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Predicting triplanar and bidirectional movements for a transtibial prosthesis for rehabilitation using intelligent neural networks

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Abstract

In this study, artificial neural networks (NN) are applied to the design of a transtibial prosthesis to adapt triplanar and bidirectional movements of human locomotion for rehabilitation. NN-based control is used because the prosthesis system is highly nonlinear and has variables with too many uncertainties caused by variations in ankle movements, weight damping, dorsiflexion, and flexion in the amputation area due to biological stimuli. To identify and detect these movements in the transtibial prosthesis, myoelectric signals are used that determine its position and adapt its trajectory through linear and rotary actuators. The input and desired parameters for the NN controller and the backpropagation algorithm are obtained based on the movements of the human ankle and foot based on their trajectory. The prototype is manufactured from different types of plastic using a 3D grapher, which can perform the main stages of human locomotion due to the learning carried out by the NN, reducing the risk of falls, and having a more comfortable and natural gait cycle in the rehabilitation of people. From the output response obtained from the NN controller, only a time delay is obtained without overshoot terms, and the trajectory tracking is adjusted. Simulation and experimental results show that the proposed NN-based control system can ensure the stability of the system and maintain good tracking of human locomotion.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This work was supported by the Tecnologico Nacional de Mexico of the Tecnologico de Estudios Superiores de Ecatepec.

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Authors and Affiliations

  1. Tecnologico Nacional de Mexico, Tecnologico de Estudios Superiores de Ecatepec, Ecatepec de Morelos, Mexico

    Jesus de la Cruz-Alejo, J. Antonio Lobato-Cadena, M. Belem Arce-Vázquez & Agustin Mora-Ortega

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  1. Jesus de la Cruz-Alejo
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  2. J. Antonio Lobato-Cadena
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  3. M. Belem Arce-Vázquez
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Contributions

Experimental were from L-C and A-V. Data collection was performed by M-O, de la C-A. Data analysis was performed by de la C-A and L-C. The first draft was written by de la C-A and L-C, and M-O reviewed and edited the draft. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript and agree with the order of presentation of the authors.

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Correspondence to Jesus de la Cruz-Alejo.

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de la Cruz-Alejo, J., Lobato-Cadena, J.A., Arce-Vázquez, M.B. et al. Predicting triplanar and bidirectional movements for a transtibial prosthesis for rehabilitation using intelligent neural networks. Neural Comput & Applic 36, 6085–6098 (2024). https://doi.org/10.1007/s00521-023-09393-0

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