Design of controller and intelligent adaptive neural identifier for innovative knee rehabilitation devices

Document Type : Article

Authors

F‌a‌c‌u‌l‌t‌y o‌f M‌e‌c‌h‌a‌n‌i‌c‌a‌l E‌n‌g‌i‌n‌e‌e‌r‌i‌n‌g U‌n‌i‌v‌e‌r‌s‌i‌t‌y o‌f T‌e‌h‌r‌a‌n

Abstract

Continuous passive motion devices commonly referred to as "CPM" devices are used to maintain and restore joint range of motions. However, this device has been used for many years in joint rehabilitation. It is used especially for the knee, but new research has underestimated the clinical value of this device, which is also available in Iran at a high price and has recommended the development of its capabilities. Therefore, an innovative device with extensive capabilities has been designed to rehabilitate the knee, for which a control system is presented in this article. This system is a combination of CPM device as light as possible and a stationary bike. At the beginning of the treatment cycle, the patient regains a range of motions for his knee with the CPM device and then, regains his muscular strength and balance with the help of a stationary bike (which can maintain a speed of 35 rpm). Using a driving force to create both user modes to reduce production costs and increase economic feasibility is one of the design principles of this system and one of its innovations. On the other hand, the device is designed to be usable for a wide range of patients and its structure can change dimensions in a range. Therefore, the most reasonable way to control this system is to use an adaptive control system. Due to the interaction of the system with humans, PID structure has been used to ensure the stability of the system. One of the most important results presented is the design of an adaptive intelligent identifier and controller for this system. The purpose of designing the intelligent identifier is to create an approximate model for estimating the system's online operating point, which is provided to the adaptive intelligent PID controller to update its coefficients depending on the status of the controlled plant.

Keywords


1. Harvey, Lisa A., Lucie Brosseau. and Robert D. Herbert. \Continuous passive motion following total knee arthroplasty in people with arthritis", Cochrane Database of Systematic Reviews (2014). 2. https://helpmedicalsupplies.com/products/phoenixknee- cpm-machine. 3. \Chattanooga Active-K", https://www. chattanoogarehab.com/chattanooga-active-k-80-00-072- int. 4. Adli, M.A., Tacgln, E. and Akdogan, E. \Knee rehabilitation using an intelligent robotic system", (2009). 5. Golgouneh, A., Bamshad, A., Tarvirdizadeh, B. and et al. \Design of a new, light and portable mechanism for knee CPM machine with a user-friendly interface", In 2016 Arti cial Intelligence and Robotics (IRANOPEN), IEEE 103-8 (2016). 6. Rajestari, Z., Feizi, N. and Taghvaei, S. \Kinematic synthesis and optimization of continuous passive motion mechanisms for knee", In 2017 7th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO), pp. 1-6 (2017). 7. Rupali, N. JoshiPT, PhD, MEdPeter B.WhiteBAMary Murray-WeirPT, MBAMichael M.AlexiadesMDThomas P.SculcoMDAmar S.RanawatMD. \Prospective randomized trial of the ecacy of continuous passive motion post total knee arthroplasty, experience of the hospital for special surgery", The Journal of Arthroplasty, 30(12), pp. 2364-2369 (December 2015). 8. Martin Schulza., Bernhard Krohneb., Wolfgang Roderc. and et al. \Randomized, prospective, monocentric study to compare the outcome of continuous passive motion and controlled active motion after total knee arthroplasty", (31 January 2018). 9. Domen Novak, Robert Riener. \Control strategies and arti cial intelligence in rehabilitation robotics", Association for the Advancement of Arti cial Intelligence. ISSN 0738-4602 (2015).