited studies presented a computer and mathematical model of a human leg hydraulic exoskeleton based on anthropometric data. This study aimed to examine lower limb joint angles during walking and running by using Inertial Measurement Units. The geometry and kinematic parameters were calculated. Twenty-six healthy adults participated in walking and running experiments. The geometric model of a human leg hydraulic exoskeleton was presented. Joint angle data acquired during experiments were used in the mathematical model. The position and velocity of exoskeleton actuators in each phase of movement were calculated using the MATLAB package (Matlab_R2017b, The MathWorks Company, Novi, MI, USA). The highest velocity of the knee actuator during walking and running was in the swing phase, 0.3 and 0.4 m/s, respectively. For the ankle and hip joints, the highest velocity of actuators occurred during the push-off phase. The results with 26 healthy subjects demonstrated that the system's compliance can be effectively adjusted while guiding the subjects walking in predefined trajectories. The developed mathematical model makes it possible to determine the position of lower limb segments and exoskeleton elements. The proposed model allows for calculating the position of the human leg and actuators’ characteristic points.

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“…Proportional-Derivative (PD) based control shows good performance in the absence of disturbance [ 6 ], but usually suffers when the disturbance occurs in the system [ 7 ]. Particle swarm optimization (PSO) based active force rejection control is introduced in [ 8 ] for rejecting the disturbance in gait trajectory tracking requires evaluation of a large number of parameters. Computed-torque control (CTC) [ 9 , 10 ] depends on the exact model of the system and may require additional control to compensate for modeling errors.…”

Section: Introductionmentioning

confidence: 99%

Improved Active Disturbance Rejection Control for Trajectory Tracking Control of Lower Limb Robotic Rehabilitation Exoskeleton

Aole¹,

Elamvazuthi

Waghmare³

et al. 2020

Sensors

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Neurological disorders such as cerebral paralysis, spinal cord injuries, and strokes, result in the impairment of motor control and induce functional difficulties to human beings like walking, standing, etc. Physical injuries due to accidents and muscular weaknesses caused by aging affect people and can cause them to lose their ability to perform daily routine functions. In order to help people recover or improve their dysfunctional activities and quality of life after accidents or strokes, assistive devices like exoskeletons and orthoses are developed. Control strategies for control of exoskeletons are developed with the desired intention of improving the quality of treatment. Amongst recent control strategies used for rehabilitation robots, active disturbance rejection control (ADRC) strategy is a systematic way out from a robust control paradox with possibilities and promises. In this modern era, we always try to find the solution in order to have minimum resources and maximum output, and in robotics-control, to approach the same condition observer-based control strategies is an added advantage where it uses a state estimation method which reduces the requirement of sensors that is used for measuring every state. This paper introduces improved active disturbance rejection control (I-ADRC) controllers as a combination of linear extended state observer (LESO), tracking differentiator (TD), and nonlinear state error feedback (NLSEF). The proposed controllers were evaluated through simulation by investigating the sagittal plane gait trajectory tracking performance of two degrees of freedom, Lower Limb Robotic Rehabilitation Exoskeleton (LLRRE). This multiple input multiple output (MIMO) LLRRE has two joints, one at the hip and other at the knee. In the simulation study, the proposed controllers show reduced trajectory tracking error, elimination of random, constant, and harmonic disturbances, robustness against parameter variations, and under the influence of noise, with improvement in performance indices, indicates its enhanced tracking performance. These promising simulation results would be validated experimentally in the next phase of research.

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A hybrid active force control of a lower limb exoskeleton for gait rehabilitation

Cited by 16 publications

References 26 publications

Human kinematic, kinetic and EMG data during different walking and stair ascending and descending tasks

Human kinematic, kinetic and EMG data during different walking and stair ascending and descending tasks

A Kinematic Model of a Humanoid Lower Limb Exoskeleton with Hydraulic Actuators

Improved Active Disturbance Rejection Control for Trajectory Tracking Control of Lower Limb Robotic Rehabilitation Exoskeleton

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