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    |December 3, 2025
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    Summary

    This study developed an algorithm using inertial measurement units (IMUs) to create a reliable spinal model for monitoring hunchback posture at home. The method shows potential for remote medical care applications.

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    Area of Science:

    • Biomedical Engineering
    • Medical Imaging
    • Rehabilitation Technology

    Background:

    • Hunchback (kyphosis) is a common postural issue requiring accessible monitoring solutions.
    • Current methods for assessing spinal curvature can be complex and may not be suitable for home use.
    • Developing non-invasive, user-friendly tools for posture assessment is crucial for early intervention.

    Purpose of the Study:

    • To propose and validate an algorithm for computing sagittal plane spinal curvature using inertial measurement units (IMUs).
    • To construct a personalized spinal model by integrating IMU data with neural network-derived features.
    • To assess the accuracy and reliability of the developed method for home-based posture monitoring.

    Main Methods:

    • Five IMUs were attached to the spine's surface to collect movement data.
    • A neural network, trained on X-ray data, extracted personalized spinal features.
    • The algorithm integrated IMU data and spinal features to construct a 3D spinal model.
    • An optical motion capture system was used for algorithm validation.

    Main Results:

    • The algorithm achieved an average Hausdorff distance (HD) of 9.873% and a mean absolute error (MAE) of 4.830% relative to total spine length.
    • The sagittal vertical axis showed an average relative error of 14.941%.
    • The constructed spinal model demonstrated high accuracy and quantifiability.

    Conclusions:

    • The proposed algorithm reliably generates a quantifiable spinal model for static posture assessment.
    • This method offers a promising solution for home monitoring of spinal conditions like hunchback.
    • The technology has significant potential for remote medical care and telehealth applications.