A wavelet approach to detecting electrocautery noise in the ECG

• Published in: IEEE engineering in medicine and biology magazine Vol. 25; no. 4; pp. 76 - 82
• Main Authors: Brouse, C., Dumont, G.A., Herrmann, F.J., Ansermino, J.M.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01-07-2006; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Biomedical monitoring; Computer programs; Diagnosis, Computer-Assisted - methods; Electrocardiography; Electrocardiography - methods; Electrocoagulation; Electrodes; Expert systems; Hardware; Monitoring; Noise; Noise measurement; Patient monitoring; Signal design; Signal Processing, Computer-Assisted; Signal to noise ratio; Software; Trends; Wavelet; Working environment noise
• DOI: 10.1109/MEMB.2006.1657791
• EISSN: 1937-4186
• ISSN: 0739-5175

A software approach has been developed for detecting electrocautery noise in the electrocardiogram (ECG) using a wavelet decomposition of the signal. With this approach, a clinical monitoring expert system can be forewarned of potential artifacts in trend values derived from the ECG, allowing it to proceed with caution when making decisions based on these trends. In 15 operations spanning 38.5 h of ECG data, we achieved a false positive rate of 0.71% and a false negative rate of 0.33%. While existing hardware approaches detect the source of the noise without any ability to assess its impact on the measured ECG, our software approach detects the presence of noise in the signal itself. Furthermore, the software approach is cheaper and easier to implement in a clinical environment than existing hardware approaches