Araştırma Makalesi
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Investigation of Maximum Voluntary Contraction Activity during Robotic Gait

Yıl 2023, , 803 - 812, 05.07.2023
https://doi.org/10.2339/politeknik.1051988

Öz

The purpose of this study is to investigate healthy people’s and patients’ lower extremity muscle activities during robotic gait using kinesiology analysis. Initially, muscle signals were taken from 6 paraplegic patients such as spinal cord injury (SCI) and stroke patients, 2 hemiplegic patients and 4 healthy persons. Then, signals were analyzed by using signal processing techniques such as filtering, rectifying, Root Mean Square (RMS) and also by calculating the Max Voluntary Contraction (MVC). As a result, it was seen that hip muscles such as the Gluteus Maximus (GMA), Gluteus Medius (GM) and Iliopsoas (ILP) had lower MVC values in the hemiplegic patients than those of the SCI patients and the healthy persons. Additionally, when the signals that were obtained were analyzed, it was found that the activity of the Medial Gastrocnemius (MG) muscle could be used in determination of movement path and movement intention. Moreover, the EMG results of gait motion may be helpful in applying accurate amplitude and frequency stimulation in epidural stimulation (ES) therapy.

Kaynakça

  • [1] K. R. Embry, D. J. Villarreal, and R. D. Gregg, "A unified parameterization of human gait across ambulation modes," in 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2179-2183, (2016).
  • [2] R. S. Kakar, Y. Li, C. N. Brown, T. S. Oswald, and K. J. Simpson, "Spine and lower extremity kinematics exhibited during running by adolescent idiopathic scoliosis patients with spinal fusion," Spine deformity, 7,254-261, (2019).
  • [3] G. Barbareschi, R. Richards, M. Thornton, T. Carlson, and C. Holloway, "Statically vs dynamically balanced gait: Analysis of a robotic exoskeleton compared with a human," in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 6728-6731, (2015).
  • [4] R. Riener, "Technology of the robotic gait orthosis Lokomat," in Neurorehabilitation technology, ed: Springer, 395-407, (2016).
  • [5] J. L. Contreras-Vidal, M. Bortole, F. Zhu, K. Nathan, A. Venkatakrishnan, G. E. Francisco, et al., "Neural decoding of robot-assisted gait during rehabilitation after stroke," American journal of physical medicine & rehabilitation,97, 541-550, (2018).
  • [6] G. Kinali, "Differencies in robotic rehabilitation according to clinic requirements," in 2017 Medical Technologies National Congress (TIPTEKNO), 1-3,(2017).
  • [7] L. Ada, C. M. Dean, J. Vargas, and S. Ennis, "Mechanically assisted walking with body weight support results in more independent walking than assisted overground walking in non-ambulatory patients early after stroke: a systematic review," Journal of physiotherapy, 56, 153-161, (2010.
  • [8] İ. s. ÇALIKUŞU, E. UZUNHİSARCIKLI, M. B. ÇETİNKAYA, and U. FİDAN, "Robotic Design and Modelling of Medical Lower Extremity Exoskeletons," İleri Mühendislik Çalışmaları ve Teknolojileri Dergisi, 1,2,198- 214, (2020).
  • [9] A. Cisnal, R. Alonso, J. Turiel, J. Fraile, V. Lobo, and V. Moreno, "EMG based bio-cooperative direct force control of an exoskeleton for hand rehabilitation: a preliminary study," in International Conference on NeuroRehabilitation, 390-394, (2018).
  • [10] E. UZUNHİSARCIKLI, M. B. ÇETİNKAYA, U. FİDAN, and İ. ÇALIKUŞU, "Investigation of EMG signals in lower extremity muscle groups during robotic gait exercises," Avrupa Bilim ve Teknoloji Dergisi, 109-118, (2019).
  • [11] D. Lee, Y. Kim, J. Yun, M. Jung, and G. Lee, "A comparative study of the electromyographic activities of lower extremity muscles during level walking and Pedalo riding," Journal of physical therapy science, 28, 1478-1481, (2016).
  • [12] G. I. Papagiannis, A. I. Triantafyllou, I. M. Roumpelakis, F. Zampeli, P. Garyfallia Eleni, P. Koulouvaris, et al., "Methodology of surface electromyography in gait analysis: review of the literature," Journal of medical engineering & technology, 43, 59-65, (2019).
  • [13] S. Mesbah, F. Gonnelli, A. El-baz, C. Angeli, S. Harkema, and E. Rejc, "Spectral analysis of lower limb EMG activity in individuals with motor complete SCI during standing with epidural stimulation," in 2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 1-5, (2018).
  • [14] C. Yue, X. Lin, X. Zhang, J. Qiu, and H. Cheng, "Design and Performance Evaluation of a Wearable Sensing System for Lower-Limb Exoskeleton," Applied bionics and biomechanics, 1,( 2018).
