Physiological measurement
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Physiological measurement · Feb 2015
Observational StudyPET(CO2) measurement and feature extraction of capnogram signals for extubation outcomes from mechanical ventilation.
Capnography is a continuous and noninvasive method for carbon dioxide (CO2) measurement, and it has become the standard of care for basic respiratory monitoring for intubated patients in the intensive care unit. In addition, it has been used to adjust ventilatory parameters during mechanical ventilation (MV). However, a substantial debate remains as to whether capnography is useful during the process of weaning and extubation from MV during the postoperative period. ⋯ The [Formula: see text] mean value for success and failure extubation group was 39.04 mmHg and 46.27 mmHg, respectively. It was also observed that high CO2 values in patients who had returned MV was 82.8 ± 21 mmHg at the time of extubation failure. Thus, [Formula: see text] measurements and analysis of features extracted from a capnogram can differentiate extubation outcomes in infant patients under MV, thereby reducing the physiologic instability caused by failure in this process.
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Physiological measurement · Dec 2014
Measuring dissimilarity between respiratory effort signals based on uniform scaling for sleep staging.
Polysomnography (PSG) has been extensively studied for sleep staging, where sleep stages are usually classified as wake, rapid-eye-movement (REM) sleep, or non-REM (NREM) sleep (including light and deep sleep). Respiratory information has been proven to correlate with autonomic nervous activity that is related to sleep stages. For example, it is known that the breathing rate and amplitude during NREM sleep, in particular during deep sleep, are steadier and more regular compared to periods of wakefulness that can be influenced by body movements, conscious control, or other external factors. ⋯ Experiments were conducted with a data set of 48 healthy subjects using a linear discriminant classifier and a ten-fold cross validation. It is revealed that this feature can help discriminate between sleep stages, but with an exception of separating wake and REM sleep. When combining the new feature with 26 existing respiratory features, we achieved a Cohen's Kappa coefficient of 0.48 for 3-stage classification (wake, REM sleep and NREM sleep) and of 0.41 for 4-stage classification (wake, REM sleep, light sleep and deep sleep), which outperform the results obtained without using this new feature.
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Physiological measurement · Dec 2014
Segmentation and classification of capnograms: application in respiratory variability analysis.
Variability analysis of respiratory waveforms has been shown to provide key insights into respiratory physiology and has been used successfully to predict clinical outcomes. The current standard for quality assessment of the capnogram signal relies on a visual analysis performed by an expert in order to identify waveform artifacts. Automated processing of capnograms is desirable in order to extract clinically useful features over extended periods of time in a patient monitoring environment. ⋯ Decision Tree, K-Nearest Neighbors (KNN) and Naive Bayes classifiers were close in terms of performance (AUC of 90%, 89% and 88% respectively), while using 7, 4 and 5 breath features, respectively. When compared to airflow derived timings, the 95% confidence interval on the mean difference in interbreath intervals was ± 0.18 s. This breath classification system provides a fast and robust pre-processing of continuous respiratory waveforms, thereby ensuring reliable variability analysis of breath-by-breath parameter time series.
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Physiological measurement · Dec 2014
Detection of motion artifact patterns in photoplethysmographic signals based on time and period domain analysis.
The presence of motion artifacts in photoplethysmographic (PPG) signals is one of the major obstacles in the extraction of reliable cardiovascular parameters in continuous monitoring applications. In the current paper we present an algorithm for motion artifact detection based on the analysis of the variations in the time and the period domain characteristics of the PPG signal. ⋯ The proposed method has been tested in healthy and cardiovascular diseased volunteers, considering 11 different motion artifact sources. The results achieved by the current algorithm (sensitivity--SE: 84.3%, specificity--SP: 91.5% and accuracy--ACC: 88.5%) show that the current methodology is able to identify both corrupted and clean PPG sections with high accuracy in both healthy (ACC: 87.5%) and cardiovascular diseases (ACC: 89.5%) context.
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Physiological measurement · Oct 2014
Obstructive sleep apnea-hypopnea results in significant variations in cerebral hemodynamics detected by diffuse optical spectroscopies.
The objective of this study was to adapt a novel near-infrared diffuse correlation spectroscopy (DCS) flow-oximeter for simultaneous and continuous monitoring of relative changes in cerebral blood flow (rCBF) and cerebral oxygenation (i.e. oxygenated/deoxygenated/total hemoglobin concentration: Δ[HbO2]/Δ[Hb]/ΔTHC) during overnight nocturnal polysomnography (NPSG) diagnostic test for obstructive sleep apnea-hypopnea (OSAH). A fiber-optic probe was fixed on subject's frontal head and connected to the DCS flow-oximeter through a custom-designed fiber-optic connector, which allowed us to easily connect/detach the optical probe from the device when the subject went to bathroom. To minimize the disturbance to the subject, the DCS flow-oximeter was remotely operated by a desktop located in the control room. ⋯ Moreover, the degrees of variations in all measured cerebral variables were significantly correlated with the severity of OSAH as determined by the apnea-hypopnea index (AHI), demonstrating the OSAH influence on both CBF and cerebral oxygenation. Large variations in arterial blood oxygen saturation (SaO2) were also found during OSAH. Since frequent variations/disturbances in cerebral hemodynamics may adversely impact brain function, future study will investigate the correlations between these cerebral variations and functional impairments for better understanding of OSAH pathophysiology.