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The Significance of the Thoracic Spinal Multiple Segments During Different Pick-Object Approaches

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Intelligent Manufacturing and Mechatronics (iM3F 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 850))

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Abstract

To conduct everyday tasks safely and effectively, it is essential to understand spinal kinematics. Even while there have been various attempts to look at the kinematics of the area during daily activities, very little study has specifically focused on the multi-segmental contribution of the thoracic spine. The credibility of actual multi-segment contributions is diminished since the thoracic area has only been investigated as a single segment. This study aims to evaluate the significance of the thoracic spinal segments during various pick-object approaches among healthy individuals. All tasks examined had interclass correlation coefficients (ICC) greater than or equal to 0.97 (0.958–0.996), which indicates a high level of reliability. There were statistically significant variations in the majority of the task completion percentages between tasks with and without a global section (P-value = 0.05). At the middle transition for every segment of the Begin cycle of pick-object, the thoracic spine reaches its maximum mobility. Picking up an object while squat had the least increase in thoracic kinematics as compared to Semi-squat and Stoop indicating the optimal postural implementation for minimizing spinal injury. The results give a clear explanation of the good spinal condition of asymptomatic people and might be helpful for ergonomic spinal rehabilitation.

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Acknowledgements

The authors would like to thank you Shibaura Institute of Technology (SIT), Japan for laboratory facilities and assistance during the completion of this research study and gratitude toward the Universiti Teknologi Malaysia (UTM).

Author information

Authors and Affiliations

  1. Department of Applied Mechanics and Design, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia (UTM), 81310, Skudai, Johor Bahru, Malaysia

    Wan Aliff Abdul Saad, Azuwan Mat Dzahir, Zair Asrar Ahmad, Mat Hussin Ab. Talib, Shaharil Mad Saad, Muhammad Danial Abu Hasan, Muhammad Firdaus Isham, Mohd Syahril Ramadhan Saufi & Muhammad Asyraf Muhammad Rizal

  2. Department of Biomedical Engineering and Health Sciences, Faculty of Electrical Engineering, Universiti Teknologi Malaysia (UTM), 81310, Skudai, Johor Bahru, Malaysia

    Aizreena Azaman

Authors
  1. Wan Aliff Abdul Saad
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  2. Azuwan Mat Dzahir
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  3. Aizreena Azaman
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  4. Zair Asrar Ahmad
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  5. Mat Hussin Ab. Talib
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  6. Shaharil Mad Saad
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  7. Muhammad Danial Abu Hasan
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  8. Muhammad Firdaus Isham
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  9. Mohd Syahril Ramadhan Saufi
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  10. Muhammad Asyraf Muhammad Rizal
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Corresponding author

Correspondence to Wan Aliff Abdul Saad .

Editor information

Editors and Affiliations

  1. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, Malaysia

    Wan Hasbullah Mohd. Isa

  2. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, Malaysia

    Ismail Mohd. Khairuddin

  3. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, Malaysia

    Mohd. Azraai Mohd. Razman

  4. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, Malaysia

    Sarah 'Atifah Saruchi

  5. School of Intelligent Manufacturing Ecosystem, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Sze-Hong Teh

  6. Department of Computer Science, University of York, York, UK

    Pengcheng Liu

Appendices

Appendix 1. P-Values of One-Way ANOVA During Begin Cycle of Pick-Object

Approach

POST

POSS

POSQ

Task (%)

W/O

W

W/O

W

W/O

W

Percentage of motion completion

0

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

10

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

20

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

30

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

40

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

50

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

60

0.976

0.994

 < 0.05

 < 0.05

 < 0.05

 < 0.05

70

 < 0.05

 < 0.05

0.001

0.001

 < 0.05

 < 0.05

80

 < 0.05

 < 0.05

0.025

0.036

 < 0.05

 < 0.05

90

 < 0.05

 < 0.05

0.067

0.093

 < 0.05

 < 0.05

100

 < 0.05

 < 0.05

0.073

0.101

 < 0.05

 < 0.05

  1. • Without, W/O, or With, W global mean

Appendix 2. P-Values of One-Way ANOVA During Return Cycle of Pick-Object

Approach

POST

POSS

POSQ

Task (%)

W/O

W

W/O

W

W/O

W

Percentage of motion completion

0

 < 0.05

 < 0.05

0.071

0.099

 < 0.05

 < 0.05

10

 < 0.05

 < 0.05

0.034

0.047

 < 0.05

 < 0.05

20

 < 0.05

 < 0.05

0.001

0.001

 < 0.05

 < 0.05

30

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

40

0.017

0.019

 < 0.05

 < 0.05

 < 0.05

 < 0.05

50

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

60

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

70

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

80

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

90

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

100

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

 < 0.05

  1. • Without, W/O, or With, W global mean

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Abdul Saad, W.A. et al. (2024). The Significance of the Thoracic Spinal Multiple Segments During Different Pick-Object Approaches. In: Mohd. Isa, W.H., Khairuddin, I.M., Mohd. Razman, M.A., Saruchi, S.'., Teh, SH., Liu, P. (eds) Intelligent Manufacturing and Mechatronics. iM3F 2023. Lecture Notes in Networks and Systems, vol 850. Springer, Singapore. https://doi.org/10.1007/978-981-99-8819-8_13

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  • DOI: https://doi.org/10.1007/978-981-99-8819-8_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8818-1

  • Online ISBN: 978-981-99-8819-8

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