Bio-Inspired Robotic Exoskeletons with Adaptive Electrical Control for Enhanced Upper Extremity Rehabilitation

Main Article Content

Trupti Yadav, Piyush S. Patil, Prashant Jadhav, Vivek Deshpande, Sandeep Shinde, Ashwin S. Chtpalliwar

Abstract

Robotic exoskeletons are a new and hopeful technology for rehabbing the upper limbs. They offer exact control and adjustable help to make traditional treatment more effective. This study suggests a new way to improve the recovery process that combines bio-inspired design with flexible electrical control. It is based on the way biological systems work. The suggested exoskeleton design is biomimetic, meaning that it looks and works like a human arm. This is done to make sure that the person can move naturally and comfortably. Lightweight, flexible materials make up the exoskeleton, which has sensors that track the user's movements and muscle activity. These monitors send input to the control system in real time, which lets it make changes that are more helpful for the user while they do different recovery routines. The control system uses an adaptable electrical treatment method that is based on how the human body controls its muscles. The control system constantly checks the user's muscle action and changes the amount of electrical stimulation to give the best support and help during recovery exercises. This flexible method makes sure that the exoskeleton's help is tailored to the person using it's wants and skills, which helps them recover more quickly. A bio-inspired robotic suit with adjustable electrical control is tested in a set of tests with healthy people and people who have had a stroke. The data show that the exoskeleton improves therapy for the upper limbs by giving individualized help and encouraging natural movement patterns. The adjustable electrical control makes it a lot easier for the user to do recovery exercises, which leads to better performance and a higher quality of life.

Article Details

Section
Articles
Author Biography

Trupti Yadav, Piyush S. Patil, Prashant Jadhav, Vivek Deshpande, Sandeep Shinde, Ashwin S. Chtpalliwar

[1]Dr. Trupti Yadav

2Piyush S. Patil

3Dr. Prashant Jadhav

4Dr. Vivek Deshpande

5Dr. Sandeep Shinde

6Dr. Ashwin S. Chtpalliwar

 

[1]Assistant Professor & HOD, Department of Oncology Physiotherapy, Krishna College of Physiotherapy,Krishna Vishwa Vidyapeeth (Deemed to be University), Karad. Email: drtruptiwarude@gmail.com

2Assistant Professor, Department of Electrical Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, Maharashtra, India. Email: psp4india16@gmail.com

3Assistant Professor, Department of Mechanical Engineering, Rajarambapu Institute of Technology, Islampur, Shivaji University, Kolhapur, Maharashtra, India. Email: prashant.jadhav@ritindia.edu

4Professor, Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, Maharashtra, India. Email: vivek.deshpande@viit.ac.in

5Associate Professor & HOD, Department of Musculoskeletal Physiotherapy, Krishna College of Physiotherapy, Krishna Vishwa Vidyapeeth (Deemed to be University), Karad.    Email: drsandeepshinde24@gmail.com 

6Associate Professor, Department of Industrial Engineering, Shri Ramdeobaba College of Engineering and Management, Nagpur, Maharashtra, India.

Corresponding: Piyush S. Patil (psp4india16@gmail.com)

 

References

Noda, T., Yamamoto, K., Nakazawa, K., & Kawashima, N. (2017). Bio-inspired design of a shoulder complex exoskeleton for the rehabilitation of shoulder impairments. Journal of Neuroengineering and Rehabilitation, 14(1), 1-14.

Zhang, Y., Chen, X., Zhang, S., & Zhang, L. (2018). A bio-inspired exoskeleton for elbow rehabilitation. Journal of Bionic Engineering, 15(2), 340-348.

Chen, C., Ye, M., Xie, Y., & Chen, X. (2016). Adaptive control of a robotic exoskeleton for upper-limb rehabilitation based on EMG signals. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(3), 314-323.

Kang, J., Kim, J., & Lee, J. (2019). Reinforcement learning-based adaptive control of a robotic exoskeleton for upper-limb rehabilitation. IEEE Transactions on Industrial Electronics, 66(12), 9727-9735.

Hu, H., Li, J., Yang, Z., & Sun, Y. (2018). Bio-inspired robotic exoskeleton with adaptive control for shoulder rehabilitation. Robotics and Autonomous Systems, 100, 101-109.

