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

Pérez Rodríguez, Rodrigo and Marcano Cedeño, Alexis Enrique and Costa, Ursula and Solana Sánchez, Javier and Cáceres Taladriz, César and Opisso, Eloy and Tormos Muñoz, Josep M. and Medina, Josep and 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.

Description

Title: Inverse kinematics of a 6 DoF human upper limb using ANFIS and ANN for anticipatory actuation in ADL-based physical Neurorehabilitation
Author/s:
  • 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.
Item Type: Article
Título de Revista/Publicación: Expert Systems With Applications
Date: August 2012
ISSN: 0957-4174
Volume: 39
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Tecnología Fotónica [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

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.

More information

Item ID: 15299
DC Identifier: http://oa.upm.es/15299/
OAI Identifier: oai:oa.upm.es:15299
DOI: 10.1016/j.eswa.2012.02.143
Official URL: http://www.sciencedirect.com/science/article/pii/S095741741200406X
Deposited by: Memoria Investigacion
Deposited on: 05 Jun 2013 16:14
Last Modified: 21 Apr 2016 15:21
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