  • [15] H. Hobara, K. Kimura, K. Omuro, K. Gomi, T. Muraoka, S. Iso, et al., "Determinants of difference in leg stiffness between endurance-and power-trained athletes," Journal of biomechanics, 41, 506-514, (2008).
  • [16] V. BAKIRCIOĞLU and M. Kalyoncu, "Bacaklı robotların yürüme stratejileri üzerine bir literatür taraması," Politeknik Dergisi, 23, 961-986,(2020).
  • [17] F. CELLEK and B. KALAYCIOĞLU, "Inverse Dynamics of Bipedal Gait: The Assumption of the Center of Pressure as an Instantaneous Center of Rotation," Politeknik Dergisi, 1-1.
  • [18] R. Cheng, Y. Sui, D. Sayenko, and J. W. Burdick, "On Muscle Activation for Improving Robotic Rehabilitation after Spinal Cord Injury," in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 798-805, (2018).
  • [19] Z. Svoboda, L. Bizovska, M. Janura, E. Kubonova, K. Janurova, and N. Vuillerme, "Variability of spatial temporal gait parameters and center of pressure displacements during gait in elderly fallers and nonfallers: A 6-month prospective study," PloS one, 12, (2017).
  • [20] R. Sabırlı, "Acil serviste infron micro cor elektrokardiyografi cihazının klinik geçerlilik ve güvenilirliği,", Tıp uzmanlık (Dr) Tezi, Pamukkale Tıp Fakultesi, Acil Anabilimdalı, (2017).
  • [21] İ. Çalıkuşu, E. Uzunhisarcıklı, U. Fidan, and M. B. Çetinkaya, "Analysing the effect of robotic gait on lower extremity muscles and classification by using deep learning," Computer Methods in Biomechanics and Biomedical Engineering, 1-20, (2021).
  • [22] D. Erbil, G. Tugba, T. H. Murat, A. Melike, A. Merve, K. Cagla, et al., "Effects of robot‐assisted gait training in chronic stroke patients treated by botulinum toxin‐a: A pivotal study," Physiotherapy Research International, 23,718, (2018).
  • [23] H. P. French, X. Huang, A. Cummiskey, D. Meldrum, and A. Malone, "Normalisation method can affect gluteus medius electromyography results during weight bearing exercises in people with hip osteoarthritis (OA): a case control study," Gait & posture, 41, 470-475, (2015).
  • [24] S. Al-Qaisi and F. Aghazadeh, "Electromyography analysis: Comparison of maximum voluntary contraction methods for anterior deltoid and trapezius muscles," Procedia Manufacturing, vol. 3, pp. 4578-4583, 2015.
  • [25] K. Huseth, P. Aagaard, A. Gutke, J. Karlsson, and R. Tranberg, "Assessment of neuromuscular activity during maximal isometric contraction in supine vs standing body positions," Journal of Electromyography and Kinesiology, 50, 102365, (2020).
  • [26] T. Ulrich, "Envelope calculation from the Hilbert transform," Los Alamos Nat. Lab., Los Alamos, NM, USA, Tech. Rep,(2006).
  • [27] C. Anders, "Activation patterns of human abdominal muscles during walking: electrode positions make a difference," Medical Research Archives, 5, (2017).
  • [28] S. W. Lee, T. Yi, J.-W. Jung, and Z. Bien, "Design of a gait phase recognition system that can cope with EMG electrode location variation," IEEE Transactions on Automation Science and Engineering,14, 1429-1439, (2015).
  • [29] L. S. George, S. J. Hobbs, J. Richards, J. Sinclair, D. Holt, and S. Roy, "The effect of cut-off frequency when high-pass filtering equine sEMG signals during locomotion," Journal of Electromyography and Kinesiology, 43, 28-40, (2018).
  • [30] L. St. George, S. Roy, J. Richards, J. Sinclair, and S. J. Hobbs, "Surface EMG signal normalisation and filtering improves sensitivity of equine gait analysis," Comparative Exercise Physiology, 1-14, (2019).
  • [31] A. Strazza, A. Mengarelli, S. Fioretti, L. Burattini, V. Agostini, M. Knaflitz, et al., "Surface-EMG analysis for the quantification of thigh muscle dynamic co-contractions during normal gait," Gait & posture, 51, 228-233, (2017).
  • [32] D. De Venuto, V. F. Annese, G. Defazio, V. Gallo, and G. Mezzina, "Gait analysis and quantitative drug effect evaluation in Parkinson disease by jointly EEG-EMG monitoring," in 2017 12th International Conference on Design & Technology of Integrated Systems In Nanoscale Era (DTIS), 1-6, (2017).
  • [33] F. Di Nardo, A. Mengarelli, L. Burattini, E. Maranesi, V. Agostini, A. Nascimbeni, et al., "Normative EMG patterns of ankle muscle co-contractions in school-age children during gait," Gait & posture, 46, 161-166, (2016).
  • [34] SERBEST, K., & ELDOĞAN, O. (2020). Design, development and evaluation of a new hand exoskeleton for stroke rehabilitation at home. Politeknik Dergisi, 24(1), 305-314, (2020).

