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Related Experiment Video

Updated: Jan 4, 2026

Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder

Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder

Published on: March 4, 2018

Running gait pattern recognition based on cross-correlation analysis of single acceleration sensor.

Ling Fei Mo¹, Lu Jie Zeng¹

¹The School of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu, China.

Mathematical Biosciences and Engineering : MBE

|November 9, 2019

Summary

Running gait analysis is crucial for injury prevention. This study effectively distinguishes between forefoot and rearfoot strike patterns using acceleration sensor data, enabling personalized training programs for runners.

Keywords:

acceleration sensor cross-correlation analysis foot strike gait analysis wearable device

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Last Updated: Jan 4, 2026

Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder

Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder

Published on: March 4, 2018

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults

Published on: November 7, 2014

Home-Based Monitor for Gait and Activity Analysis

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

Area of Science:

Biomechanics
Sports Science
Wearable Technology

Background:

Running is a popular exercise, but improper techniques can lead to injuries, particularly affecting knee joints.
Understanding running gait, specifically foot strike patterns, is vital for optimizing training and preventing health issues.

Purpose of the Study:

To develop and validate a method for identifying and differentiating between forefoot and rearfoot strike running patterns.
To enable personalized training programs by accurately monitoring running gait.

Main Methods:

Utilized cross-correlation analysis on two axial signals from an acceleration sensor.
Designed and conducted experiments to recognize common running gait patterns (forefoot and rearfoot strike).

Main Results:

The proposed method effectively characterized and distinguished between forefoot and rearfoot strike patterns.
Demonstrated good universality and generalization across different subjects.

Conclusions:

The developed technique provides an effective means for monitoring running gait patterns.
This technology can support the customization of training programs to enhance runner safety and performance.