Robotic Knee Exoskeleton Prototype to Assist Patients in Gait Rehabilitation

Authors

  • Esteban Javier Mora Tola Universidad de Cuenca
  • Juan Loja-Duchi Universidad Internacional de la Rioja https://orcid.org/0000-0001-7595-1837
  • Andres Ordonez-Torres
  • Andres Vazquez-Rodas Department of Electrical, Electronic, and Telecommunications Engineering (DEET), Universidad de Cuenca, Cuenca, Ecuador. https://orcid.org/0000-0002-6114-1179
  • Fabian Astudillo-Salinas Department of Electrical, Electronic, and Telecommunications Engineering (DEET), Universidad de Cuenca, Cuenca, Ecuador.
  • Luis I. Minchala Department of Electrical, Electronic, and Telecommunications Engineering (DEET), Universidad de Cuenca, Cuenca, Ecuador. https://orcid.org/0000-0003-0822-0705

Keywords:

knee exoskeleton, emg signal processing, motion intention detection, rectus femoris, gait rehabilitation, Artificial Neural Network, remote supervision

Abstract

This paper presents the design and development of a low cost robotic knee exoskeleton with mobile interface for active assistance of gait rehabilitation of patients who suffer lower limb impairment. Interaction based on electromyography (EMG) is used for detecting motion intention to recognize muscular activity patterns by applying artificial neural network (ANN) algorithms. A comparison of muscular activity between the rectus femoris of each lower limb is made in order to find which offers better results. Once the system identifies a motion intention, it generates a predefined trajectory that mimics the gait cycle pattern of the knee joint. The actuator of the exoskeleton is required to accomplish this movement based on a position control strategy. The exoskeleton’s operation is supervised remotely through a mobile device, which is connected to a database that contains three rehabilitation routines previously set by medical staff. The robotic knee prototype is validated by monitoring its performance while being used, initially by healthy subjects.

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Author Biographies

Esteban Javier Mora Tola, Universidad de Cuenca

Esteban Mora-Tola received the B.S.E.E. degree from Universidad del Azuay, Cuenca, Ecuador, in 2011, and the M.S degree in Automatic control and Robotics from Universitat Polit`ecnica de Catalunya Barcelonatech (UPC), Barcelona, Spain, in 2016. He did a medical robotics internship in Neuromuscular & Rehabilitation Robotics Laboratory (NeuRRo Lab)- University of Michigan, Ann Arbor, United States, in 2016. Since 2017, he has been a researcher with the Department of Electrical, Electronic, and Telecommunications Engineering (DEET), Universidad de Cuenca, Cuenca, Ecuador. He is currently professor in the DEET. His research interests include biomedical signal processing, medical robotics and computer vision.

Juan Loja-Duchi, Universidad Internacional de la Rioja

Juan Loja-Duchi received the degree of Electronics and Telecommunications Engineer from University of Cuenca (Ecuador) in 2016. He participated in the 11th international Symposium on Medical Information Processing and Analysis (2015). He is currently studying a Master’s degree of Engineer in Mathematics and computing in the Universidad Internacional de la Rioja (Based in Spain). His research interests include the processing of biomedical signals and the study of robotics.

Andres Ordonez-Torres

Andres Ordonez-Torres received the degree of Electronics and Telecommunications Engineer from University of Cuenca (Ecuador) in 2016. He participated in 11th international Symposium on Medical Information Processing and Analysis (2015). He is currently working on software development. His research interests include the processing of biomedical signals and the study of robotics.

Andres Vazquez-Rodas, Department of Electrical, Electronic, and Telecommunications Engineering (DEET), Universidad de Cuenca, Cuenca, Ecuador.

Andres Vazquez-Rodas received the Electronics Engineering degree in 2004 from the Salesian Polytechnic University in Cuenca, Ecuador, the Master degree in Telematics Engineering (Honors) from Universidad de Cuenca – Ecuador in 2010, and the Ph.D. from the Networking Department of the Universitat Politècnica de Catalunya BarcelonaTech (UPC), Spain. He was also an assistant professor at the Universidad Polit´ecnica Salesiana until 2017. Since 2015 he is full time professor of the Universidad de Cuenca at the Electric, Electronic and Telecommunication Department (DEET). His research interests include wireless mesh networks, wireless sensor networks, industrial networking and complex systems.

Fabian Astudillo-Salinas, Department of Electrical, Electronic, and Telecommunications Engineering (DEET), Universidad de Cuenca, Cuenca, Ecuador.