Robotik Yürüyüş Sırasında Maksimum İstemli Kasılma Aktivitesinin İncelenmesi

Yıl 2023, , 803 - 812, 05.07.2023
https://doi.org/10.2339/politeknik.1051988

Öz

Bu çalışmanın amacı, sağlıklı kişilerin ve hastaların robotik yürüyüş sırasında alt ekstremite kas aktivitelerini kinesiyoloji analizi kullanarak incelemektir. Başlangıçta spinal cord injury (SCI) ve inme hastaları gibi 6 paraplejik hastadan, 2 hemiplejik hastadan ve 4 sağlıklı kişiden kas sinyalleri alındı. Ardından, filtreleme, doğrultma, Ortalama Karekök (RMS) gibi sinyal işleme teknikleri kullanılarak ve ayrıca Maksimum Gönüllü Kasılma (MVC) hesaplanarak sinyaller analiz edilmiştir. Sonuç olarak hemiplejik hastalarda Gluteus Maximus (GMA), Gluteus Medius (GM) ve Iliopsoas (ILP) gibi kalça kaslarının MVC değerlerinin SCI hastalarına ve sağlıklı kişilere göre daha düşük olduğu görüldü. Ayrıca elde edilen sinyaller analiz edildiğinde Medial Gastrocnemius (MG) kasının aktivitesinin hareket yolunun ve hareket niyetinin belirlenmesinde kullanılabileceği bulundu. Ayrıca, yürüyüş hareketinin EMG sonuçları, epidural stimülasyon (ES) tedavisinde doğru genlik ve frekans stimülasyonunun uygulanmasında yardımcı olabilir.

