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A new method for determining lumbar spine motion using Bayesian belief network

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Abstract

A Bayesian network dynamic model was developed to determine the kinematics of the intervertebral joints of the lumbar spine. Radiographic images in flexion and extension postures were used as input data for modeling, together with movement information from the skin surface using an electromagnetic motion tracking system. Intervertebral joint movements were then estimated by the graphic network. The validity of the model was tested by comparing the predicted position of the vertebrae in the neutral position with those obtained from the radiographic image in the neutral posture. The correlation between the measured and predicted movements was 0.99 (p < 0.01) with a mean error of less than 1.5°. The movement sequence of the various vertebrae was examined based on the model output, and wide variations in the kinematic patterns were observed. The technique is non-invasive and has potential to be used clinically to measure the kinematics of lumbar intervertebral movement.

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Acknowledgments

This work was supported by the Hong Kong Research Grant Council (Competitive Earmarked Research Grant CERG CUHK5251/04E).

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Authors and Affiliations

  1. Department of Diagnostic Radiology and Organ Imaging, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong

    Heather Ting Ma & James F. Griffith

  2. Centre for Magnetic Resonance, University of Queensland, Brisbane, QLD, Australia

    Zhengyi Yang

  3. Department of Orthopaedics and Traumatology, Prince of Wales Hospital, Chinese University of Hong Kong, Shatin, Hong Kong

    Ping Chung Leung

  4. Clinical Research Centre for Health Professions, University of Brighton, Aldro Building, 49 Darley Road, Eastbourne, East Sussex, BN20 7UR, UK

    Raymond Y. W. Lee

Authors
  1. Heather Ting Ma
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  2. Zhengyi Yang
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  3. James F. Griffith
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  4. Ping Chung Leung
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  5. Raymond Y. W. Lee
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Corresponding author

Correspondence to Raymond Y. W. Lee.

Additional information

This work was supported by the Hong Kong Research Grant Council (Competitive Earmarked Research Grant CERG CUHK5251/04E).

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Ma, H.T., Yang, Z., Griffith, J.F. et al. A new method for determining lumbar spine motion using Bayesian belief network. Med Biol Eng Comput 46, 333–340 (2008). https://doi.org/10.1007/s11517-008-0318-y

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  • DOI: https://doi.org/10.1007/s11517-008-0318-y

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