![]() The data set used in the present manuscript comes from two prospective observational studies. We demonstrate that an artifact in the PTT signal referred to as sawtooth artifact can occur because the marketed patient monitor was not designed and calibrated for this specific purpose in the first place. Specifically, we focus on the pulse transit time (PTT) signal derived from the electrocardiogram (ECG) and photoplethysmography (PPG). We identify a calibration problem and the artifact it produces. We analyzed two databases collected passively during patient care in a hospital environment. In this paper, we provide an evidence confirming our hypothesis. To the best of our knowledge, this critical validation step in the work flow of any secondary (or even primary) analysis of data collected from clinical acquisition systems has not been reported, with relevance rising, particularly as more massively and passively collected databases become available. We hypothesize that this less discussed calibration issue for a secondary analysis will become an important source of artifacts in patient monitor data. For most online available databases, in general it is not consistently known which are suitable for which purposes, since the original clinical data acquisition device may not have been designed for the intended purpose of a secondary analysis and we do not have access to the device hardware or software details. Without a specific quantification of the underlying problem, the information we can extract from the waveform is limited. ![]() For example, while in the MIMIC III waveform database the inter-waveform alignment problem is mentioned, there is no specific quantification of it but only a description. Usually, less background information is available to the data analysts, which precludes a comprehensive judgement of the data quality. The calibration problem becomes more severe when we access the publicly available databases. Particularly, when multiple time series recorded from an off-the-shelf patient monitor are analyzed in the framework of sensor fusion, it is often implicitly assumed that on the device level the relationship between channels, such as synchronization, is not an issue. While there has been a lot of discussion about the artifact issues in patient monitoring data, if and how the data is calibrated is often not discussed and, rather, implicitly assumed when collecting and analyzing data acquired from clinical monitors. While using clinical monitors as scientific instrument has been questioned, in our era of medical big data research, we rely on clinical monitors, such as patient vital signs monitors or Holter ECG, heavier than ever before to collect as much data as possible in the hospital research setting for the data analysis purposes. By calibration, we mean the validity of the signal source and checking if the signal is correctly recorded for the specific purpose. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist.Ĭalibration is one of the most important initial steps in any signal acquisition and experiment-the data collection equipment, or the quality of the data, needs to be calibrated before a meaningful data analysis can take place. MGF gratefully acknowledges funding support from the Canadian Institutes of Health Research (CIHR #1). This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: Data underlying the study are shared in the Harvard Dataverse ( ).įunding: The work of YTL was supported by the National Science and Technology Development Fund (MOST 106-2115-M-075-001) of Ministry of Science and Technology, Taipei, Taiwan. Received: JAccepted: AugPublished: September 9, 2019Ĭopyright: © 2019 Lin et al. PLoS ONE 14(9):Įditor: Yan Li, Cleveland Clinic, UNITED STATES Citation: Lin Y-T, Lo Y-L, Lin C-Y, Frasch MG, Wu H-T (2019) Unexpected sawtooth artifact in beat-to-beat pulse transit time measured from patient monitor data.
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