What question did this study set out to answer?

The aim is to enhance biometric recognition of human gait by addressing disruptions caused by asymmetric loading.

March 21, 2026SensorsOpen Access

Recognition of Human Gait Under Asymmetric Loading

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Authors

MDMarcin DerlatkaBialystok University of Technology

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Implication

This work demonstrates high accuracy in gait recognition under asymmetric loading using advanced classifiers, suggesting improved identification methods.

Key Points

The aim is to enhance biometric recognition of human gait by addressing disruptions caused by asymmetric loading.
Utilized ensemble classifiers and deep neural networks as base classifiers.
Employed data augmentation to improve model generalization.
Tested on a sample of 215 individuals, covering 7351 gait cycles.
Analyzed different strategies for combining classifier decisions.
Achieved accuracy rates of 99.8%, 98.55%, and 98.85% under varying scenarios.
Results significantly exceeded existing methods documented in related literature.

Cite This Study

Marcin Derlatka (2026) studied this question.

synapsesocial.com/papers/69be371c6e48c4981c6768b8 https://doi.org/10.3390/s26061940

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Implication

This work demonstrates high accuracy in gait recognition under asymmetric loading using advanced classifiers, suggesting improved identification methods.

Recognition of Human Gait Under Asymmetric Loading

Discussion

Member takes

Implication

Key Points

Cite This Study

Recognition of Human Gait Under Asymmetric Loading

Discussion

Member takes

Implication

Key Points

Cite This Study

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