Can HDEMG-Based Low Back Muscle Fatigue Estimates Be Used in Exoskeleton Control During Prolonged Trunk Bending? A Pilot Study

Niels P. Brouwer; Ali Tabasi; Alejandro Moya-Esteban; Massimo Sartori; Wietse van Dijk; Idsart Kingma; Jaap H. van Dieën

doi:10.1007/978-3-030-69547-7_30

Can HDEMG-Based Low Back Muscle Fatigue Estimates Be Used in Exoskeleton Control During Prolonged Trunk Bending? A Pilot Study

Niels P. Brouwer^*, Ali Tabasi, Alejandro Moya-Esteban, Massimo Sartori, Wietse van Dijk, Idsart Kingma, Jaap H. van Dieën

^*Corresponding author for this work

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Abstract

The effectiveness of exoskeletons could be enhanced by incorporating low back muscle fatigue estimates in their control. The aim of the present study was to evaluate whether low back muscle fatigue can be estimated using the spectral content of trunk extensor muscle high-density EMG (HDEMG) by considering the motor unit action potential conduction velocity (MUAP CV) as a reference. The HDEMG-based MUAP CV was estimated for multiple sites on the lower back consistently throughout a 30 degrees lumbar flexion endurance trial. Significant linear relationships were observed between MUAP CV and spectral content. However, MUAP CV and spectral changes over time did not show the expected decrease, probably due to additional recruitment of motor units or alternating activity of synergistic muscles. The anatomical information about the sites that allow MUAP CV estimation can be valuable for future low back muscle fatigue estimations.

Original language	English
Title of host publication	Wearable Robotics: Challenges and Trends
Subtitle of host publication	Proceedings of the 5th International Symposium on Wearable Robotics, WeRob2020, and of WearRAcon Europe 2020, October 13–16, 2020
Editors	Juan C. Moreno, Jawad Masood, Urs Schneider, Christophe Maufroy, Jose L. Pons
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	183-187
Number of pages	5
ISBN (Electronic)	9783030695477
ISBN (Print)	9783030695460, 9783030695491
DOIs	https://doi.org/10.1007/978-3-030-69547-7_30
Publication status	Published - 2022

Publication series

Name	Biosystems and Biorobotics
Volume	27
ISSN (Print)	2195-3562
ISSN (Electronic)	2195-3570

Bibliographical note

Funding Information:
Acknowledgements This work was supported by the Dutch Research Council (NWO), program ‘perspectief’ (project P16-05).

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Funding

Acknowledgements This work was supported by the Dutch Research Council (NWO), program ‘perspectief’ (project P16-05).

Funders	Funder number
Nederlandse Organisatie voor Wetenschappelijk Onderzoek	P16-05
Horizon 2020 Framework Programme	779963

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10.1007/978-3-030-69547-7_30

Brouwer2022_Chapter_CanHDEMG-BasedLowBackMuscleFatigueEstimatesBeUsedInExoskeletonControlFinal published version, 165 KBLicence: Article 25fa Dutch Copyright Act

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Brouwer, N. P., Tabasi, A., Moya-Esteban, A., Sartori, M., van Dijk, W., Kingma, I., & van Dieën, J. H. (2022). Can HDEMG-Based Low Back Muscle Fatigue Estimates Be Used in Exoskeleton Control During Prolonged Trunk Bending? A Pilot Study. In J. C. Moreno, J. Masood, U. Schneider, C. Maufroy, & J. L. Pons (Eds.), Wearable Robotics: Challenges and Trends: Proceedings of the 5th International Symposium on Wearable Robotics, WeRob2020, and of WearRAcon Europe 2020, October 13–16, 2020 (pp. 183-187). (Biosystems and Biorobotics; Vol. 27). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-69547-7_30

Brouwer, Niels P. ; Tabasi, Ali ; Moya-Esteban, Alejandro et al. / Can HDEMG-Based Low Back Muscle Fatigue Estimates Be Used in Exoskeleton Control During Prolonged Trunk Bending? A Pilot Study. Wearable Robotics: Challenges and Trends: Proceedings of the 5th International Symposium on Wearable Robotics, WeRob2020, and of WearRAcon Europe 2020, October 13–16, 2020. editor / Juan C. Moreno ; Jawad Masood ; Urs Schneider ; Christophe Maufroy ; Jose L. Pons. Springer Science and Business Media Deutschland GmbH, 2022. pp. 183-187 (Biosystems and Biorobotics).

