What question did this study set out to answer?

This study aims to compare various predictive models for foot trajectory complexity during ambulation on different terrains in the context of robotic prostheses.

June 20, 2026Applied IntelligenceOpen Access

Comparative analysis of models capturing foot trajectory complexity across ambulation modes: application to robotic prostheses

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Authors

HKHamza Al KouzbaryUniversity of Malaya MKMouaz Al KouzbaryMinistry of Culture JLJinjing LiuMinistry of Culture

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Implication

Comparative analysis reveals recurrent neural networks generate superior gait signals in powered prostheses, indicating potential for improved control.

Key Points

This study aims to compare various predictive models for foot trajectory complexity during ambulation on different terrains in the context of robotic prostheses.
Collected training and testing data from ten healthy individuals walking on level ground and stairs.
Compared regression-based models, ensemble machine learning methods, and recurrent neural networks (RNNs).
Evaluated predictive accuracy and generalizability across different ambulation modes.
Statistical models showed poor accuracy and generalization for gait prediction.
Ensemble methods achieved moderate performance but were sensitive to outliers and inter-subject variation.
Recurrent neural networks, particularly LSTM, achieved the highest accuracy with a mean correlation of 0.88 and low error of 0.09 rad.

Cite This Study

Kouzbary et al. (2026) studied this question.

synapsesocial.com/papers/6a362de1db0793dc1a535eda https://doi.org/10.1007/s10489-026-07315-w

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Implication

Comparative analysis reveals recurrent neural networks generate superior gait signals in powered prostheses, indicating potential for improved control.

Comparative analysis of models capturing foot trajectory complexity across ambulation modes: application to robotic prostheses

Discussion

Member takes

Implication

Key Points

Cite This Study

Comparative analysis of models capturing foot trajectory complexity across ambulation modes: application to robotic prostheses

Discussion

Member takes

Implication

Key Points

Cite This Study

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