Fabian Astudillo-Salinas received the B.S.E (C.S) degree from Universidad de Cuenca, Cuenca, Ecuador, in 2007, and the M.S. and Ph.D. degrees from the Institut National Polytechnique de Toulouse, Toulouse, France, in 2009 and 2013, respectively. Since 2013, he has been a Full-Time Researcher with the Department of Electrical, Electronic, and Telecommunications Engineering, Universidad de Cuenca, Cuenca, Ecuador. His research interests include network coding, wireless sensor networks, vehicular networks, networked control systems, simulation of networks, and performance of networks.

Luis I. Minchala, Department of Electrical, Electronic, and Telecommunications Engineering (DEET), Universidad de Cuenca, Cuenca, Ecuador.

Luis I. Minchala-Avila (M’05) received his B.S.E.E. degree in 2006 from the Salesian Polytechnic University in Cuenca, Ecuador, and his Ms.C and Ph.D. degrees from Instituto Tecnológico y de Estudios Superiores de Monterrey in Monterrey, México, in 2011 and 2014, respectively. During summer 2012 to summer 2013 he was a visiting scholar in Concordia University in Montreal, Canada. Between 2017-2018 he was a Postdoctoral Fellow at Tecnológico de Monterrey in the Climate Change Research Group. Currently, he is a full-time researcher with the Department of Electrical, Electronic and Telecommunications Engineering, Universidad de Cuenca, Ecuador. Dr. Minchala has authored and co-authored over 40 indexed publications, including journal articles, conference proceedings, book chapters, and a book.

References

S. F. dos Reis Alves, A. J. Uribe-Quevedo, I. N. da Silva, and H. Ferasoli Filho, “Pomodoro, a mobile robot platform for hand motion exercising,” in Biomedical Robotics and Biomechatronics (2014 5th IEEE RAS & EMBS International Conference on. IEEE, 2014, pp. 970–974.

J. Li, G. Chen, P. Thangavel, H. Yu, N. Thakor, A. Bezerianos, and Y. Sun, “A robotic knee exoskeleton for walking assistance and connectivity topology exploration in eeg signal,” in Biomedical Robotics and Biomechatronics (BioRob), 2016 6th IEEE International Conference on. IEEE, 2016, pp. 1068–1073.

S. Oh, E. Baek, S.-k. Song, S. Mohammed, D. Jeon, and K. Kong, “A generalized control framework of assistive controllers and its application to lower limb exoskeletons,” Robotics and Autonomous Systems, vol. 73, pp. 68–77, 2015.

Y. Ren and D. Zhang, “Fexo knee: A rehabilitation device for knee joint combining functional electrical stimulation with a compliant exoskeleton,” in Biomedical Robotics and Biomechatronics (2014 5th IEEE RAS & EMBS International Conference on. IEEE, 2014, pp. 683–688.

P. F´elix, J. Figueiredo, C. P. Santos, and J. C. Moreno, “Electronic design and validation of powered knee orthosis system embedded with wearable sensors,” in Autonomous Robot Systems and Competitions (ICARSC), 2017 IEEE International Conference on. IEEE, 2017, pp. 110–115.

P. A. G´omez, M. D. Rodr´ıguez, and V. Amela, “Dise˜no de dispositivo rob´otico para la rehabilitaci´on y diagnosis de extremidades inferiores,” 2017.

J. J. Craig, Introduction to robotics: mechanics and control. Pearson Prentice Hall Upper Saddle River, 2005, vol. 3.

H. Aguilar-Sierra, W. Yu, S. Salazar, and R. Lopez, “Design and control of hybrid actuation lower limb exoskeleton,” Advances in Mechanical Engineering, vol. 7, no. 6, 2015.

L. I. Minchala, F. Astudillo-Salinas, K. Palacio-Baus, and A. Vazquez-Rodas, “Mechatronic design of a lower limb exoskeleton,” in Design, Control and Applications of Mechatronic Systems in Engineering. InTech, 2017.

J. P. Loja Duchi and A. S. Ord´o˜nez Torres, “Dise˜no y construcci´on de un exoesqueleto de rodilla rob´otica para asistir a pacientes en etapas de rehabilitaci´on,” B.S. thesis, 2016.

C. C. Yang and D. A. Dennis, “Mobile-bearing total knee arthroplasty: Technique and clinical results,” Basics in Hip and Knee Arthroplasty-E-book, p. 280, 2015.

A. Rojas, A. Farfan, M. Ayavaca, V. Cardenas, E. Mora, S. Wong, and L. I. Minchala, “Single-channel electromyography based on arduino for analysis of the swing phase in normal gait,” in 2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON). IEEE, 2018, pp. 1–4.

N. Nazmi, M. A. Abdul Rahman, S.-I. Yamamoto, S. A. Ahmad, H. Zamzuri, and S. A. Mazlan, “A review of classification techniques of emg signals during isotonic and isometric contractions,” Sensors, vol. 16, no. 8, p. 1304, 2016.