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abstract = "The effectiveness of exoskeletons could be enhanced by incorporating low back muscle fatigue estimates in their control. The aim of the present study was to evaluate whether low back muscle fatigue can be estimated using the spectral content of trunk extensor muscle high-density EMG (HDEMG) by considering the motor unit action potential conduction velocity (MUAP CV) as a reference. The HDEMG-based MUAP CV was estimated for multiple sites on the lower back consistently throughout a 30 degrees lumbar flexion endurance trial. Significant linear relationships were observed between MUAP CV and spectral content. However, MUAP CV and spectral changes over time did not show the expected decrease, probably due to additional recruitment of motor units or alternating activity of synergistic muscles. The anatomical information about the sites that allow MUAP CV estimation can be valuable for future low back muscle fatigue estimations.",

author = "Brouwer, {Niels P.} and Ali Tabasi and Alejandro Moya-Esteban and Massimo Sartori and {van Dijk}, Wietse and Idsart Kingma and {van Die{\"e}n}, {Jaap H.}",

note = "Funding Information: Acknowledgements This work was supported by the Dutch Research Council (NWO), program {\textquoteleft}perspectief{\textquoteright} (project P16-05). Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.",

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Brouwer, NP, Tabasi, A, Moya-Esteban, A, Sartori, M, van Dijk, W, Kingma, I & van Dieën, JH 2022, Can HDEMG-Based Low Back Muscle Fatigue Estimates Be Used in Exoskeleton Control During Prolonged Trunk Bending? A Pilot Study. in JC Moreno, J Masood, U Schneider, C Maufroy & JL Pons (eds), Wearable Robotics: Challenges and Trends: Proceedings of the 5th International Symposium on Wearable Robotics, WeRob2020, and of WearRAcon Europe 2020, October 13–16, 2020. Biosystems and Biorobotics, vol. 27, Springer Science and Business Media Deutschland GmbH, pp. 183-187. https://doi.org/10.1007/978-3-030-69547-7_30

Can HDEMG-Based Low Back Muscle Fatigue Estimates Be Used in Exoskeleton Control During Prolonged Trunk Bending? A Pilot Study. / Brouwer, Niels P.; Tabasi, Ali; Moya-Esteban, Alejandro et al.
Wearable Robotics: Challenges and Trends: Proceedings of the 5th International Symposium on Wearable Robotics, WeRob2020, and of WearRAcon Europe 2020, October 13–16, 2020. ed. / Juan C. Moreno; Jawad Masood; Urs Schneider; Christophe Maufroy; Jose L. Pons. Springer Science and Business Media Deutschland GmbH, 2022. p. 183-187 (Biosystems and Biorobotics; Vol. 27).

Research output: Chapter in Book / Report / Conference proceeding › Chapter › Academic › peer-review

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Brouwer NP, Tabasi A, Moya-Esteban A, Sartori M, van Dijk W, Kingma I et al. Can HDEMG-Based Low Back Muscle Fatigue Estimates Be Used in Exoskeleton Control During Prolonged Trunk Bending? A Pilot Study. In Moreno JC, Masood J, Schneider U, Maufroy C, Pons JL, editors, Wearable Robotics: Challenges and Trends: Proceedings of the 5th International Symposium on Wearable Robotics, WeRob2020, and of WearRAcon Europe 2020, October 13–16, 2020. Springer Science and Business Media Deutschland GmbH. 2022. p. 183-187. (Biosystems and Biorobotics). Epub 2021 Jul 2. doi: 10.1007/978-3-030-69547-7_30

Can HDEMG-Based Low Back Muscle Fatigue Estimates Be Used in Exoskeleton Control During Prolonged Trunk Bending? A Pilot Study

Abstract

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