@inproceedings{01ee99ffb1e7491997b68e7692e1e58c,
title = "Using fuzzy logic for decision support in vital signs monitoring",
abstract = "This research investigated whether a fuzzy logic rule-based decision support system could be used to detect potentially abnormal health conditions, by processing physiological data collected from vital signs monitoring devices. An application of the system to predict postural status of a person was demonstrated using real data, to mimic the effects of body position changes while doing certain normal daily activities. The results gathered in this experiment achieved accuracies of >85%. Applying this type of fuzzy logic approach, a decision system could be constructed to inform necessary actions by caregivers or for a person themself to make simple care decisions to manage their health situation.",
author = "Shohas Dutta and Anthony Maeder and Jim Basilakis",
year = "2013",
language = "English",
publisher = "CEUR-WS.org",
pages = "29--33",
booktitle = "Proceedings of the Third Australasian Workshop on Artificial Intelligence in Health (AIH 2013) and the Fourth International Workshop on Collaborative Agents - Research and Development (CARE 2013) co-located with the 26th Australasian Joint Conference on Artificial Intelligence (AI 2013) Dunedin, New Zealand, December 3, 2013",
note = "Australasian Workshop on Artificial Intelligence in Health ; Conference date: 03-12-2013",
}