Research Article
BibTex RIS Cite

Investigation of EMG Signals in Lower Extremity Muscle Groups During Robotic Gait Exercises

Year 2019, Special Issue 2019, 109 - 118, 31.10.2019
https://doi.org/10.31590/ejosat.637577

Abstract

Many people have been exposed to lower extremity function losses due to neurological, pathological or traffic accidents. In the physical therapy and rehabilitation of these patients, treatment programs based on robotic systems have started to be preferred instead of conventional methods. In robotic gait rehabilitation, mobilized lower extremity exoskeletons such as Rewalk or un-mobilized lower extremity exoskeletons such as RoboGait are used. It is important to evaluate the rehabilitation process in patients with lower extremity problems. Measurement of surface electromyogram (EMG) signals during the treatment process give information about the functional activities of the muscles. Obtained information plays an important role in determining the intention of patient motion in musculoskeletal design and musculoskeletal activities of the musculoskeletal. Changes in muscle activation timing and amplitude during the use of lower extremity exoskeleton can be determined by analysis of EMG. In this study, muscles involved in walking movement during robotic rehabilitation were examined. The examined iliopsoas, gluteus maximus, gluteus medius muscles provide flexion, extension and abduction movements of the hip, while the medial gastrocnemius and tibialis anterior muscles perform flexion and dorsiflexion movements of the foot. During the gait, the knee joint patency is controlled by the Vastus Medialis and Biceps Femoris muscles. In this study, while 6 patients with lower limb dysfunction were walking on the RoboGait device, the muscle activation potentials obtained from 7 different muscle groups were transferred to the computer simultaneously and wirelessly and displayed in the Matlab environment. The EMG signals measured with the MicroCor Lab device are shaped according to the activation of the muscles during walking. The electrode placement plan is critical for the analysis of EMG signals, and an appropriate electrode placement plan was obtained as a result of the study. Examined measured signals by following with the electrode placement plan, the maximum gluteus and iliopsoas muscles responsible for the extension and flexion movements of the hips are more effective during walking. Gletous maximum muscle was found to be the most effective muscle in walking while the iliopsoas muscle group was involved in the first movement of the leg. As a result of this study, these findings will help to follow the development of the treatment process and to develop EMG controlled mobilized lower extremity exoskeletons.

Thanks

We would like to thank Erciyes Scientific Research Projects Office for financial support. In addition, we would like to thank Adana City Hospital Management for its contribution to the Ethics Committee. In particular, we would like to thank the Renaissance Business Services who own and allow the use of the RoboGait device and Fimer Private Health Services responsible for the use of the device. We would like to thank Dr. Turgay Özcüler and Dr.Halit Fidancı for their contribution to the evaluation of EMG signals.

References

  • AbdulKareem, A. H., Adila, A. S., & Husi, G. (2018). Recent trends in robotic systems for upper-limb stroke recovery: A low-cost hand and wrist rehabilitation device. Paper presented at the 2018 2nd International Symposium on Small-scale Intelligent Manufacturing Systems (SIMS).
  • Antonucci, G., & Paolucci, S. (2018). Tailored, Technological Therapy: Physician and Therapists Point of View on Robotic Rehabilitation. Paper presented at the Converging Clinical and Engineering Research on Neurorehabilitation III: Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018), October 16-20, 2018, Pisa, Italy.
  • Chen, B., Ma, H., Qin, L.-Y., Gao, F., Chan, K.-M., Law, S.-W., . . . Liao, W.-H. (2016). Recent developments and challenges of lower extremity exoskeletons. Journal of Orthopaedic Translation, 5, 26-37.
  • Chen, B., Zi, B., Wang, Z., Qin, L., & Liao, W.-H. (2019). Knee exoskeletons for gait rehabilitation and human performance augmentation: A state-of-the-art. Mechanism and Machine Theory, 134, 499-511.
  • Fernandes, P. N., Figueredo, J., Moreira, L., Félix, P., Correia, A., Moreno, J. C., & Santos, C. P. (2019). EMG-based Motion Intention Recognition for Controlling a Powered Knee Orthosis. Paper presented at the 2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC).
  • Schmitz, A., Silder, A., Heiderscheit, B., Mahoney, J., & Thelen, D. G. (2009). Differences in lower-extremity muscular activation during walking between healthy older and young adults. Journal of electromyography and kinesiology, 19(6), 1085-1091.
  • Schwartz, I., & Meiner, Z. (2015). Robotic-assisted gait training in neurological patients: who may benefit? Annals of biomedical engineering, 43(5), 1260-1269.
  • Wilcox, M., Rathore, A., Ramirez, D. Z. M., Loureiro, R. C., & Carlson, T. (2016). Muscular activity and physical interaction forces during lower limb exoskeleton use. Healthcare technology letters, 3(4), 273-279.
  • Wu, X., Liu, D.-X., Liu, M., Chen, C., & Guo, H. (2018). Individualized gait pattern generation for sharing lower limb exoskeleton robot. IEEE Transactions on Automation Science and Engineering, 15(4), 1459-1470.
  • Yepes, J. C., Portela, M. A., Saldarriaga, Á. J., Pérez, V. Z., & Betancur, M. J. (2019). Myoelectric control algorithm for robot-assisted therapy: a hardware-in-the-loop simulation study. Biomedical engineering online, 18(1), 3.

