Towards Predictive Control of Trunk Internal Loads: Modeling Musculotendon Loads and Predicting Muscle Excitations

Youhan Li; M. Sartori; Mahdi Nabipour

doi:10.1007/978-3-031-77588-8_32

Towards Predictive Control of Trunk Internal Loads: Modeling Musculotendon Loads and Predicting Muscle Excitations

Youhan Li
, M. Sartori
, Mahdi Nabipour^*

^*Corresponding author for this work

Neuromuscular Robotics

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

1 Citation (Scopus)

21 Downloads (Pure)

Abstract

Low back pain is prevalent among industrial workers due to heavy lifting and poor posture, causing significant back injuries globally and affecting health and productivity. Existing back-support exoskeletons (BSEs) lack closed-loop control for musculotendon unit (MTU) or joint loads. This study proposes a framework for closed-loop control of L5/S1 joint loads, featuring a simplified BSE dynamics model, a muscle excitation predictor (MEP), and a nonlinear model predictive control (NMPC) algorithm. The simplified model matches the neuromusculoskeletal model with a correlation %0.98, and the MEP has a prediction accuracy of 0.86 ± 0.06. Future work will develop the MPC algorithm to finalize the control framework.

Original language	English
Title of host publication	Converging Clinical and Engineering Research on Neurorehabilitation V
Subtitle of host publication	Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain - Volume 1
Editors	Jose L. Pons, Jesus Tornero, Metin Akay
Pages	164-168
Number of pages	5
ISBN (Electronic)	978-3-031-77588-8
DOIs	https://doi.org/10.1007/978-3-031-77588-8_32
Publication status	Published - 27 Feb 2025
Event	6th International Conference on NeuroRehabilitation, ICNR 2024 - Centro de Congresos y Convenciones Guardia de Corps, La Granja de San Ildefonso, Spain Duration: 5 Nov 2024 → 8 Nov 2024 Conference number: 6 https://2024.icneurorehab.org

Publication series

Name	Biosystems & Biorobotics
Volume	31

Conference

Conference	6th International Conference on NeuroRehabilitation, ICNR 2024
Abbreviated title	ICNR 2024
Country/Territory	Spain
City	La Granja de San Ildefonso
Period	5/11/24 → 8/11/24
Internet address	https://2024.icneurorehab.org

Keywords

2025 OA procedure

Access to Document

10.1007/978-3-031-77588-8_32

978-3-031-77588-8_32Final published version, 822 KBLicence: Taverne

Cite this

Li, Y., Sartori, M., & Nabipour, M. (2025). Towards Predictive Control of Trunk Internal Loads: Modeling Musculotendon Loads and Predicting Muscle Excitations. In J. L. Pons, J. Tornero, & M. Akay (Eds.), Converging Clinical and Engineering Research on Neurorehabilitation V: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain - Volume 1 (pp. 164-168). ( Biosystems & Biorobotics; Vol. 31). https://doi.org/10.1007/978-3-031-77588-8_32

Li, Youhan ; Sartori, M. ; Nabipour, Mahdi. / Towards Predictive Control of Trunk Internal Loads: Modeling Musculotendon Loads and Predicting Muscle Excitations. Converging Clinical and Engineering Research on Neurorehabilitation V: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain - Volume 1. editor / Jose L. Pons ; Jesus Tornero ; Metin Akay. 2025. pp. 164-168 ( Biosystems & Biorobotics).

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title = "Towards Predictive Control of Trunk Internal Loads: Modeling Musculotendon Loads and Predicting Muscle Excitations",

abstract = "Low back pain is prevalent among industrial workers due to heavy lifting and poor posture, causing significant back injuries globally and affecting health and productivity. Existing back-support exoskeletons (BSEs) lack closed-loop control for musculotendon unit (MTU) or joint loads. This study proposes a framework for closed-loop control of L5/S1 joint loads, featuring a simplified BSE dynamics model, a muscle excitation predictor (MEP), and a nonlinear model predictive control (NMPC) algorithm. The simplified model matches the neuromusculoskeletal model with a correlation \%0.98, and the MEP has a prediction accuracy of 0.86 ± 0.06. Future work will develop the MPC algorithm to finalize the control framework.",

keywords = "2025 OA procedure",

author = "Youhan Li and M. Sartori and Mahdi Nabipour",

year = "2025",

month = feb,

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doi = "10.1007/978-3-031-77588-8\_32",

