Chern-Pin Chua

Continuous Blood Pressure Monitoring using ECG and Finger Photoplethysmogram

Pulse arrival time and the amplitude of the finger photoplethysmogram were used to track blood pressure continuously over 10-minute intervals. The measures were recorded with a holter-oximeter from a sample of 8 young, healthy human subjects in the supine and standing positions. Results indicate that, with individual calibration, systolic and diastolic blood pressure can be estimated with an average error of plusmn6 and plusmn4 mmHg respectively. Using pulse arrival time in combination with the amplitude of the finger photoplethysmogram gave better results than using any one alone, with PPG amplitude appearing to be more robust

Combined electrocardiogram and photoplethysmogram measurements as an indicator of objective sleepiness

There is considerable interest in unobtrusive and portable methods of monitoring sleepiness outside the laboratory setting. This study evaluates the usefulness of combined electrocardiogram (ECG) and photoplethysmogram (PPG) measurements for estimating psychomotor vigilance. The psychomotor vigilance test (PVT) was performed at various points over the course of a day, and one channel each of ECG and PPG was recorded simultaneously. Features derived from ECG and PPG were entered into multiple linear regression models to estimate PVT values. A double-loop, subject-independent validation scheme was used to develop and validate the models. We show that features obtained from the RR interval were reasonably useful for estimating absolute PVT levels, but were somewhat inadequate for estimating within-subject PVT changes. Combined ECG and PPG measurements appear to be useful for predicting PVT values, and deserve further investigation for portable sleepiness monitoring.

Pulse transit time-derived respiratory parameters and their variability across sleep stages

We considered the capability of pulse transit time (PTT) to provide respiratory information in obstructive sleep apnea (OSA) patients. PTT-derived respiratory frequency was quite well correlated with that derived from inductance plethysmography, with amplitude slightly less so. The PTT-derived respiratory estimates were also used to distinguish sleep stage. In some subjects, statistically significant differences in respiratory parameters were observed between wake, REM, and stage 2 sleep, but this effect was highly subject dependent

Towards Automated Sleep State Estimation using a Holter-Oximeter

Single-channel ECG and linger photoplethysmogram were used to estimate sleep states in obstructive sleep apnea patients. Overnight Holter-oximeter recordings from 14 subjects with suspected sleep apnea were analysed. Parameters including the RR interval, photoplethysmogram amplitude and rise time, and pulse arrival time were characterised and a hidden Markov model classifier used to identify wake, REM and sleep states. An overall accuracy of 77% and Cohens kappa of 0.54 was achieved, establishing a baseline level of usefulness for sleep state estimation using a Holter-oximeter. Autonomic arousals detected using pulse arrival time also appeared to be strongly correlated with Epworth Sleepiness Scale scores.