Sitting posture detection using fuzzy logic development of a neuro-fuzzy algorithm to classify postural transitions in a sitting posture

Bruno Ribeiro, Leonardo Martins, Hugo Pereira, Rui Almeida, Cláudia Regina Pereira Quaresma, Adelaide Ferreira, Pedro Vieira

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

In a previous work, a chair prototype was used to detect 11 standardized seating 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 a new classification algorithm, which was developed in order to classify the postures using as input the Centre of Pressure, the Posture Adoption Time and the Posture Output from the existing Neural Network Algorithm. This new Posture Classification Algorithm is based on Fuzzy Logic and is able to determine if the user is adopting a good or a bad posture for specific time periods. The newly developed Classification Algorithms will prompt the improvement of new Posture Correction Algorithms based on Fuzzy Actuators.

Original languageEnglish
Title of host publicationHEALTHINF 2015 - 8th International Conference on Health Informatics, Proceedings; Part of 8th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2015
PublisherSciTePress
Pages191-199
Number of pages9
ISBN (Electronic)9789897580680
Publication statusPublished - 2015
Event8th International Conference on Health Informatics, HEALTHINF 2015 - Lisbon, Portugal
Duration: 12 Jan 201515 Jan 2015

Conference

Conference8th International Conference on Health Informatics, HEALTHINF 2015
CountryPortugal
CityLisbon
Period12/01/1515/01/15

Keywords

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

Fingerprint Dive into the research topics of 'Sitting posture detection using fuzzy logic development of a neuro-fuzzy algorithm to classify postural transitions in a sitting posture'. Together they form a unique fingerprint.

Cite this