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Gait measurement system for the multi-target stepping task using a laser range sensor.

Ayanori Yorozu1, Shu Nishiguchi2, Minoru Yamada3

  • 1School of Science for Open and Environmental Systems, Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan. ayanoriyorozu@a5.keio.jp.

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This study introduces an improved gait measurement system for elderly fall prevention. The novel leg detection method enhances accuracy in tracking steps during the multi-target stepping task (MTST).

Keywords:
Kalman filterdata associationgait measurementlaser range sensor

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Area of Science:

  • Biomechanics
  • Gerontology
  • Robotics and Sensors

Background:

  • Gait training, including the multi-target stepping task (MTST), is crucial for preventing falls in the elderly.
  • Existing gait measurement systems face challenges with leg tracking accuracy due to occlusions and leg proximity during MTST.

Purpose of the Study:

  • To develop and validate an advanced gait measurement system for the MTST to accurately assess fall risk in the elderly.
  • To enhance leg detection and tracking capabilities for improved gait analysis.

Main Methods:

  • A novel leg detection method utilizing five observed leg patterns and global nearest neighbor-based data association with adaptive validation regions.
  • Development of algorithms to accurately judge target steps and detect cross steps based on leg trajectory analysis.
  • Implementation of a laser range sensor-based system for real-time gait parameter measurement.

Main Results:

  • The proposed system significantly improves leg-tracking performance, overcoming issues of leg occlusion and proximity.
  • High accuracy was achieved in judging target steps and detecting cross steps, crucial for cognitive and gait assessment.
  • Experimental validation with elderly participants confirmed the system's effectiveness in gait analysis for fall risk evaluation.

Conclusions:

  • The novel leg detection and trajectory analysis system offers a robust solution for accurate gait measurement during the MTST.
  • This technology has the potential to enhance the effectiveness of fall prevention strategies for the elderly.
  • Improved gait and cognitive function assessment through accurate leg tracking can lead to better personalized interventions.