Controller design for upper limb motion using measurements of shoulder, elbow and wrist joints

Passive exercises are implemented by physiotherapists to people who have movement functionality loss due to any reason at their limbs for recovering all or a part of movement functionality. Physiotherapists are constantly repeating the passive therapy movements with patients. Nowadays, rehabilitatio...

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Bibliographic Details
Published in:Neural computing & applications 2018-07, Vol.30 (1), p.307-325
Main Authors: Eski, İkbal, Kırnap, Ahmet
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Computer simulation
Control systems design
Data Mining and Knowledge Discovery
Elbow (anatomy)
Image Processing and Computer Vision
Limbs
Neural networks
Original Article
Parameter identification
Patients
Probability and Statistics in Computer Science
Proportional integral derivative
Rehabilitation
Therapy
Tracking control
Trajectories
Wrist
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Summary:Passive exercises are implemented by physiotherapists to people who have movement functionality loss due to any reason at their limbs for recovering all or a part of movement functionality. Physiotherapists are constantly repeating the passive therapy movements with patients. Nowadays, rehabilitation devices which are capable of repeating therapy exercises and control techniques for that device are developing. For this reason, controller design for the angular trajectory of human shoulder, elbow and wrist joints is presented in this paper. This paper consists of two parts. At first part, patients who had loss of function at their upper limbs were identified and shoulder, elbow and wrist angular displacement parameters were obtained by means of sensors. At second part, three control structures were selected for tracking shoulder, elbow and wrist angle trajectories. According to the experimental and simulation results, neural network-based PID control structure is the best controller on tracking given trajectories.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-018-3522-1