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Real-Time Fuzzy Monitoring of Sitting Posture: Development of a New Prototype and a New Posture Classification Algorithm to Detect Postural Transitions

  • Leonardo MartinsEmail author
  • Bruno Ribeiro
  • Hugo Pereira
  • Rui Almeida
  • Jéssica Costa
  • Cláudia Quaresma
  • Adelaide Jesus
  • Pedro Vieira
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 574)

Abstract

In a previous work, a chair prototype was used to detect 11 standardized siting postures of users, using just 8 air bladders (4 in the chair’s seat and 4 in the backrest) and one pressure sensor for each bladder. In this paper we describe the development of a new prototype, which is able to classify 12 standard postures with an overall score of 80.9 % (using a Neural Network Algorithm). We tested how this Algorithm worked during postural transitions (frontal and lateral flexion) and in intermediate postures, identifying some limitation of this Algorithm. This prompted the development of a Posture Classification Algorithm based on Fuzzy Logic and is able to determine if the user is adopting a good or a bad posture for specific time periods, using as input the Centre of Pressure, the Posture Adoption Time and the Posture Output from the existing Neural Network Algorithm. This newly developed Classification Algorithms is advancing the development of new Posture Correction Algorithms based on Fuzzy Actuators.

Keywords

Intelligent chair Pressure-distribution sensors Sitting posture Posture classification Fuzzy logic Neural Networks 

Notes

Acknowledgements

This project (QREN 13330 – SYPEC) is supported by FEDER, QREN – Quadro de Referência Estratégico Nacional, Portugal 07/13 and PORLisboa – Programa Operacional Regional de Lisboa. The authors wish to thank Eng. Pedro Duque, Eng. Rui Lucena, Eng. João Belo and Eng. Marcelo Santos for the help provided in the construction of the first prototype.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Leonardo Martins
    • 2
    • 1
    Email author
  • Bruno Ribeiro
    • 1
  • Hugo Pereira
    • 1
  • Rui Almeida
    • 1
  • Jéssica Costa
    • 1
  • Cláudia Quaresma
    • 3
  • Adelaide Jesus
    • 1
  • Pedro Vieira
    • 3
  1. 1.Department of Physics, Faculdade de Ciências e TecnologiasUniversidade Nova de LisboaCaparicaPortugal
  2. 2.UNINOVAInstitute for the Development of New TechnologiesCaparicaPortugal
  3. 3.LIBPhys-UNL, Department of Physics, Faculdade de Ciências e TecnologiasUniversidade Nova de LisboaMonte da CaparicaPortugal

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