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Related Experiment Video

Updated: Jun 3, 2025

Design and Analysis for Fall Detection System Simplification
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Estimating hip impact velocity and acceleration from video-captured falls using a pose estimation algorithm.

Reese Michaels1, Tiago V Barreira1, Stephen N Robinovitch2

  • 1Department of Exercise Science, Syracuse University, 150 Crouse Dr, Syracuse, NY, 13244, USA.

Scientific Reports
|January 9, 2025
PubMed
Summary
This summary is machine-generated.

AI pose estimation (OpenPose) accurately measures hip impact velocity in older adult falls but struggles with acceleration. This method offers a less labor-intensive alternative to lab studies for analyzing fall biomechanics.

Keywords:
Artificial IntelligenceBiomechanicsFallOlder adultsPose estimation

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Area of Science:

  • Biomechanics
  • Gerontology
  • Artificial Intelligence

Background:

  • Video analysis of falls in older adults is an alternative to lab studies.
  • Manual labeling of body parts in videos is labor-intensive.
  • AI-based pose estimation offers potential for automated analysis.

Purpose of the Study:

  • Validate AI pose estimation (OpenPose) for assessing hip impact velocity and acceleration in older adult falls.
  • Compare AI-derived kinematics against ground truth measurements.
  • Investigate AI's ability to differentiate fall responses.

Main Methods:

  • Analyzed 110 videos of 13 older adults experiencing sideways falls.
  • Applied OpenPose to estimate hip positions and calculate impact kinematics.
  • Validated OpenPose against VICON (velocity) and MC10 (acceleration) systems.

Main Results:

  • OpenPose demonstrated good accuracy for hip impact velocity (MAE: 0.17 m/s, MAPE: 7.28%).
  • OpenPose showed poor accuracy for hip impact acceleration (MAPE: 26.3%), underestimating high impacts.
  • OpenPose could distinguish kinematic differences based on fall response types.

Conclusions:

  • OpenPose is a viable tool for analyzing hip impact velocity in older adult falls.
  • Further validation is needed for hip impact acceleration and diverse fall scenarios.
  • AI pose estimation can aid in understanding fall biomechanics and injury risk.