An Edge Computing Method for Extracting Pathological Information from Phonocardiogram

Sepehri, A. A. (författare): CAPIS Biomedical Research and Development Centre, Mons, Belgium

Babic, A. (författare): Department of Biomedical Engineering, Linköping University, Sweden

(creator_code:org_t)

IOS Press, 2019
2019
Engelska.
Ingår i: Studies in Health Technology and Informatics. - : IOS Press. - 0926-9630 .- 1879-8365. - 9781614999867 ; 262, s. 364-367

Relaterad länk:: https://urn.kb.se/re...; visa fler...; https://doi.org/10.3...; visa färre...

Abstract Ämnesord

Stäng

This paper presents a structure of decision support system for pediatric cardiac disease, based on an Internet of Things (IoT) framework. The structure performs the intelligent decision making at its edge processing level, which classifies the heart sound signal, to three classes of cardiac conditions, normal, mild disease, and critical disease. Three types of the errors are introduced to evaluate the performance of the processing method, Type 1, 2 and 3, defined as the incorrect classification from the critical disease, mild, and normal, respectively. The method is validated using 140 real data patient records collected from the hospital referrals. The estimated negative errors for the Type 1, and 2, are calculated to be 0% and 4.8%, against the positive errors which are 6.3% and 13.3%, respectively. The Type 3, is calculated to be 16.7%, showing a high sensitivity of the method to be used in an IoT healthcare framework.

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