Computationally Efficient Human Body Modelling for Real Time Motion Comfort Assessment

Raj Desai; Marko Cvetković; Georgios Papaioannou; Riender Happee

doi:10.1007/978-3-031-37848-5_32

Computationally Efficient Human Body Modelling for Real Time Motion Comfort Assessment

Raj Desai^*, Marko Cvetković, Georgios Papaioannou, Riender Happee

^*Corresponding author for this work

Intelligent Vehicles

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

35 Downloads (Pure)

Abstract

Due to the complexity of the human body and its neuromuscular stabilization, it has been challenging to efficiently and accurately predict human motion and capture posture while being driven. Existing simple models of the seated human body are mostly two-dimensional and developed in the mid-sagittal plane exposed to in-plane excitation. Such models capture fore-aft and vertical motion but not the more complex 3D motions due to lateral loading. Advanced 3D full body active human models (AHMs), such as in MADYMO, can be used for comfort analysis and to investigate how vibrations influence the human body while being driven. However, such AHMs are very time-consuming due to their complexity. To effectively analyze motion comfort, a computationally efficient and accurate three dimensional (3D) human model, which runs faster than real time, is presented. The model's postural stabilization parameters are tuned using available 3D vibration data for head, trunk and pelvis translation and rotation. A comparison between AHM and EHM is conducted regarding human body kinematics. According to the results, the EHM model configuration with two neck joints, two torso bending joints, and a spinal compression joint accurately predicts body kinematics.

Original language	English
Title of host publication	Advances in Digital Human Modeling
Subtitle of host publication	Proceedings of the 8th International Digital Human Modeling Symposium
Editors	Sofia Scataglini, Wim Saeys, Steven Truijen, Gregor Harih
Publisher	Springer
Pages	285-295
ISBN (Electronic)	978-3-031-37848-5
ISBN (Print)	978-3-031-37847-8
DOIs	https://doi.org/10.1007/978-3-031-37848-5_32
Publication status	Published - 2023
Event	8th International Digital Human Modeling Symposium - Antwerp, Belgium Duration: 4 Sept 2023 → 6 Sept 2023

Publication series

Name	Lecture Notes in Networks and Systems
Volume	744 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	8th International Digital Human Modeling Symposium
Country/Territory	Belgium
City	Antwerp
Period	4/09/23 → 6/09/23

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

MADYMO
motion comfort
multibody model
posture
vibrations

Access to Document

10.1007/978-3-031-37848-5_32

978-3-031-37848-5_32Final published version, 1.13 MB

Cite this

Desai, R., Cvetković, M., Papaioannou, G., & Happee, R. (2023). Computationally Efficient Human Body Modelling for Real Time Motion Comfort Assessment. In S. Scataglini, W. Saeys, S. Truijen, & G. Harih (Eds.), Advances in Digital Human Modeling : Proceedings of the 8th International Digital Human Modeling Symposium (pp. 285-295). (Lecture Notes in Networks and Systems; Vol. 744 LNNS). Springer. https://doi.org/10.1007/978-3-031-37848-5_32

Desai, Raj ; Cvetković, Marko ; Papaioannou, Georgios et al. / Computationally Efficient Human Body Modelling for Real Time Motion Comfort Assessment. Advances in Digital Human Modeling : Proceedings of the 8th International Digital Human Modeling Symposium. editor / Sofia Scataglini ; Wim Saeys ; Steven Truijen ; Gregor Harih. Springer, 2023. pp. 285-295 (Lecture Notes in Networks and Systems).

@inproceedings{9cad1cced8904eaf832561f65001fd1c,

title = "Computationally Efficient Human Body Modelling for Real Time Motion Comfort Assessment",

abstract = "Due to the complexity of the human body and its neuromuscular stabilization, it has been challenging to efficiently and accurately predict human motion and capture posture while being driven. Existing simple models of the seated human body are mostly two-dimensional and developed in the mid-sagittal plane exposed to in-plane excitation. Such models capture fore-aft and vertical motion but not the more complex 3D motions due to lateral loading. Advanced 3D full body active human models (AHMs), such as in MADYMO, can be used for comfort analysis and to investigate how vibrations influence the human body while being driven. However, such AHMs are very time-consuming due to their complexity. To effectively analyze motion comfort, a computationally efficient and accurate three dimensional (3D) human model, which runs faster than real time, is presented. The model's postural stabilization parameters are tuned using available 3D vibration data for head, trunk and pelvis translation and rotation. A comparison between AHM and EHM is conducted regarding human body kinematics. According to the results, the EHM model configuration with two neck joints, two torso bending joints, and a spinal compression joint accurately predicts body kinematics.",

keywords = "MADYMO, motion comfort, multibody model, posture, vibrations",

author = "Raj Desai and Marko Cvetkovi{\'c} and Georgios Papaioannou and Riender Happee",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 8th International Digital Human Modeling Symposium ; Conference date: 04-09-2023 Through 06-09-2023",

