Key result
Applying the Hilbert Huang Transform to ECG signals re-classified 4 of 24 pseudo-positive cases as positive, reducing pseudo-positives requiring follow-up testing by 83.3%.
Why the study?
Cardiovascular diseases are the leading cause of death worldwide, and new non-invasive methods are needed to improve upon standard exercise ECG testing.
Does Hilbert Huang Transform (HHT) of ECG signals improve diagnostic accuracy compared to standard 12-lead ECG in patients undergoing exercise testing?
Observational (n=49)
Does Hilbert Huang Transform (HHT) of ECG signals improve diagnostic accuracy compared to standard 12-lead ECG in patients undergoing exercise testing?
Answers are grounded in this paper and cite their sources.
The use of Hilbert Huang Transform for ECG signal decomposition may significantly reduce false-positive results in exercise testing, potentially saving medical resources.
Statistics released by the World Health Organization in 2018 show that the total death of people is 56.9 million worldwide in 2016. The first one is cardiovascular diseases, including ischemic heart disease and stroke, which accounted for 17.65 million people (31%) [1]. Treadmill Exercise Test is suitable for measuring the changes in Electrocardiography (ECG) initial, middle, and after exercise [2]. They are using it to distinguish chest pain without apparent causes, judging the severity of coronary artery disease, and screening personnel with coronary artery disease risk factors. The most important contribution of this study is to use the Hilbert Huang Transform (HHT) [3], a non-invasive method, to decompose the original ECG signals of inspectors through the Empirical Mode Decomposition (EMD) [4-7], not the commonly used of 12-lead ECG detection method. There is a total of 49 participants in 24 pseudo-positive persons; 4 were re-judged into positive, reducing 83.3% pseudo-positive persons who need to do the follow-up testing, significantly reducing the consumption of medical and time.
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Lin et al. (2020) conducted an observational in Coronary artery disease (n=49). Hilbert Huang Transform (HHT) of ECG signals vs. Standard 12-lead ECG was evaluated on Reduction in pseudo-positive cases. Applying the Hilbert Huang Transform to ECG signals re-classified 4 of 24 pseudo-positive cases as positive, reducing pseudo-positives requiring follow-up testing by 83.3%.
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