Robotik Yürüme Egzersizleri Sırasında Alt Ekstremite Kas Gruplarındaki EMG İşaretlerinin İncelenmesi

Year 2019, Special Issue 2019, 109 - 118, 31.10.2019
https://doi.org/10.31590/ejosat.637577

Abstract

Birçok kişi nörolojik, patolojik veya trafik kazası gibi nedenlerle alt eksremite fonksiyon kayıplarına maruz kalmaktadır. Bu hastaların fizik tedavi ve rehabilitasyonunda konvaksiyonel yöntemler yerine robotik sistemlere dayalı tedavi programları tercih edilmeye başlanmıştır. Robotik yürüme rehabilitasyonun da Rewalk gibi mobilize alt ekstremite dış iskeletleri veya RoboGait gibi sabit alt ekstremite dış iskeletleri kullanılmaktadır. Alt ekstremite sorunu yaşayan hastalarda rehabilitasyon sürecinin değerlendirilmesi önem arz etmektedir. Tedavi sürecinde yüzey elektromiyogram (EMG) işaretlerinin ölçülmesi kaslarının fonksiyonel aktiviteleri hakkında bilgi vermektedir. Elde edilen bu bilgiler dış iskelet tasarımında hasta hareketi niyetinin belirlenmesinde ve dış iskeletin kas aktiviteleri üzerinde önemli rol oynamaktadır. Alt ekstremite dış iskeletlerinin kullanımı sırasında kas aktivasyon zamanlaması ve genliğindeki değişiklikler, EMG'nin analizi ile ortaya çıkarılabilmektedir. Bu çalışmada, robotik rehabilitasyon sürecinde yürüme hareketi sırasında görev alan kaslar incelenmiştir. İncelenen ilipsoas, Gluteus Maksimus, Gluteus Medius kasları kalçanın fleksiyon, ekstansiyon ve abdüsksiyon hareketlerini sağlarken Medial Gastrokinemus ve Tibialis Anterior kasları ayağın fleksiyon ve dorsifleksiyon hareketlerini gerçekleştirmektedir. Yürüme fazı sırasında diz eklem açıklığı ise Vastus Medialis ve Biseps Femorus kasları ile kontrol edilmektedir. Çalışmada alt ekstremitede fonksiyon yetersizliği olan 5 hastanın RoboGait cihazı üzerinde yürürken 7 farklı kas grubundan alınan kas aktivasyon potansiyelleri eş zamanlı ve kablosuz olarak bilgisayara aktarılmış ve Matlab ortamında görüntülenmiştir. MicroCor Lab cihazı ile ölçülen EMG sinyalleri yürüme sırasında kasların aktivasyonuna göre şekillenmiştir. EMG işaretlerinin analizinde elektrot yerleşim planı kritik öneme sahip olup çalışma sonucunda uygun elektrot yerleşim planı elde edilmiştir. Elektrot yerleşim planına uygun olarak ölçülen işaretler incelendiğinde yürüme fazının gerçekleştirilmesi sırasında kalçanın ektansiyon ve fleksiyon hareketlerini sorumlu Gletous maximum ve İlipsioas kaslarının daha etkin olduğu ölçülmüştür. Gletous maximum kasının yürümede en etkili kas olduğu görülürken İlipsioas kas grubunun bacağın ilk hareketinde yer aldığı EMG işaretlerinin analiz sonucunda belirlenmiştir. Çalışma sonucunda elde edilen bu bulgular hem tedavi sürecinde ki gelişimin takip edilmesinde hemde EMG kontrollü mobilize alt ekstremite dış iskeletlerin geliştirilmesinde yardımcı olacaktır.