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editor = "Pons, \{Jose L.\} and Jesus Tornero and Metin Akay",

booktitle = "Converging Clinical and Engineering Research on Neurorehabilitation V",

note = "6th International Conference on NeuroRehabilitation, ICNR 2024, ICNR 2024 ; Conference date: 05-11-2024 Through 08-11-2024",

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Li, Y, Sartori, M & Nabipour, M 2025, Towards Predictive Control of Trunk Internal Loads: Modeling Musculotendon Loads and Predicting Muscle Excitations. in JL Pons, J Tornero & M Akay (eds), Converging Clinical and Engineering Research on Neurorehabilitation V: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain - Volume 1. Biosystems & Biorobotics, vol. 31, pp. 164-168, 6th International Conference on NeuroRehabilitation, ICNR 2024, La Granja de San Ildefonso, Spain, 5/11/24. https://doi.org/10.1007/978-3-031-77588-8_32

Towards Predictive Control of Trunk Internal Loads: Modeling Musculotendon Loads and Predicting Muscle Excitations. / Li, Youhan; Sartori, M.; Nabipour, Mahdi.
Converging Clinical and Engineering Research on Neurorehabilitation V: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain - Volume 1. ed. / Jose L. Pons; Jesus Tornero; Metin Akay. 2025. p. 164-168 ( Biosystems & Biorobotics; Vol. 31).

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

TY - GEN

T1 - Towards Predictive Control of Trunk Internal Loads: Modeling Musculotendon Loads and Predicting Muscle Excitations

AU - Li, Youhan

AU - Sartori, M.

AU - Nabipour, Mahdi

N1 - Conference code: 6

PY - 2025/2/27

Y1 - 2025/2/27

N2 - Low back pain is prevalent among industrial workers due to heavy lifting and poor posture, causing significant back injuries globally and affecting health and productivity. Existing back-support exoskeletons (BSEs) lack closed-loop control for musculotendon unit (MTU) or joint loads. This study proposes a framework for closed-loop control of L5/S1 joint loads, featuring a simplified BSE dynamics model, a muscle excitation predictor (MEP), and a nonlinear model predictive control (NMPC) algorithm. The simplified model matches the neuromusculoskeletal model with a correlation %0.98, and the MEP has a prediction accuracy of 0.86 ± 0.06. Future work will develop the MPC algorithm to finalize the control framework.

AB - Low back pain is prevalent among industrial workers due to heavy lifting and poor posture, causing significant back injuries globally and affecting health and productivity. Existing back-support exoskeletons (BSEs) lack closed-loop control for musculotendon unit (MTU) or joint loads. This study proposes a framework for closed-loop control of L5/S1 joint loads, featuring a simplified BSE dynamics model, a muscle excitation predictor (MEP), and a nonlinear model predictive control (NMPC) algorithm. The simplified model matches the neuromusculoskeletal model with a correlation %0.98, and the MEP has a prediction accuracy of 0.86 ± 0.06. Future work will develop the MPC algorithm to finalize the control framework.

KW - 2025 OA procedure

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DO - 10.1007/978-3-031-77588-8_32

M3 - Conference contribution

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BT - Converging Clinical and Engineering Research on Neurorehabilitation V

A2 - Pons, Jose L.

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Li Y, Sartori M, Nabipour M. Towards Predictive Control of Trunk Internal Loads: Modeling Musculotendon Loads and Predicting Muscle Excitations. In Pons JL, Tornero J, Akay M, editors, Converging Clinical and Engineering Research on Neurorehabilitation V: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain - Volume 1. 2025. p. 164-168. ( Biosystems & Biorobotics). doi: 10.1007/978-3-031-77588-8_32

Towards Predictive Control of Trunk Internal Loads: Modeling Musculotendon Loads and Predicting Muscle Excitations

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