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Hip Positioning and Sitting Posture Recognition Based on Human Sitting Pressure Image.

Qilong Wan1, Haiming Zhao1,2, Jie Li1

  • 1College of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China.

Sensors (Basel, Switzerland)
|January 13, 2021
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This study introduces an intelligent system for recognizing poor sitting posture using a novel hip positioning algorithm. The system achieves high accuracy in identifying different postures, aiding in health improvement.

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hip positioning algorithmsitting posture classificationsitting pressure image acquisition systemsupport vector machine

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Area of Science:

  • Biomedical Engineering
  • Computer Science
  • Ergonomics

Background:

  • Poor sitting posture poses significant health risks.
  • Intelligent algorithms can prompt posture correction.
  • A system for acquiring sitting pressure images was developed.

Purpose of the Study:

  • To propose an innovative hip positioning algorithm based on hip templates.
  • To extract regional pressure values for posture classification.
  • To achieve accurate recognition of sitting postures.

Main Methods:

  • Designed a sitting pressure image acquisition system.
  • Developed a hip positioning algorithm using hip templates.
  • Utilized Support Vector Machine (SVM) with a polynomial kernel for classification.

Main Results:

  • The hip positioning algorithm achieved an average deviation of 1.306 pixels (1.50 cm).
  • 94.1% of maximum positioning deviations were less than three pixels.
  • Sitting posture classification accuracy reached 89.6%.

Conclusions:

  • The proposed hip positioning algorithm is effective and adaptable to various subjects and rotation angles.
  • The system accurately extracts features for posture classification.
  • The intelligent system shows promise for improving sitting habits and health.