A robotic assistant based on fuzzy logic and kinesthetic stimuli for gross motor rehabilitation of children with disabilities

Brian Pinos-Chuya, Víctor Uguña-Uguña, Angel Pérez-Muñóz, Paola Suquilanda-Cuesta, Vladimir Robles-Bykbaev, Katherine González-Arias

Research output: Contribution to journalArticlepeer-review

Abstract

Cerebral Palsy (CP) is considered one of the most common types of motor disability in childhood. Worldwide the latest estimates claim that prevalence of CP is between 1.5 to more than 4 per 1,000 live births. In the same way, children and adolescents with intellectual disabilities are characterized by deficits in fundamental movement skills. For these reasons, it is essential providing early intervention plans for children that present motor difficulties. In this line, this paper describes a robotic assistant that adapts the velocity of its movements to respond to the patient’s profile during therapy sessions. To this aim, the robot uses a fuzzy logic-based inference module that considers three variables of the patient’s profile: disability level, intelligence quotient, and age. During the robot’s preliminary validation, we have obtained encouraging results in both laboratory tests and in the interaction with experts.

Original languageEnglish
Pages (from-to)213-224
Number of pages12
JournalRISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
Volume2020
Issue numberE 33
StatePublished - Aug 2020

Bibliographical note

Publisher Copyright:
© 2020, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Children with disabilities
  • Expert system
  • Fuzzy logic
  • Gross motor skills
  • Robotic assistant

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