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Self-Tuning Threshold Method for Real-Time Gait Phase Detection Based on Ground Contact Forces Using FSRs.

Jing Tang^1,2, Jianbin Zheng^3,4, Yang Wang^5,6

¹School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China. mimitang85119@163.com.

Sensors (Basel, Switzerland)

|February 9, 2018

Summary

This study introduces a self-tuning triple threshold algorithm (STTTA) for accurate human gait phase detection. The novel method adapts to various walking speeds and individuals, improving upon previous threshold methods.

Keywords:

adaptability force sensitive resistors self-tuning triple threshold algorithm

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Area of Science:

Biomechanics
Human locomotion analysis
Wearable sensor technology

Background:

Existing gait phase detection methods lack adaptability to individual variations and walking speeds.
Traditional threshold methods for analyzing ground contact forces (GCFs) are insufficient for diverse populations.

Purpose of the Study:

To develop and validate a novel, adaptive algorithm for real-time gait phase detection.
To overcome the limitations of previous methods in accommodating different individuals and walking paces.

Main Methods:

Implementation of a self-tuning triple threshold algorithm (STTTA) using two force sensitive resistors (FSRs) on the ball and heel.
Utilizing high, middle, and low thresholds to self-adjust based on maximum and minimum GCFs.
Employing a gait phase detection algorithm (GPDA) for rule-based calculations within the STTTA framework.

Main Results:

The STTTA demonstrates high reliability in real-time gait phase detection.
The proposed method shows significant adaptability to different users and walking speeds.
Validation against established methods like the Mariani method (timing analysis module) and Lopez-Meyer methods confirms reliability.

Conclusions:

The STTTA offers a robust and adaptable solution for gait phase detection in human walking.
This novel approach enhances the accuracy and applicability of GCF analysis in biomechanics.
The method's adaptability makes it suitable for diverse real-world applications requiring precise gait analysis.