Y.-L. Wang, A. W. Su, T.-Y. Han, C.-L. Lin, and L.-C. Hsu, “Emg based rehabilitation systems-approaches for als patients in different stages,” in Multimedia and Expo (ICME), 2015 IEEE International Conference on. IEEE, 2015, pp. 1–6.

S. Pasinetti, M. Lancini, I. Bodini, and F. Docchio, “A novel algorithm for emg signal processing and muscle timing measurement,” IEEE Transactions on Instrumentation and Measurement, vol. 64, no. 11, pp. 2995–3004, 2015.

Z. A. Wright, W. Z. Rymer, and M. W. Slutzky, “Reducing abnormal muscle coactivation after stroke using a myoelectric-computer interface: a pilot study,” Neurorehabilitation and neural repair, vol. 28, no. 5, pp. 443–451, 2014.

L. R. Altimari, J. L. Dantas, M. Bigliassi, T. F. D. Kanthack, A. C. de Moraes, and T. Abr˜ao, “Influence of different strategies of treatment muscle contraction and relaxation phases on emg signal processing and analysis during cyclic exercise,” in Computational Intelligence in Electromyography Analysis-A Perspective on Current Applications and Future Challenges. InTech, 2012.

A. Phinyomark, C. Limsakul, and P. Phukpattaranont, “Application of wavelet analysis in emg feature extraction for pattern classification,” Measurement Science Review, vol. 11, no. 2, pp. 45–52, 2011.

D. Bai, C. Xia, J. Yang, S. Zhang, Y. Jiang, and H. Yokoi, “Shoulder joint control method for smart prosthetic arm based on surface emg recognition,” in Information and Automation (ICIA), IEEE Int. Conference on. IEEE, 2016, pp. 1267–1272.

G. Morantes, G. Fern´andez, and M. Altuve, “A threshold-based approach for muscle contraction detection from surface emg signals,” in IX International Seminar on Medical Information Processing and Analysis. International Society for Optics and Photonics, 2013, pp. 89 220C.

R. T. Gulshan and M. Singh, “Analysis of emg signals based on wavelet transform–a review.”

R. H. Chowdhury, M. B. Reaz, M. A. B. M. Ali, A. A. Bakar, K. Chellappan, and T. G. Chang, “Surface electromyography signal processing and classification techniques,” Sensors, vol. 13, no. 9, pp. 12 431–12 466, 2013.

O. Wahyunggoro, H. A. Nugroho et al., “Dwt analysis of semg for muscle fatigue assessment of dynamic motion flexion-extension of elbow joint,” in Information Technology and Electrical Engineering (ICITEE), 2016 8th International Conference on. IEEE, 2016, pp. 1–6.

M. Hakonen, H. Piitulainen, and A. Visala, “Current state of digital signal processing in myoelectric interfaces and related applications,” Biomedical Signal Processing and Control, vol. 18, pp. 334–359, 2015.

A. Rojas, A. Farfan, E. Mora, L. I. Minchala, and S. Wong, “Assessing the snr influence in the estimation of the mean frequency of lower limbs semg signals,” IEEE Latin America Transactions, vol. 16, no. 8, pp. 2108–2114, 2018.

G. Wu, C. Wang, X. Wu, Z. Wang, Y. Ma, and T. Zhang, “Gait phase prediction for lower limb exoskeleton robots,” in Information and Automation (ICIA), 2016 IEEE International Conference on. IEEE, 2016, pp. 19–24.

P.-A. Willems, B. Schepens, and C. Detrembleur, “Marcha normal,” EMC-Kinesiterapia-Medicina F´ısica, vol. 33, no. 2, pp. 1–29, 2012.

C.-Y. Ko, J. Ko, H. J. Kim, and D. Lim, “New wearable exoskeleton for gait rehabilitation assistance integrated with mobility system,” International Journal of Precision Engineering and Manufacturing, vol. 17, no. 7, pp. 957–964, 2016.

R. F. da Silva, R. Filgueira, E. Deelman, E. Pairo-Castineira, I. M. Overton, and M. P. Atkinson, “Using simple pid controllers to prevent and mitigate faults in scientific workflows.” in WORKS@ SC, 2016, pp. 15–24.

Published

2021-03-13

How to Cite

Mora Tola, E. J., Loja-Duchi, J., Ordonez-Torres, A., Vazquez-Rodas, A., Astudillo-Salinas, F., & Minchala, L. I. (2021). Robotic Knee Exoskeleton Prototype to Assist Patients in Gait Rehabilitation. IEEE Latin America Transactions, 18(9), 1503–1510. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/1398