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

Author:

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

Funder

Tecnológico Nacional de México

Publisher

Springer Science and Business Media LLC

Reference36 articles.

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2. Cisneros-González N, Ascencio-Montiel IJ, Libreros-Bango VN, Rodríguez-Vázquez H, Campos-Hernández Á, Dávila-Torres J, Kumate-Rodríguez J, Borja-Aburto VH (2016) Índice de amputaciones de extremidades inferiores en pacientes con diabetes [Lower extremity amputation rates in diabetic patients]. Rev Med Inst Mex Seguro Soc 54(4):472–479

3. Gordleeva SY, Lobov SA, Grigorev NA, Savosenkov AO, Shamshin MO, Lukoyanov MV, Khoruzhko MA, Kazantsev VB (2020) Real-time eeg-emg human-machine interface-based control system for a lower-limb exoskeleton. IEEE Access 8:84070

4. Fleming A, Stafford N, Huang S, Hu X, Ferris DP, Huang HH (2021) Myoelectric control of robotic lower limb prostheses: a review of electromyography interfaces, control paradigms, challenges and future directions. J Neural Eng 18:041004

5. Hamzaid NA, Yusof NHM, Jasni F (2019) Sensory systems in micro-processor controlled prosthetic leg: a review. IEEE Sens J 20(9):4544–4554

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