Evidence map›Paper›PMID 32630115›Full record

ArticleSensors (Basel, Switzerland)2020

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

Sumit Aole, Irraivan Elamvazuthi, Laxman Waghmare, Balasaheb Patre, Fabrice Meriaudeau

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 50 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Sumit AoleDepartment of Instrumentation Engineering, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded 431606, Maharashtra, India.ORCID 0000-0002-2381-0685
Irraivan ElamvazuthiDepartment of Electrical & Electronic Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia.ORCID 0000-0002-4721-9400
Laxman WaghmareDepartment of Instrumentation Engineering, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded 431606, Maharashtra, India.
Balasaheb PatreDepartment of Instrumentation Engineering, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded 431606, Maharashtra, India.
Fabrice MeriaudeauImViA, University of Burgundy, Maison de l'université, 21078 Dijon, Le Creusot, France.
Université de Bourgogne · FRUniversiti Teknologi Petronas · MY

Funding

Universiti Teknologi Petronas 015LC0-243
6 · The paper itself

Abstract

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.

Indexed as

Exoskeleton DeviceLower ExtremityRoboticsHumansQuality of LifeRehabilitationWalkingimproved active disturbance rejection control (I-ADRC)linear extended state observer (LESO)lower limb robotic rehabilitation exoskeleton (LLRRE)nonlinear state error feedback (NLSEF)tracking differentiator (TD)trajectory tracking

Identifiers

PMID32630115
PMCPMC7374546
OpenAlexW3039329167

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.