Semiautomatic validation of RR time series in an ECG stress test database

Jairo Armijos; David García; Darwin Astudillo; Kenneth Palacio-Baus; Rubén Medina; Sara Wong

doi:10.1117/12.2214314

22 December 2015 Semiautomatic validation of RR time series in an ECG stress test database

Jairo Armijos, David García, Darwin Astudillo, Kenneth Palacio-Baus, Rubén Medina, Sara Wong

Proceedings Volume 9681, 11th International Symposium on Medical Information Processing and Analysis; 968119 (2015) https://doi.org/10.1117/12.2214314
Event: 11th International Symposium on Medical Information Processing and Analysis (SIPAIM 2015), 2015, Cuenca, Ecuador

Abstract

This paper reports an automatic method for characterizing the quality of the RR-time series in the stress test database known as DICARDIA. The proposed methodology is simple and consists in subdividing the RR time series in a set of windows for estimating the quantity of artifacts based on a threshold value that depends on the standard deviation of RR-time series for each recorded lead. In a first stage, a manual annotation was performed considering four quality classes for the RR-time series (Reference lead, Good Lead, Low Quality Lead and Useless Lead). Automatic annotation was then performed varying the number of windows and threshold value for the standard deviation of the RR-time series. The metric used for evaluating the quality of the annotation was the Matching Ratio. The best results were obtained using a higher number of windows and considering only three classes (Good Lead, Low Quality Lead and Useless). The proposed methodology allows the utilization of the online available DICARDIA Stress Test database for different types of research.

Citation Download Citation

Jairo Armijos, David García, Darwin Astudillo, Kenneth Palacio-Baus, Rubén Medina, and Sara Wong "Semiautomatic validation of RR time series in an ECG stress test database", Proc. SPIE 9681, 11th International Symposium on Medical Information Processing and Analysis, 968119 (22 December 2015); https://doi.org/10.1117/12.2214314

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