Increasing accuracy of pulse transit time measurements by automated elimination of distorted photoplethysmography waves

• Published in: Medical & biological engineering & computing Vol. 55; no. 11; pp. 1989 - 2000
• Main Authors: van Velzen, Marit H. N., Loeve, Arjo J., Niehof, Sjoerd P., Mik, Egbert G.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2017; Springer Nature B.V
• Subjects: Adult; Algorithms; Artefacts; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Computer Applications; EKG; Female; Heart Rate - physiology; Human Physiology; Humans; Imaging; Male; Mathematical analysis; Original; Original Article; Photoplethysmography - methods; Pulse - methods; Pulse Wave Analysis - methods; Radiology; Reproducibility; Reproducibility of Results; Sensitivity and Specificity; Time measurement; Transit time; Young Adult; Pressure pulse waves (PWs); Pulse transit time (PTT); Algorithm; Photoplethysmography (PPG)
• DOI: 10.1007/s11517-017-1642-x
• ISSN: 0140-0118; 1741-0444

Photoplethysmography (PPG) is a widely available non-invasive optical technique to visualize pressure pulse waves (PWs). Pulse transit time (PTT) is a physiological parameter that is often derived from calculations on ECG and PPG signals and is based on tightly defined characteristics of the PW shape. PPG signals are sensitive to artefacts. Coughing or movement of the subject can affect PW shapes that much that the PWs become unsuitable for further analysis. The aim of this study was to develop an algorithm that automatically and objectively eliminates unsuitable PWs. In order to develop a proper algorithm for eliminating unsuitable PWs, a literature study was conducted. Next, a ‘7Step PW-Filter’ algorithm was developed that applies seven criteria to determine whether a PW matches the characteristics required to allow PTT calculation. To validate whether the ‘7Step PW-Filter’ eliminates only and all unsuitable PWs, its elimination results were compared to the outcome of manual elimination of unsuitable PWs. The ‘7Step PW-Filter’ had a sensitivity of 96.3% and a specificity of 99.3%. The overall accuracy of the ‘7Step PW-Filter’ for detection of unsuitable PWs was 99.3%. Compared to manual elimination, using the ‘7Step PW-Filter’ reduces PW elimination times from hours to minutes and helps to increase the validity, reliability and reproducibility of PTT data.