Inverse kinematics of a 6 DoF human upper limb using ANFIS and ANN for anticipatory actuation in ADL-based physical Neurorehabilitation

Pérez Rodríguez, Rodrigo; Marcano Cedeño, Alexis Enrique; Costa, Ursula; Solana Sánchez, Javier; Cáceres Taladriz, César; Opisso, Eloy; Tormos Muñoz, Josep M.; Medina, Josep y Gómez Aguilera, Enrique J. (2012). Inverse kinematics of a 6 DoF human upper limb using ANFIS and ANN for anticipatory actuation in ADL-based physical Neurorehabilitation. "Expert Systems With Applications", v. 39 (n. 10); pp. 9612-9622. ISSN 0957-4174. https://doi.org/10.1016/j.eswa.2012.02.143.

Descripción

Título: Inverse kinematics of a 6 DoF human upper limb using ANFIS and ANN for anticipatory actuation in ADL-based physical Neurorehabilitation
Autor/es:
  • Pérez Rodríguez, Rodrigo
  • Marcano Cedeño, Alexis Enrique
  • Costa, Ursula
  • Solana Sánchez, Javier
  • Cáceres Taladriz, César
  • Opisso, Eloy
  • Tormos Muñoz, Josep M.
  • Medina, Josep
  • Gómez Aguilera, Enrique J.
Tipo de Documento: Artículo
Título de Revista/Publicación: Expert Systems With Applications
Fecha: Agosto 2012
Volumen: 39
Materias:
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Tecnología Fotónica [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Objective: This research is focused in the creation and validation of a solution to the inverse kinematics problem for a 6 degrees of freedom human upper limb. This system is intended to work within a realtime dysfunctional motion prediction system that allows anticipatory actuation in physical Neurorehabilitation under the assisted-as-needed paradigm. For this purpose, a multilayer perceptron-based and an ANFIS-based solution to the inverse kinematics problem are evaluated. Materials and methods: Both the multilayer perceptron-based and the ANFIS-based inverse kinematics methods have been trained with three-dimensional Cartesian positions corresponding to the end-effector of healthy human upper limbs that execute two different activities of the daily life: "serving water from a jar" and "picking up a bottle". Validation of the proposed methodologies has been performed by a 10 fold cross-validation procedure. Results: Once trained, the systems are able to map 3D positions of the end-effector to the corresponding healthy biomechanical configurations. A high mean correlation coefficient and a low root mean squared error have been found for both the multilayer perceptron and ANFIS-based methods. Conclusions: The obtained results indicate that both systems effectively solve the inverse kinematics problem, but, due to its low computational load, crucial in real-time applications, along with its high performance, a multilayer perceptron-based solution, consisting in 3 input neurons, 1 hidden layer with 3 neurons and 6 output neurons has been considered the most appropriated for the target application.

Más información

ID de Registro: 15299
Identificador DC: http://oa.upm.es/15299/
Identificador OAI: oai:oa.upm.es:15299
Identificador DOI: 10.1016/j.eswa.2012.02.143
URL Oficial: http://www.sciencedirect.com/science/article/pii/S095741741200406X
Depositado por: Memoria Investigacion
Depositado el: 05 Jun 2013 16:14
Ultima Modificación: 21 Abr 2016 15:21
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