Li, M., Zhang, H., Zhang, Y., & Zhang, X. (2017). Bio-inspired robotic exoskeleton with adaptive control for wrist rehabilitation. International Journal of Advanced Robotic Systems, 14(4), 1729881417717698.

Birouaș, F.I.; Țarcă, R.C.; Dzitac, S.; Dzitac, I. Preliminary Results in Testing of a Novel Asymmetric Underactuated Robotic Hand Exoskeleton for Motor Impairment Rehabilitation. Symmetry 2020, 12, 1470.

VélezGuerrero, M.A.; CallejasCuervo, M.; Mazzoleni, S. Design, Development, and Testing of an Intelligent Wearable Robotic Exoskeleton Prototype for Upper Limb Rehabilitation. Sensors 2021, 21, 5411.

Gull, M.A.; Thoegersen, M.; Bengtson, S.H.; Mohammadi, M.; Andreasen Struijk, L.N.S.; Moeslund, T.B.; Bak, T.; Bai, S. A 4−DOF Upper Limb Exoskeleton for Physical Assistance: Design, Modeling, Control and Performance Evaluation. Appl. Sci. 2021, 11, 5865.

Li, N.; Yu, P.; Zhao, L.; Yang, T. Bioinspired wearable soft upperlimb exoskeleton robot for stroke survivors. In Proceedings of the 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO), Macau, China, 5–8 December 2017; pp. 2693–2698.

Ong, A.P.; Bugtaib, N.T. A Bioinspired Design of a Hand Robotic Exoskeleton for Rehabilitation. AIP Conf. Proc. 2018, 1933, 1–8.

Lenzi, T.; de Rossi, S. The neurorobotics paradigm: NEURARM, NEUROExos, HANDEXOS. In Proceedings of the 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, MN, USA, 3–6 September 2009; pp. 2430–2433.

Dinha, B.; Xiloyannis, M. Adaptive backlash compensation in upper limb soft wearable exoskeletons. Robot. Auton. Syst. 2017, 92, 173–186.

Cui, X.; Chen, W.; Jin, X.; Argawal, S.K. Design of a 7DOF CableDriven Arm Exoskeleton 11 (CAREX7) and a Controller for Dexterous Motion Training or Assistance. IEEE/ASME Trans. Mechatron. 2017, 22, 161–172.

Gonçalves, R.S.; Brito, L.S.F.; Moraes, L.P.; Carbone, G.; Ceccarelli, M. A fairly simple mechatronic device for training human wrist motion. Int. J. Adv. Robot. Syst. 2020, 17, 1–15.

Zhang, L.; Li, J.; Cui, Y.; Dong, M.; Fang, B.; Zhang, P. Design and performance analysis of a parallel wrist rehabilitation robot (PWRR). Rob. Auton. Syst. 2020, 125, 103390.

Xu, D.; Zhang, M.; Sun, Y.; Zhang, X.; Xu, H.; Li, Y.; Li, X.; Xie, S.Q. Development of a reconfigurable wrist rehabilitation device with an adaptive forearm holder. In Proceedings of the 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Auckland, New Zealand, 9–12 July 2018; pp. 454–459.

Anandpwar, W., Barhate, S., Limkar, S., Vyawahare, M., Ajani, S. N., & Borkar, P. (2023). Significance of Artificial Intelligence in the Production of Effective Output in Power Electronics. International Journal on Recent and Innovation Trends in Computing and Communication, 11(3s), 30–36.

Jeong, J.; Yasir, I.B.; Han, J.; Park, C.H.; Bok, S.K.; Kyung, K.U. Design of shape memory alloy-based soft wearable robot for assistingwrist motion. Appl. Sci. 2019, 9, 4025.

Wang, Y.; Xu, Q. Design and testing of a soft parallel robot based on pneumatic artificial muscles for wrist rehabilitation. Sci. Rep. 2021, 11, 1273.

Perry, J.C.; Rosen, J. Design of a 7 degree-of-freedom upper-limb powered exoskeleton. In Proceedings of the First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, Pisa, Italy, 20–22 February 2006; Volume 2006, pp. 805–810.