Stiffness-Observer-Based Adaptive Control of an Intrinsically Compliant Parallel Wrist Rehabilitation Robot

Goyal, Tanishka; Hussain, Shahid; Martinez-Marroquin, Elisa; Brown, Nicholas; Jamwal, Prashant K.

doi:10.1109/thms.2022.3211164

Cited by 8 publications

(3 citation statements)

References 44 publications

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“…An adaptive controller, based on the fuzzy model and stiffness-observer, governed the four BMAs, giving the robot end-effector three rotational degrees of freedom. Initial tests with three healthy individuals confirmed the controller's effectiveness in guiding the robot while accounting for the compliant and nonlinear nature of the BMAs, even adjusting for higher-stiffness areas within the wrist's range of motion [66]. In the same year, Goyal et al developed a trajectory-tracking controller for a wrist rehabilitation robot with three degrees of freedom.…”

Section: Parallel Robot For Wrist Rehabilitationmentioning

confidence: 95%

A Review of Parallel Robots: Rehabilitation, Assistance, and Humanoid Applications for Neck, Shoulder, Wrist, Hip, and Ankle Joints

Abarca,

Elias

2023

Robotics

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This review article presents an in-depth examination of research and development in the fields of rehabilitation, assistive technologies, and humanoid robots. It focuses on parallel robots designed for human body joints with three degrees of freedom, specifically the neck, shoulder, wrist, hip, and ankle. A systematic search was conducted across multiple databases, including Scopus, Web of Science, PubMed, IEEE Xplore, ScienceDirect, the Directory of Open Access Journals, and the ASME Journal. This systematic review offers an updated overview of advancements in the field from 2012 to 2023. After applying exclusion criteria, 93 papers were selected for in-depth review. This cohort included 13 articles focusing on the neck joint, 19 on the shoulder joint, 22 on the wrist joint, 9 on the hip joint, and 30 on the ankle joint. The article discusses the timeline and advancements of parallel robots, covering technology readiness levels (TRLs), design, the number of degrees of freedom, kinematics structure, workspace assessment, functional capabilities, performance evaluation methods, and material selection for the development of parallel robotics. It also examines critical technological challenges and future prospects in rehabilitation, assistance, and humanoid robots.

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Section: Parallel Robot For Wrist Rehabilitationmentioning

confidence: 95%

A Review of Parallel Robots: Rehabilitation, Assistance, and Humanoid Applications for Neck, Shoulder, Wrist, Hip, and Ankle Joints

Abarca,

Elias

2023

Robotics

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“…Collectively these methods are sometimes referred to as compliance control. Control algorithms simply referred to as fuzzy control are used in [23][24]. Experimental data is presented in [17] comparing a proposed fuzzy PID controller to standard PID with an unimpaired participant.…”

Section: B Fuzzy Logic Controlmentioning

confidence: 99%

Effectiveness of Intelligent Control Strategies in Robot-Assisted Rehabilitation—A Systematic Review

Felix Brown,

Quan Xie

2024

IEEE Trans. Neural Syst. Rehabil. Eng.

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This review aims to provide a systematic analysis of the literature focused on the use of intelligent control systems in robotics for physical rehabilitation, identifying trends in recent research and comparing the effectiveness of intelligence used in control, with the aim of determining important factors in robotassisted rehabilitation and how intelligent controller design can improve them. Seven electronic research databases were searched for articles published in the years 2015 -2022 with articles selected based on relevance to the subject area of intelligent control systems in rehabilitation robotics. It was found that the most common use of intelligent algorithms for control is improving traditional control strategies with optimization and learning techniques. Intelligent algorithms are also commonly used in sensor output mapping, model construction, and for various data learning purposes. Experimental results show that intelligent controllers consistently outperform non-intelligent controllers in terms of transparency, tracking accuracy, and adaptability. Active participation of the patients and lowered interaction forces are consistently mentioned as important factors in improving the rehabilitation outcome as well as the patient experience. However, there are limited examples of studies presenting experimental results with impaired participants suffering limited range of motion, so the effectiveness of therapy provided by these systems is often difficult to quantify. A lack of universal evaluation criteria also makes it difficult to compare control systems outside of articles which use their own comparison criteria.

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“…During conventional treatments, patients’ limb movements are carried out manually by the therapists. During the last two decades the use of robotic devices for upper limb physical therapy of stroke survivors [5] , [6] , [7] , [8] , [9] , [10] has gained popularity in rehabilitation clinics around the globe [11] , [12] , [13] , [14] , [15] . Several robotic systems have been developed and clinically evaluated with stroke survivors for upper limb rehabilitation [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Utilizing the intelligence edge framework for robotic upper limb rehabilitation in home

Jamwal¹,

Niyetkaliyev²,

Hussain³

et al. 2023

MethodsX

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Stiffness-Observer-Based Adaptive Control of an Intrinsically Compliant Parallel Wrist Rehabilitation Robot

Cited by 8 publications

References 44 publications

A Review of Parallel Robots: Rehabilitation, Assistance, and Humanoid Applications for Neck, Shoulder, Wrist, Hip, and Ankle Joints

A Review of Parallel Robots: Rehabilitation, Assistance, and Humanoid Applications for Neck, Shoulder, Wrist, Hip, and Ankle Joints

Effectiveness of Intelligent Control Strategies in Robot-Assisted Rehabilitation—A Systematic Review

Utilizing the intelligence edge framework for robotic upper limb rehabilitation in home

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