Signal quality estimation with multichannel adaptive filtering in intensive care settings.
A signal quality estimate of a physiological waveform can be an important initial step for automated processing of real-world data. This paper presents a new generic point-by-point signal quality index (SQI) based on adaptive multichannel prediction that does not rely on ad hoc morphological feature extraction from the target waveform. An application of this new SQI to photoplethysmograms (PPG), arterial blood pressure (ABP) measurements, and ECG showed that the SQI is monotonically related to signal-to-noise ratio (simulated by adding white Gaussian noise) and to subjective human quality assessment of 1361 multichannel waveform epochs. A receiver-operating-characteristic (ROC) curve analysis, with the human "bad" quality label as positive and the "good" quality label as negative, yielded areas under the ROC curve of 0.86 (PPG), 0.82 (ABP), and 0.68 (ECG).
Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA. ikaro@mit.edu
Ikaro
I
Silva
Joon
J
Lee
Roger G
RG
Mark
D062186:Arterial Pressure; D003422:Critical Care; D004562:Electrocardiography / Q000295:instrumentation; D006801:Humans; D008991:Monitoring, Physiologic; D017156:Photoplethysmography / Q000295:instrumentation; D012372:ROC Curve; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D059629:Signal-To-Noise Ratio; D058067:Wavelet Analysis