Document Type : Full Research Paper


1 M.Sc. Graduated, School of Mechanical and Mechatronics Engineering, Shahrood University of Technology, Shahrood, Iran

2 Assistant Professor, School of Mechanical and Mechatronics Engineering, Shahrood University of Technology, Shahrood, Iran



Nowadays, one of the most effective tools for restoring patients' mobility and muscles strength is the use of stationary cycling exercises and pedaling. In this study, two methods for the treatment of lower limbs are made possible by the design, control implementation, and construction of an intelligent exercise bike. According to the damage level, the patient will fall into the active-assisted training or passive training group. In a passive training program, patients do not have enough ability to pedal on the bike, so the motor will provide the power to reach a predefined pedaling speed. In this program, feet of patients will pedal at a constant speed above the speed patient is able to achieve compulsorily. In an active-assisted training program, the patient is already improved enough to have a higher ability to pedal at the same constant speed and the motor will provide less power according to the pedaling power of the patient. Hence, the provided power by the motor is set based on the provided force by the patient. In this study, it is aimed to design the control theory for these two treatment methods and this bike. Furthermore, speed control was done by force and speed feedback. Experimental and theoretical results showed that the implementation and equipping of stationary bike with the mentioned method has led the research to the goals of speed control for rehabilitation use. Eventually, the experimental results show an average accuracy of 98.71% for the passive method in the test sample reported in this study and 98.24% for the six tests after reaching a steady state speed. Also, these results are 96.33% for the active-assisted mode and for the test reported in this study; and 95.59% for four tests to reach the desired pedaling speed.