References

  • AbdulKareem, A. H., Adila, A. S., & Husi, G. (2018). Recent trends in robotic systems for upper-limb stroke recovery: A low-cost hand and wrist rehabilitation device. Paper presented at the 2018 2nd International Symposium on Small-scale Intelligent Manufacturing Systems (SIMS).
  • Antonucci, G., & Paolucci, S. (2018). Tailored, Technological Therapy: Physician and Therapists Point of View on Robotic Rehabilitation. Paper presented at the Converging Clinical and Engineering Research on Neurorehabilitation III: Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018), October 16-20, 2018, Pisa, Italy.
  • Chen, B., Ma, H., Qin, L.-Y., Gao, F., Chan, K.-M., Law, S.-W., . . . Liao, W.-H. (2016). Recent developments and challenges of lower extremity exoskeletons. Journal of Orthopaedic Translation, 5, 26-37.
  • Chen, B., Zi, B., Wang, Z., Qin, L., & Liao, W.-H. (2019). Knee exoskeletons for gait rehabilitation and human performance augmentation: A state-of-the-art. Mechanism and Machine Theory, 134, 499-511.
  • Fernandes, P. N., Figueredo, J., Moreira, L., Félix, P., Correia, A., Moreno, J. C., & Santos, C. P. (2019). EMG-based Motion Intention Recognition for Controlling a Powered Knee Orthosis. Paper presented at the 2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC).
  • Schmitz, A., Silder, A., Heiderscheit, B., Mahoney, J., & Thelen, D. G. (2009). Differences in lower-extremity muscular activation during walking between healthy older and young adults. Journal of electromyography and kinesiology, 19(6), 1085-1091.
  • Schwartz, I., & Meiner, Z. (2015). Robotic-assisted gait training in neurological patients: who may benefit? Annals of biomedical engineering, 43(5), 1260-1269.
  • Wilcox, M., Rathore, A., Ramirez, D. Z. M., Loureiro, R. C., & Carlson, T. (2016). Muscular activity and physical interaction forces during lower limb exoskeleton use. Healthcare technology letters, 3(4), 273-279.
  • Wu, X., Liu, D.-X., Liu, M., Chen, C., & Guo, H. (2018). Individualized gait pattern generation for sharing lower limb exoskeleton robot. IEEE Transactions on Automation Science and Engineering, 15(4), 1459-1470.
  • Yepes, J. C., Portela, M. A., Saldarriaga, Á. J., Pérez, V. Z., & Betancur, M. J. (2019). Myoelectric control algorithm for robot-assisted therapy: a hardware-in-the-loop simulation study. Biomedical engineering online, 18(1), 3.
There are 10 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Esma Uzunhisarcıklı This is me 0000-0003-2821-4177

Mehmet Bahadır Çetinkaya This is me 0000-0003-3378-4561

Uğur Fidan This is me 0000-0003-0356-017X

İsmail Çalıkuşu This is me 0000-0002-6640-7917

Publication Date October 31, 2019
Published in Issue Year 2019 Special Issue 2019

Cite

APA Uzunhisarcıklı, E., Çetinkaya, M. B., Fidan, U., Çalıkuşu, İ. (2019). Investigation of EMG Signals in Lower Extremity Muscle Groups During Robotic Gait Exercises. Avrupa Bilim Ve Teknoloji Dergisi109-118. https://doi.org/10.31590/ejosat.637577