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projects:year6:6a.002.tut

6a.002.TUT - Monitoring & Advance Warning for Cardiac Arrhythmia Using PCG & ECG

Project - Summary

Auscultation of heart, besides the advanced heart diagnostic methods, continues to play an important role. The high correlation between phonocardiographic events and the characteristics of the hemodynamic affirm the heart sound crucial role in outpatient monitoring. In this project, we focus deliberately on the anomaly detection of heart sounds by using 1D Convolutional Neural Networks (CNN) trained with a novel data purification approach. The experimental results over the PhysioNet (CinC) Challenge 2016 benchmark dataset show that the proposed approach achieves high detection performance and a real-time processing ability under the condition that a reasonable signal quality (SNR) is present.

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Moncef Gabbouj PI moncef.gabbouj@tuni.fi +358 (400) 736613 Tampere University
Serkan Kiranyaz Co-PI Serkan.kiranyaz@tut.fi 97 43 063 5600 Tampere University
Morteza Zabihi Researcher Morteza.zabihi@tut.fi Not available Tampere University
Matti Vakkuri Project Mentor Not available +358 (40) 512 6894 Tieto

Project - Deliverables

Deliverables
1 Realization of the capabilities of the PCG/ECG signals in early detection of heart anomalies.
2 Design the state of the art classification method (Normal vs. Abnormal) for the PCG dataset.
3 Design the state of the art classification method (Normal, AF, other rhythms, and too noisy) for the ECG dataset.
4 Modeling the common cause of “degradation system” for advance warning.

Project - Documents

FilenameFilesizeLast modified
6a.002.tut_poster_pdf.pdf847.3 KiB2019/08/14 15:25
6a.002.tut_monitoring_and_advance_warning_for_cardiac_poster_2017_fall_meeting.pptx2.6 MiB2019/08/14 15:25
6a.002.tut_ppt_presentation.pptx3.7 MiB2019/08/14 15:25
6a.002.tut_poster_ppt.pptx3.4 MiB2019/08/14 15:25
6a.002.tut_executive_summary.pdf83.5 KiB2019/08/14 15:25
6a.002.tut_confluence_project_page.pdf147.2 KiB2019/08/14 15:25
6a.002.tut_final_report.docx956.9 KiB2019/08/14 15:25
6a.002.tut_cvdi_mid-year-report.pdf278.0 KiB2019/08/14 15:25
projects/year6/6a.002.tut.txt · Last modified: 2021/06/02 14:45 by sally.johnson