Jusak, Jusak 
ORCID: https://orcid.org/0000-0001-5646-4865, Puspasari, Ira and Kusumawati, Weny Indah
(2021)
A Semi-automatic Heart Sounds Identification Model and Its Implementation in Internet of Things Devices.
Advances In Electrical and Computer Engineering (AECE), 21 (1).
pp. 45-56.
ISSN 1582-7445
|
Text
1. Dokumen AECE2021.pdf - Accepted Version Download (3MB) | Preview |
|
|
Text
2. Peer Review AECE 2021.pdf - Accepted Version Download (237kB) | Preview |
|
|
Text
3. Turnitin AECE2021.pdf - Accepted Version Download (5MB) | Preview |
|
|
Text
4. Review Correspondence.pdf - Accepted Version Download (217kB) | Preview |
Search this title on : 
| 
Abstract
Identification of heart sound signals in the form of a phonocardiogram (PCG) has recently attracted the attention of many researchers along with the development of small devices and global Internet connection in a way to offer automatic illness detection and monitoring. In this work, we propose a semi-automatic envelope-based heart sounds identification method called the Largest Interval Heart Sounds Detection (LiHSD) that exploits the superiority of the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and the cubic spline interpolation to discover several heart sounds’ components such as period and location of S1 and S2, an interval of a cardiac cycle, and to obtain the duration and location of murmurs. Evaluation of the proposed system over several life sample data showed promising results comparable to the previous models. The algorithm was able to capture the largest interval of S1 and S2. The examination for normal heart sounds exhibited detection accuracy 98%, whereas for anomaly heart sounds samples the detection accuracy ranging from 89% to 97.5%. Furthermore, the proposed system has been successfully implemented in a real Internet of Things device while eyeing its contribution to the future of the smart healthcare system.
Export Record
| Item Type: | Article |
|---|---|
| Additional Information: | Jusak, Ira Puspasari, Weny Indah Kusumawati |
| Uncontrolled Keywords: | Internet of Things, phonocardiography, signal detection, system identification, telemedicine |
| Dewey Decimal Classification: | 600 – Technology > 620 Engineering & Applied operations > 621 Applied physics |
| Divisions: | Perpustakaan > Journals |
| Depositing User: | Annuh Liwan Nahar |
| Date Deposited: | 10 May 2021 14:22 |
| Last Modified: | 15 Mar 2022 10:57 |
| URI: | http://repository.dinamika.ac.id/id/eprint/5608 |
Download Statistics
Downloads over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
Actions (login required)
 |
View Item |
Altmetric
Altmetric