Using Fuzzy Logic for Decision Support in Vital Signs Monitoring

Shohas Dutta, Anthony Maeder, Jim Basilakis

    Research output: Contribution to conferencePaperpeer-review

    1 Citation (Scopus)

    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. .

    Original languageEnglish
    Pages29-33
    Number of pages5
    Publication statusPublished - 2013
    EventAustralasian Workshop on Artificial Intelligence in Health (AIH 2013) and International Workshop on Collaborative Agents - Research and Development (CARE 2013) -
    Duration: 3 Dec 2013 → …

    Conference

    ConferenceAustralasian Workshop on Artificial Intelligence in Health (AIH 2013) and International Workshop on Collaborative Agents - Research and Development (CARE 2013)
    Period3/12/13 → …

    Keywords

    • Assistive technologies
    • Care management
    • Decision support
    • Fuzzy logic
    • Patient monitoring

    Fingerprint Dive into the research topics of 'Using Fuzzy Logic for Decision Support in Vital Signs Monitoring'. Together they form a unique fingerprint.

    Cite this