Kaynakça

  • [1] K. R. Embry, D. J. Villarreal, and R. D. Gregg, "A unified parameterization of human gait across ambulation modes," in 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2179-2183, (2016).
  • [2] R. S. Kakar, Y. Li, C. N. Brown, T. S. Oswald, and K. J. Simpson, "Spine and lower extremity kinematics exhibited during running by adolescent idiopathic scoliosis patients with spinal fusion," Spine deformity, 7,254-261, (2019).
  • [3] G. Barbareschi, R. Richards, M. Thornton, T. Carlson, and C. Holloway, "Statically vs dynamically balanced gait: Analysis of a robotic exoskeleton compared with a human," in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 6728-6731, (2015).
  • [4] R. Riener, "Technology of the robotic gait orthosis Lokomat," in Neurorehabilitation technology, ed: Springer, 395-407, (2016).
  • [5] J. L. Contreras-Vidal, M. Bortole, F. Zhu, K. Nathan, A. Venkatakrishnan, G. E. Francisco, et al., "Neural decoding of robot-assisted gait during rehabilitation after stroke," American journal of physical medicine & rehabilitation,97, 541-550, (2018).
  • [6] G. Kinali, "Differencies in robotic rehabilitation according to clinic requirements," in 2017 Medical Technologies National Congress (TIPTEKNO), 1-3,(2017).
  • [7] L. Ada, C. M. Dean, J. Vargas, and S. Ennis, "Mechanically assisted walking with body weight support results in more independent walking than assisted overground walking in non-ambulatory patients early after stroke: a systematic review," Journal of physiotherapy, 56, 153-161, (2010.
  • [8] İ. s. ÇALIKUŞU, E. UZUNHİSARCIKLI, M. B. ÇETİNKAYA, and U. FİDAN, "Robotic Design and Modelling of Medical Lower Extremity Exoskeletons," İleri Mühendislik Çalışmaları ve Teknolojileri Dergisi, 1,2,198- 214, (2020).
  • [9] A. Cisnal, R. Alonso, J. Turiel, J. Fraile, V. Lobo, and V. Moreno, "EMG based bio-cooperative direct force control of an exoskeleton for hand rehabilitation: a preliminary study," in International Conference on NeuroRehabilitation, 390-394, (2018).
  • [10] E. UZUNHİSARCIKLI, M. B. ÇETİNKAYA, U. FİDAN, and İ. ÇALIKUŞU, "Investigation of EMG signals in lower extremity muscle groups during robotic gait exercises," Avrupa Bilim ve Teknoloji Dergisi, 109-118, (2019).
  • [11] D. Lee, Y. Kim, J. Yun, M. Jung, and G. Lee, "A comparative study of the electromyographic activities of lower extremity muscles during level walking and Pedalo riding," Journal of physical therapy science, 28, 1478-1481, (2016).
  • [12] G. I. Papagiannis, A. I. Triantafyllou, I. M. Roumpelakis, F. Zampeli, P. Garyfallia Eleni, P. Koulouvaris, et al., "Methodology of surface electromyography in gait analysis: review of the literature," Journal of medical engineering & technology, 43, 59-65, (2019).
  • [13] S. Mesbah, F. Gonnelli, A. El-baz, C. Angeli, S. Harkema, and E. Rejc, "Spectral analysis of lower limb EMG activity in individuals with motor complete SCI during standing with epidural stimulation," in 2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 1-5, (2018).
  • [14] C. Yue, X. Lin, X. Zhang, J. Qiu, and H. Cheng, "Design and Performance Evaluation of a Wearable Sensing System for Lower-Limb Exoskeleton," Applied bionics and biomechanics, 1,( 2018).
  • [15] H. Hobara, K. Kimura, K. Omuro, K. Gomi, T. Muraoka, S. Iso, et al., "Determinants of difference in leg stiffness between endurance-and power-trained athletes," Journal of biomechanics, 41, 506-514, (2008).
  • [16] V. BAKIRCIOĞLU and M. Kalyoncu, "Bacaklı robotların yürüme stratejileri üzerine bir literatür taraması," Politeknik Dergisi, 23, 961-986,(2020).
  • [17] F. CELLEK and B. KALAYCIOĞLU, "Inverse Dynamics of Bipedal Gait: The Assumption of the Center of Pressure as an Instantaneous Center of Rotation," Politeknik Dergisi, 1-1.
  • [18] R. Cheng, Y. Sui, D. Sayenko, and J. W. Burdick, "On Muscle Activation for Improving Robotic Rehabilitation after Spinal Cord Injury," in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 798-805, (2018).
  • [19] Z. Svoboda, L. Bizovska, M. Janura, E. Kubonova, K. Janurova, and N. Vuillerme, "Variability of spatial temporal gait parameters and center of pressure displacements during gait in elderly fallers and nonfallers: A 6-month prospective study," PloS one, 12, (2017).
  • [20] R. Sabırlı, "Acil serviste infron micro cor elektrokardiyografi cihazının klinik geçerlilik ve güvenilirliği,", Tıp uzmanlık (Dr) Tezi, Pamukkale Tıp Fakultesi, Acil Anabilimdalı, (2017).
  • [21] İ. Çalıkuşu, E. Uzunhisarcıklı, U. Fidan, and M. B. Çetinkaya, "Analysing the effect of robotic gait on lower extremity muscles and classification by using deep learning," Computer Methods in Biomechanics and Biomedical Engineering, 1-20, (2021).
  • [22] D. Erbil, G. Tugba, T. H. Murat, A. Melike, A. Merve, K. Cagla, et al., "Effects of robot‐assisted gait training in chronic stroke patients treated by botulinum toxin‐a: A pivotal study," Physiotherapy Research International, 23,718, (2018).
  • [23] H. P. French, X. Huang, A. Cummiskey, D. Meldrum, and A. Malone, "Normalisation method can affect gluteus medius electromyography results during weight bearing exercises in people with hip osteoarthritis (OA): a case control study," Gait & posture, 41, 470-475, (2015).
  • [24] S. Al-Qaisi and F. Aghazadeh, "Electromyography analysis: Comparison of maximum voluntary contraction methods for anterior deltoid and trapezius muscles," Procedia Manufacturing, vol. 3, pp. 4578-4583, 2015.
  • [25] K. Huseth, P. Aagaard, A. Gutke, J. Karlsson, and R. Tranberg, "Assessment of neuromuscular activity during maximal isometric contraction in supine vs standing body positions," Journal of Electromyography and Kinesiology, 50, 102365, (2020).
  • [26] T. Ulrich, "Envelope calculation from the Hilbert transform," Los Alamos Nat. Lab., Los Alamos, NM, USA, Tech. Rep,(2006).
  • [27] C. Anders, "Activation patterns of human abdominal muscles during walking: electrode positions make a difference," Medical Research Archives, 5, (2017).
  • [28] S. W. Lee, T. Yi, J.-W. Jung, and Z. Bien, "Design of a gait phase recognition system that can cope with EMG electrode location variation," IEEE Transactions on Automation Science and Engineering,14, 1429-1439, (2015).
  • [29] L. S. George, S. J. Hobbs, J. Richards, J. Sinclair, D. Holt, and S. Roy, "The effect of cut-off frequency when high-pass filtering equine sEMG signals during locomotion," Journal of Electromyography and Kinesiology, 43, 28-40, (2018).
  • [30] L. St. George, S. Roy, J. Richards, J. Sinclair, and S. J. Hobbs, "Surface EMG signal normalisation and filtering improves sensitivity of equine gait analysis," Comparative Exercise Physiology, 1-14, (2019).
  • [31] A. Strazza, A. Mengarelli, S. Fioretti, L. Burattini, V. Agostini, M. Knaflitz, et al., "Surface-EMG analysis for the quantification of thigh muscle dynamic co-contractions during normal gait," Gait & posture, 51, 228-233, (2017).
  • [32] D. De Venuto, V. F. Annese, G. Defazio, V. Gallo, and G. Mezzina, "Gait analysis and quantitative drug effect evaluation in Parkinson disease by jointly EEG-EMG monitoring," in 2017 12th International Conference on Design & Technology of Integrated Systems In Nanoscale Era (DTIS), 1-6, (2017).
  • [33] F. Di Nardo, A. Mengarelli, L. Burattini, E. Maranesi, V. Agostini, A. Nascimbeni, et al., "Normative EMG patterns of ankle muscle co-contractions in school-age children during gait," Gait & posture, 46, 161-166, (2016).
  • [34] SERBEST, K., & ELDOĞAN, O. (2020). Design, development and evaluation of a new hand exoskeleton for stroke rehabilitation at home. Politeknik Dergisi, 24(1), 305-314, (2020).
Toplam 34 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Ugur Fidan 0000-0003-0356-017X