Main Subjects

  1. Hassan Mohammadi Abdar, “Development of an Intelligent Exercise Platform for Rehabilitation in Parkinson’s Disease,” Case Western Reserve University, 2014.
  2. Linder, “Motorized Bicycling May Improve Motor Function Recovery Among Patients With Stroke,” in Neurology Reviews, pp. 11–13, 2015.
  3. Bradley, C. Acosta-Marquez, M. Hawley, S. Brownsell, P. Enderby, and S. Mawson, “NeXOS – The Design, Development and Evaluation of a Rehabilitation System for the Lower Limbs,” Mechatronics, vol. 19, no. 2, pp. 247–257, Mar. 2009.
  4. L. Alberts, S. M. Linder, A. L. Penko, M. J. Lowe, and M. Phillips, “It’s not about the Bike, It’s About the Pedaling: Forced Exercise and Parkinson’s Disease,” Exerc. Sport Sci. Rev., vol. 39, no. 4, pp.177-86, Jul. 2011.
  5. Kim, H. Cho, Y. L. Kim, and S. Lee, “Effects of Stationary Cycling Exercise on the Balance and Gait Abilities of Chronic Stroke Patients,” J. Phys. Ther. Sci., vol. 27, no. 11, pp. 3529–3531, 2015.
  6. Stroh, “The Design of an Electro-Mechanical Bicycle for an Immersive Virtual Environment,” University of Iowa, 2017.
  7. H. Bamdad M, “Robotic rehabilitation with the elbow stiffness adjustability,” Modares Mech. Eng., vol. 14, no. 11, pp. 151–158, 2015.
  8. L. Ridgel, M. D. Muller, C.-H. Kim, E. J. Fickes, and T. O. Mera, “Acute Effects of Passive Leg Cycling on Upper Extremity Tremor and Bradykinesia in Parkinson’s Disease,” Phys. Sportsmed., vol. 39, no. 3, pp. 83–93, Sep. 2011.
  9. L. Ridgel, R. S. Phillips, B. L. Walter, F. M. Discenzo, and K. A. Loparo, “Dynamic High-Cadence Cycling Improves Motor Symptoms in Parkinson’s Disease,” Front. Neurol., vol. 6, pp. 1–8, Sep. 2015.
  10. A. Romero-Laiseca, L. S. Morelato, K. A. Hernandez-Ossa, A. Frizera, and T. F. Bastos-Filho, “Design and Development of Hardware and Software to Command a Motorized Exercise Static Bike,” IFMBE Proceedings, vol. 70, no. 1, pp. 609–617, 2019.
  11. V. S. Kaushik, “Model Based Design to Control DC Motor for Pedal Assist Bicycle,” in 2015 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), pp. 1–4, 2015.
  12. Hsueh and M. Tsai, “Reactive Torque Monitoring and Cycling Speed Control of a Belt-Driven Cycle Ergometer,” Control Eng. Pract., vol. 21, no. 11, pp. 1564–1576, Nov. 2013.
  13. Mohammadi-Abdar, A. L. Ridgel, F. M. Discenzo, and K. A. Loparo, “Design and Development of a Smart Exercise Bike for Motor Rehabilitation in Individuals With Parkinson’s Disease,” IEEE/ASME Trans. Mechatronics, vol. 21, no. 3, pp. 1650–1658, Jun. 2016.
  14. Romero-Laiseca, M.A., Cardoso, V., Pomer-Escher, A., Longo, B., Delisle-Rodriguez, D., Nascimento, S.S., Lima, J.P., Loterio, F.A., Frizera-Neto, A. and Bastos-Filho., “Towards a Lower-Limb Rehabilitation System Based on Motor Imagery and Motorized Pedal for Stroke Patients,” March, 2019.
  15. F. Sani, S. Abeywardena, and E. Psomopoulou, “Virtual interface for an active motorized pedal exerciser for human leg rehabilitation, ” Mediterranean Conference on Medical and Biological Engineering and Computing, pp. 1696-1705, Springer, Cham, 2020.
  16. Ambrosini, S. Ferrante, A. Pedrocchi, G. Ferrigno, and F. Molteni, “Cycling Induced by Electrical Stimulation Improves Motor Recovery in Postacute Hemiparetic Patients,” Stroke, vol. 42, no. 4, pp. 1068–1073, Apr. 2011.
  17. Stuckenschneider, I. Helmich, A. Raabe-Oetker, I. Froböse, and B. Feodoroff, “Active Assistive Forced Exercise Provides Long-term Improvement to Gait Velocity and Stride Length in Patients Bilaterally Affected by Parkinson’s Disease,” Gait Posture, vol. 42, no. 4, pp. 485–490, Oct. 2015.
  18. Qutubuddin, T. Reis, R. Alramadhani, D. X. Cifu, A. Towne, and W. Carne, “Parkinson’s Disease and Forced Exercise: A Preliminary Study,” Rehabil. Res. Pract., pp. 1–5, 2013.
  19. L. Ridgel, C. A. Peacock, E. J. Fickes, and C. Kim, “Active-Assisted Cycling Improves Tremor and Bradykinesia in Parkinson’s Disease,” Arch. Phys. Med. Rehabil., vol. 93, no. 11, pp. 2049–2054, Nov. 2012.
  20. Mohammadi-Abdar, A. L. Ridgel, F. M. Discenzo, R. S. Phillips, B. L. Walter, and K. A. Loparo, “Test and Validation of a Smart Exercise Bike for Motor Rehabilitation in Individuals With Parkinson’s Disease,” IEEE Trans. Neural Syst. Rehabil. Eng., vol. 24, no. 11, pp. 1254–1264, Nov. 2016.
  21. Bini, P. Hume, J. Croft, and A. Kilding, “Pedal force effectiveness in Cycling: a review of constraints and training effects,” J. Sci. Cycl., vol. 2, no. 1, pp. 11–24, 2013.
  22. H. Liu, Y. M. Li, and C. L. Wang, “Experiment Research on Control Method and Mathematic Models during Energy Storage to the Double Function Flywheel System,” Adv. Mater. Res., vol. 291–294, pp. 2814–2817, Jul. 2011.
  23. Syllignakis, P. Panagiotakopoulos, and E. Karapidakis, “Automatic Speed Controller of a DC Motor Using Arduino, for Laboratory Applications,” Eng. Ind. Ser., 2016.
  24. Alasooly, “Control Of Dc Motor Using Different Control Strategies,” Glob. J. Technol. Optim., vol. 2, no. 1, 2011.
  25. Akram Ahmad, “Speed Control of a DC Motor Using Controllers,” Autom. Control Intell. Syst., vol. 2, no. 6, pp. 1-9, 2014.
  26. Shahgholian and P. Shafaghi, “State Space Modeling and Eigenvalue Analysis of the Permanent Magnet DC Motor Drive System,” 2nd International Conference on Electronic Computer Technology, pp. 63–67, 2010.