A Fuzzy Logic Approach for a Wearable Cardiovascular and Aortic Monitoring System

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Oliveira, CC (Author) Other; Dias, R (Author) Other; José Machado da Silva (Author) FEUP

Conference proceedings International

Title: ICT INNOVATIONS 2015: EMERGING TECHNOLOGIES FOR BETTER LIVING

Pages: 265-274

7th ICT Innovations conference on Emerging Technologies for Better Living

Ohrid, MACEDONIA, OCT 01-04, 2015

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 4 Citations

Other information

Authenticus ID: P-00G-TNK

DOI: 10.1007/978-3-319-25733-4_27

Abstract (EN): A new methodology for fault detection on wearable medical devices is proposed. The basic strategy relies on correctly classifying the captured physiological signals, in order to identify whether the actual cause is a wearer health abnormality or a system functional flaw. Data fusion techniques, namely fuzzy logic, are employed to process the physiological signals, like the electrocardiogram (ECG) and blood pressure (BP), to increase the trust levels of the captured data after rejecting or correcting distorted vital signals from each sensor, and to provide additional information on the patient's condition by classifying the set of signals into normal or abnormal condition (e.g. arrhythmia, chest angina, and stroke). Once an abnormal situation is detected in one or several sensors the monitoring system runs a set of tests in a fast and energy efficient way to check if the wearer shows a degradation of his health condition or the system is reporting erroneous values.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10