İsmail Çalıkuşu 0000-0002-6640-7917

Yayımlanma Tarihi 5 Temmuz 2023
Gönderilme Tarihi 31 Aralık 2021
Yayımlandığı Sayı Yıl 2023

Kaynak Göster

APA Fidan, U., & Çalıkuşu, İ. (2023). Investigation of Maximum Voluntary Contraction Activity during Robotic Gait. Politeknik Dergisi, 26(2), 803-812. https://doi.org/10.2339/politeknik.1051988
AMA Fidan U, Çalıkuşu İ. Investigation of Maximum Voluntary Contraction Activity during Robotic Gait. Politeknik Dergisi. Temmuz 2023;26(2):803-812. doi:10.2339/politeknik.1051988
Chicago Fidan, Ugur, ve İsmail Çalıkuşu. “Investigation of Maximum Voluntary Contraction Activity During Robotic Gait”. Politeknik Dergisi 26, sy. 2 (Temmuz 2023): 803-12. https://doi.org/10.2339/politeknik.1051988.
EndNote Fidan U, Çalıkuşu İ (01 Temmuz 2023) Investigation of Maximum Voluntary Contraction Activity during Robotic Gait. Politeknik Dergisi 26 2 803–812.
IEEE U. Fidan ve İ. Çalıkuşu, “Investigation of Maximum Voluntary Contraction Activity during Robotic Gait”, Politeknik Dergisi, c. 26, sy. 2, ss. 803–812, 2023, doi: 10.2339/politeknik.1051988.
ISNAD Fidan, Ugur - Çalıkuşu, İsmail. “Investigation of Maximum Voluntary Contraction Activity During Robotic Gait”. Politeknik Dergisi 26/2 (Temmuz 2023), 803-812. https://doi.org/10.2339/politeknik.1051988.
JAMA Fidan U, Çalıkuşu İ. Investigation of Maximum Voluntary Contraction Activity during Robotic Gait. Politeknik Dergisi. 2023;26:803–812.
MLA Fidan, Ugur ve İsmail Çalıkuşu. “Investigation of Maximum Voluntary Contraction Activity During Robotic Gait”. Politeknik Dergisi, c. 26, sy. 2, 2023, ss. 803-12, doi:10.2339/politeknik.1051988.
Vancouver Fidan U, Çalıkuşu İ. Investigation of Maximum Voluntary Contraction Activity during Robotic Gait. Politeknik Dergisi. 2023;26(2):803-12.
 
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