IEEE transactions on bio-medical engineering
-
IEEE Trans Biomed Eng · May 2010
Comparative StudyEstimation of respiratory rate from ECG, photoplethysmogram, and piezoelectric pulse transducer signals: a comparative study of time-frequency methods.
We compare the performance of two different time-frequency-based breathing rate (BR) detection algorithms when used on three different physiological signals: the ECG, the photoplethysmogram (PPG), and the piezoelectric pulse transducer (PZO) signal. Studies carried out over the past have shown the existence of amplitude and/or FMs due to respiration in physiological signals, such as those mentioned. In a recent study, we analyzed the PPG signal and detected the FM and amplitude modulation effect that controlled breathing had on it, and inferred the rate of respiration using the time-frequency spectrum (TFS) (via a wavelet (WT) or complex demodulation (CDM) approach). ⋯ We now explore the possibility of using these methods on the ECG and the finger PZO signal, of which only the former has been previously used with some success to derive BR. Testing performed on 15 healthy human subjects for a range of BR and two body positions showed that though the PPG signal gave the most consistently high performance, the ECG and PZO also proved to be reasonably accurate over longer time segments. Furthermore, the CDM approach was on average either better than or comparable to the WT method in terms of both accuracy and repeatability of the detection.
-
IEEE Trans Biomed Eng · May 2010
Forecasting ICP elevation based on prescient changes of intracranial pressure waveform morphology.
Interventions of intracranial pressure (ICP) elevation in neurocritical care is currently delivered only after healthcare professionals notice sustained and significant mean ICP elevation. This paper uses the morphological clustering and analysis of ICP (MOCAIP) algorithm to derive 24 metrics characterizing morphology of ICP pulses and test the hypothesis that preintracranial hypertension (Pre-IH) segments of ICP can be differentiated, using these morphological metrics, from control segments that were not associated with any ICP elevation or at least 1 h prior to ICP elevation. Furthermore, we investigate whether a global optimization algorithm could effectively find the optimal subset of these morphological metrics to achieve better classification performance as compared to using full set of MOCAIP metrics. ⋯ While the sensitivity decreased to 21% for Pre-IH segments, 20 min prior to ICP elevation, the high specificity of 99% was retained. The performance using the full set of MOCAIP metrics was shown inferior to results achieved using the optimal subset of metrics. This paper demonstrated that advanced ICP pulse analysis combined with machine learning could potentially leads to the forecasting of ICP elevation so that a proactive ICP management could be realized based on these accurate forecasts.
-
IEEE Trans Biomed Eng · May 2010
PTT variability for discrimination of sleep apnea related decreases in the amplitude fluctuations of PPG signal in children.
In this paper, an analysis of pulse transit time variability (PTTV) during decreases in the amplitude fluctuations of pulse photoplethysmography signal (PPG) (DAP) events for obstructive sleep apnea syndrome (OSAS) screening is presented. The temporal evolution of time-frequency PTTV parameters during DAP was analyzed. The results show an increase in the sympathetic activity index low-frequency component (LF) during DAP for PTTV (85%) significantly higher than for heart rate variability (HRV) (33%), (p < 10(-13)). ⋯ The ratio of DAP events per hour r (DAP), the ratio after filtering based on HRV indexes r (HRV) (DAP), or on PTTV indexes r (PTTV) (DAP), were computed. The results show an accuracy of 75% for r (PTTV) (DAP) (14% increase with respect to r (DAP) and 5% increase with respect to r (HRV) (DAP)), a sensitivity of 81.8%, and a specificity of 73.9% when classifying 1-h polysomnographic excerpts as OSAS or normal. These results suggest that the combination of DAP and PTTV could be better alternative for sleep apnea screening using PPG with the added benefit of its low cost and simplicity.
-
IEEE Trans Biomed Eng · May 2010
Attractor structure discriminates sleep states: recurrence plot analysis applied to infant breathing patterns.
Breathing patterns are characteristically different between infant active sleep (AS) and quiet sleep (QS), and statistical quantifications of interbreath interval (IBI) data have previously been used to discriminate between infant sleep states. It has also been identified that breathing patterns are governed by a nonlinear controller. This study aims to investigate whether nonlinear quantifications of infant IBI data are characteristically different between AS and QS, and whether they may be used to discriminate between these infant sleep states. ⋯ When a threshold classifier was trained, the RQA variable recurrence was able to correctly classify 94.3% of periods in a test dataset. It was concluded that RQA of IBI data is able to accurately discriminate between infant sleep states. This is a promising step toward development of a minimal-channel automatic sleep state classification system.