Determination of toe-off event time during treadmill locomotion using kinematic data

Area of Science:

• Biomechanics
• Human Movement Science
• Gait Analysis

Background:

• Accurate gait event detection (heel strike, toe off) is crucial for treadmill locomotion analysis.
• Existing overground gait event detection methods may lack accuracy during treadmill locomotion, especially running.
• Reliance on specialized hardware can be a limitation in gait analysis.

Purpose of the Study:

• To describe and validate a novel method for determining toe-off timing during treadmill locomotion.
• To utilize only kinematic data from motion capture for gait event detection.
• To provide a more accurate alternative to existing methods for treadmill gait analysis.

Main Methods:

• Collected kinematic data (heel and toe marker positions) using motion capture during walking and running on a treadmill.
• Utilized force platforms on the treadmill for ground truth validation of foot-ground contact.
• Developed a method to determine toe-off time based on the vertical component of the toe marker's position.

Main Results:

• The proposed kinematic-based method demonstrated higher accuracy for toe-off event detection compared to previously published methods.
• The method effectively identified gait events using only positional data from heel and toe markers.
• Successful determination of toe-off times was achieved during both walking and running on the treadmill.

Conclusions:

• A validated, accurate method for determining toe-off timing during treadmill locomotion using kinematic data has been established.
• This method offers a valuable tool for researchers analyzing gait on treadmills without requiring additional hardware.
• The findings enable precise gait event identification, enhancing the reliability of treadmill-based locomotion studies.