  Recent research has shown that each apnea episode results in a significant
rise in the beat-to-beat blood pressure and by a drop to the pre-episode levels
when patient resumes normal breathing. While the physiological implications of
these repetitive and significant oscillations are still unknown, it is of
interest to quantify them. Since current array of instruments deployed for
polysomnography studies does not include beat-to-beat measurement of blood
pressure, but includes oximetry, it is both of clinical interest to estimate
the magnitude of BP oscillations from the photoplethysmography (PPG) signal
that is readily available from sleep lab oximeters. We have investigated a new
method for continuous estimation of systolic (SBP), diastolic (DBP), and mean
(MBP) blood pressure waveforms from PPG. Peaks and troughs of PPG waveform are
used as input to a 5th order autoregressive moving average model to construct
estimates of SBP, DBP, and MBP waveforms. Since breath hold maneuvers are shown
to simulate apnea episodes faithfully, we evaluated the performance of the
proposed method in 7 subjects (4 F; 32+-4 yrs., BMI 24.57+-3.87 kg/m2) in
supine position doing 5 breath maneuvers with 90s of normal breathing between
them. The modeling error ranges were (all units are in mmHg) -0.88+-4.87 to
-2.19+-5.73 (SBP); 0.29+-2.39 to -0.97+-3.83 (DBP); and -0.42+-2.64 to
-1.17+-3.82 (MBP). The cross validation error ranges were 0.28+-6.45 to
-1.74+-6.55 (SBP); 0.09+-3.37 to -0.97+-3.67 (DBP); and 0.33+-4.34 to
-0.87+-4.42 (MBP). The level of estimation error in, as measured by the root
mean squared of the model residuals, was less than 7 mmHg