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Desai, R , Cvetković, M , Papaioannou, G & Happee, R 2023, Computationally Efficient Human Body Modelling for Real Time Motion Comfort Assessment. in S Scataglini, W Saeys, S Truijen & G Harih (eds), Advances in Digital Human Modeling : Proceedings of the 8th International Digital Human Modeling Symposium. Lecture Notes in Networks and Systems, vol. 744 LNNS, Springer, pp. 285-295, 8th International Digital Human Modeling Symposium, Antwerp, Belgium, 4/09/23. https://doi.org/10.1007/978-3-031-37848-5_32

Computationally Efficient Human Body Modelling for Real Time Motion Comfort Assessment. / Desai, Raj ; Cvetković, Marko ; Papaioannou, Georgios et al.
Advances in Digital Human Modeling : Proceedings of the 8th International Digital Human Modeling Symposium. ed. / Sofia Scataglini; Wim Saeys; Steven Truijen; Gregor Harih. Springer, 2023. p. 285-295 (Lecture Notes in Networks and Systems; Vol. 744 LNNS).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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T1 - Computationally Efficient Human Body Modelling for Real Time Motion Comfort Assessment

AU - Desai, Raj

AU - Cvetković, Marko

AU - Papaioannou, Georgios

AU - Happee, Riender

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2023

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N2 - Due to the complexity of the human body and its neuromuscular stabilization, it has been challenging to efficiently and accurately predict human motion and capture posture while being driven. Existing simple models of the seated human body are mostly two-dimensional and developed in the mid-sagittal plane exposed to in-plane excitation. Such models capture fore-aft and vertical motion but not the more complex 3D motions due to lateral loading. Advanced 3D full body active human models (AHMs), such as in MADYMO, can be used for comfort analysis and to investigate how vibrations influence the human body while being driven. However, such AHMs are very time-consuming due to their complexity. To effectively analyze motion comfort, a computationally efficient and accurate three dimensional (3D) human model, which runs faster than real time, is presented. The model's postural stabilization parameters are tuned using available 3D vibration data for head, trunk and pelvis translation and rotation. A comparison between AHM and EHM is conducted regarding human body kinematics. According to the results, the EHM model configuration with two neck joints, two torso bending joints, and a spinal compression joint accurately predicts body kinematics.

AB - Due to the complexity of the human body and its neuromuscular stabilization, it has been challenging to efficiently and accurately predict human motion and capture posture while being driven. Existing simple models of the seated human body are mostly two-dimensional and developed in the mid-sagittal plane exposed to in-plane excitation. Such models capture fore-aft and vertical motion but not the more complex 3D motions due to lateral loading. Advanced 3D full body active human models (AHMs), such as in MADYMO, can be used for comfort analysis and to investigate how vibrations influence the human body while being driven. However, such AHMs are very time-consuming due to their complexity. To effectively analyze motion comfort, a computationally efficient and accurate three dimensional (3D) human model, which runs faster than real time, is presented. The model's postural stabilization parameters are tuned using available 3D vibration data for head, trunk and pelvis translation and rotation. A comparison between AHM and EHM is conducted regarding human body kinematics. According to the results, the EHM model configuration with two neck joints, two torso bending joints, and a spinal compression joint accurately predicts body kinematics.

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Desai R , Cvetković M , Papaioannou G , Happee R. Computationally Efficient Human Body Modelling for Real Time Motion Comfort Assessment. In Scataglini S, Saeys W, Truijen S, Harih G, editors, Advances in Digital Human Modeling : Proceedings of the 8th International Digital Human Modeling Symposium. Springer. 2023. p. 285-295. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-37848-5_32

Computationally Efficient Human Body Modelling for Real Time Motion Comfort Assessment

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