title: Using time-frequency analysis of the photoplethysmographic waveform to detect the withdrawal of 900 mL of blood.
abstract: BACKGROUND
  We designed this study to determine if 900 mL of blood withdrawal during spontaneous breathing in healthy volunteers could be detected by examining the time-varying spectral amplitude of the photoplethysmographic (PPG) waveform in the heart rate frequency band and/or in the breathing rate frequency band before significant changes occurred in heart rate or arterial blood pressure. We also identified the best PPG probe site for early detection of blood volume loss by testing ear, finger, and forehead sites.
  
  
  METHODS
  Eight subjects had 900 mL of blood withdrawn followed by reinfusion of 900 mL of blood. Physiological monitoring included PPG waveforms from ear, finger, and forehead probe sites, standard electrocardiogram, and standard blood pressure cuff measurements. The time-varying amplitude sequences in the heart rate frequency band and breathing rate frequency band present in the PPG waveform were extracted from high-resolution time-frequency spectra. These amplitudes were used as a parameter for blood loss detection.
  
  
  RESULTS
  Heart rate and arterial blood pressure did not significantly change during the protocol. Using time-frequency analysis of the PPG waveform from ear, finger, and forehead probe sites, the amplitude signal extracted at the frequency corresponding to the heart rate significantly decreased when 900 mL of blood was withdrawn, relative to baseline (all P < 0.05); for the ear, the corresponding signal decreased when only 300 mL of blood was withdrawn. The mean percent decrease in the amplitude of the heart rate component at 900 mL blood loss relative to baseline was 45.2% (38.2%), 42.0% (29.2%), and 42.3% (30.5%) for ear, finger, and forehead probe sites, respectively, with the lower 95% confidence limit shown in parentheses. After 900 mL blood reinfusion, the amplitude signal at the heart rate frequency showed a recovery towards baseline. There was a clear separation of amplitude values at the heart rate frequency between baseline and 900 mL blood withdrawal. Specificity and sensitivity were both found to be 87.5% with 95% confidence intervals (47.4%, 99.7%) for ear PPG signals for a chosen threshold value that was optimized to separate the 2 clusters of amplitude values (baseline and blood loss) at the heart rate frequency. Meanwhile, no significant changes in the spectral amplitude in the frequency band corresponding to respiration were found.
  
  
  CONCLUSIONS
  A time-frequency spectral method detected blood loss in spontaneously breathing subjects before the onset of significant changes in heart rate or blood pressure. Spectral amplitudes at the heart rate frequency band were found to significantly decrease during blood loss in spontaneously breathing subjects, whereas those at the breathing rate frequency band did not significantly change. This technique may serve as a valuable tool in intraoperative and trauma settings to detect and monitor hemorrhage.
authors.affiliation: Department of Biomedical Engineering, 100 Institute Rd., Worcester Polytechnic Institute, Worcester, MA 01609, USA.
authors.forename: Christopher G
authors.initials: CG
authors.lastname: Scully
authors.forename: Nandakumar
authors.initials: N
authors.lastname: Selvaraj
authors.forename: Frederick W
authors.initials: FW
authors.lastname: Romberg
authors.forename: Richa
authors.initials: R
authors.lastname: Wardhan
authors.forename: John
authors.initials: J
authors.lastname: Ryan
authors.forename: John P
authors.initials: JP
authors.lastname: Florian
authors.forename: David G
authors.initials: DG
authors.lastname: Silverman
authors.forename: Kirk H
authors.initials: KH
authors.lastname: Shelley
authors.forename: Ki H
authors.initials: KH
authors.lastname: Chon
mesh_terms: D000328:Adult; D001794:Blood Pressure; D001795:Blood Pressure Determination; D001804:Blood Transfusion, Autologous; D001810:Blood Volume; D001811:Blood Volume Determination / Q000379:methods*; D016000:Cluster Analysis; D003237:Connecticut; D004562:Electrocardiography; D006339:Heart Rate; D006801:Humans; D020896:Hypovolemia / Q000175:diagnosis* / Q000503:physiopathology; D007259:Infrared Rays; D008297:Male; D017156:Photoplethysmography; D011237:Predictive Value of Tests; D015656:Respiratory Mechanics; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors