Novel Foot Progression Angle Algorithm Estimation via Foot-Worn, Magneto-Inertial Sensing.

Area of Science:

• Biomechanics
• Wearable Technology
• Gait Analysis

Background:

• The foot progression angle (FPA) is a crucial clinical gait parameter.
• Current FPA measurement relies on laboratory-based, marker-dependent motion capture systems.
• There is a need for portable and accurate FPA estimation methods for real-world applications.

Purpose of the Study:

• To develop and validate a novel algorithm for estimating FPA using a single, foot-worn sensor unit.
• To enable accurate gait analysis in natural environments, moving beyond laboratory constraints.

Main Methods:

• Algorithm development incorporating a real-time heading vector with complementary filtering.
• Implementation of gradient descent and zero-velocity update correction for enhanced accuracy.
• Validation against a marker-based motion capture system across varied walking speeds and foot progression patterns.

Main Results:

• The proposed algorithm achieved FPA estimation with an error of 0.2 degrees or less.
• Accurate FPA estimation was demonstrated across different walking speeds (1.0-1.4 m/s) and gait patterns (normal, toe-in, toe-out).

Conclusions:

• A novel, accurate FPA estimation algorithm utilizing a single foot-worn sensor has been successfully developed and validated.
• This technology facilitates advanced wearable gait research and training in naturalistic settings.