Adaptive blood pressure estimation from wearable PPG sensors using peripheral artery pulse wave velocity measurements and multi-channel blind identification of local arterial dynamics.
A method for estimating pulse wave velocity (PWV) using circulatory waveform signals derived from multiple photoplethysmograph (PPG) sensors is described. The method employs two wearable in-line PPG sensors placed at a known distance from one another at the ulnar and digital artery. A technique for calibrating the measured pulse wave velocity to arterial blood pressure using hydrostatic pressure variation is presented. Additionally, a framework is described for estimating local arterial dynamics using PPG waveforms and multi-channel blind system ID. Initial results implementing the method on data derived from a human subject at different arterial pressures is presented. Results show that the method is capable of measuring the changes in arterial PWV that result from fluctuations in mean arterial pressure.
McCombie
Devin B
DB
Massachusetts Inst. of Technol., Cambridge, MA 02139, USA. mccombie@mit.edu
Reisner
Andrew T
AT
Asada
H Harry
HH
D001158:Arteries / Q000502:physiology*; D001698:Biomedical Engineering; D001794:Blood Pressure / Q000502:physiology; D018660:Blood Pressure Monitoring, Ambulatory / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data; D004867:Equipment Design; D006439:Hemodynamics; D006801:Humans; D006973:Hypertension / Q000175:diagnosis / Q000503:physiopathology; D008955:Models, Cardiovascular; D015233:Models, Statistical; D017156:Photoplethysmography / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data; D012815:Signal Processing, Computer-Assisted; D017535:Ulnar Artery / Q000502:physiology