Fuzzy Based Model to Detect Patient’s Health Decline in Ambient Assisted Living

Milene Santos Teixeira, Vinicius Maran, João Carlos D. Lima, Iara Augustin, Alencar Machado

2017

Abstract

Detecting a decline in the health condition of a patient may still be considered a challenge in Ambient Assisted Living (AAL) since the concept of ‘decline’ is vague and imprecise. In this context, Fuzzy Logic comes as an excellent alternative for AAL systems. This paper presents a model based on Fuzzy logic reasoning in order to identify a possible decline in the patient health condition. In order to achieve this goal, the model considers relevant situations that may somehow impact the patient. To evaluate the model, a case study was developed, showing that the developed model can simulate the human reasoning and be used in an AAL system.

Paper Citation

in Harvard Style

Santos Teixeira M., Maran V., D. Lima J., Augustin I. and Machado A. (2017). Fuzzy Based Model to Detect Patient’s Health Decline in Ambient Assisted Living . In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-247-9, pages 659-666. DOI: 10.5220/0006368806590666

in Bibtex Style

@conference{iceis17,
author={Milene Santos Teixeira and Vinicius Maran and João Carlos D. Lima and Iara Augustin and Alencar Machado},
title={Fuzzy Based Model to Detect Patient’s Health Decline in Ambient Assisted Living},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2017},
pages={659-666},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006368806590666},
isbn={978-989-758-247-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Fuzzy Based Model to Detect Patient’s Health Decline in Ambient Assisted Living
SN - 978-989-758-247-9
AU - Santos Teixeira M.
AU - Maran V.
AU - D. Lima J.
AU - Augustin I.
AU - Machado A.
PY - 2017
SP - 659
EP - 666
DO - 10.5220/0006368806590666