Title :
Effect of ECG quality measures on piecewise-linear trend detection for telehealth decision support systems
Author :
Xie, Yang ; Redmond, Stephen J. ; Basilakis, Jim ; Lovell, Nigel H.
Author_Institution :
Grad. Sch. of Biomed. Eng., Univ. of New South Wales, Sydney, NSW, Australia
fDate :
Aug. 31 2010-Sept. 4 2010
Abstract :
Fledgling clinical decision support systems (DSSs) are being designed on the false assumption that consistent, good-quality signals are created in the unsupervised telehealth environment, but it has in fact been shown that signal quality is often very poor. Hence, it is important to investigate the detrimental impact of failing to recognize erroneous clinical parameter values. This study combines previous work in this area, related to artifact detection in electrocardiogram (ECG) signals, and piecewise-linear trend detection in longitudinal heart rate parameter records, to investigate the impact of choosing to ignore ECG signal quality prior to trend detection in the heart rate (HR) records. Using an artifact detection algorithm to improve the HR estimates from the ECG signals, when compared to reference HR values derived from human annotated 2453 ECGs from nine patients, resulted in a decrease in the estimation bias from 2.54 BPM (beat per minute) to 0.70 BPM and a decrease in the standard error from 0.47 BPM to 0.17 BPM. The application of the same artifact detection also results in a significant improvement in trend fitting, when compared to a fitting of the reference HR values, by reducing the mean RMSE value of the error in the trend fit from 2.14 BPM to 0.78 BPM and standard error from 0.49 BPM to 0.10 BPM. As trend detection will be a component of future telehealth decision support systems, signal quality measures for unsupervised measurements are of paramount importance.
Keywords :
decision support systems; electrocardiography; medical signal processing; piecewise linear techniques; telemedicine; ECG quality measures; ECG signals; artifact detection; beat per minute; clinical decision support systems; electrocardiogram; longitudinal heart rate parameter records; piecewise-linear trend detection; trend fitting; unsupervised telehealth environment; Decision support systems; Detection algorithms; Electrocardiography; Fitting; Heart rate; Humans; Monitoring; Aged; Aged, 80 and over; Algorithms; Artifacts; Computer Graphics; Decision Support Systems, Clinical; Electrocardiography; Heart Rate; Humans; Linear Models; Middle Aged; Quality Control; Reproducibility of Results; Signal Processing, Computer-Assisted; Telemedicine;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5626080