Physiological measurement
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Physiological measurement · Apr 2019
Posture effects on the calibratability of remote pulse oximetry in visible light.
Remote pulse oximetry in visible light (VIS) is a relevant application of photoplethysmography (PPG). However, wavelengths penetrate at different depths and VIS-based pulse oximetry may not guarantee robustness to physiological variations of the skin properties. This paper shows how a simple manoeuver like a posture change can hamper the accuracy of a method relying on red and the less penetrating green wavelengths. ⋯ Our results show that the calibrations for remote pulse oximetry in VIS require the specification of a fixed measurement position. Future work could be aimed at controlling for posture in measurements.
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Physiological measurement · Mar 2019
Predicting forced vital capacity (FVC) using support vector regression (SVR).
Spirometry, as the gold standard approach in the diagnosis of chronic obstructive pulmonary disease (COPD), has strict end of test (EOT) criteria (e.g. complete exhalation), which cannot be met by patients with compromised health states. Thus, significant parameters measured by spirometry, such as forced vital capacity (FVC), have limited accuracies. To address this issue, the present study aimed to develop models based on support vector regression (SVR) to predict values of FVC under the condition that the EOT criteria were not fully met. ⋯ Our study shows the possibility of predicting FVC with acceptable precision in cases where the EOT criteria of spirometry were not fully met, which can be beneficial for patients who cannot or did not achieve full exhalation in spirometry.
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Physiological measurement · Jan 2019
LetterContinuous monitoring of cerebrovascular reactivity through pulse transit time and intracranial pressure.
Cerebrovascular reactivity (CR) is a mechanism that maintains stable blood flow supply to the brain. Pressure reactivity index (PRx), the correlation coefficient between slow waves of invasive arterial blood pressure (ABP) and intracranial pressure (ICP) has been validated for CR assessment. However, in clinical ward, not every subarachnoid hemorrhage (SAH) patient has invasive ABP monitoring. Pulse transit time (PTT), the propagation time of a pulse wave travelling from the heart to peripheral arteries, has been suggested as a surrogate measure of ABP. In this study, we proposed to use PTT instead of invasive ABP to monitor CR. ⋯ PTT demonstrates great potential as a useful tool for CR assessment when invasive ABP is unavailable. Key points • Pulse transit time (PTT), defined as the propagation time of a pulse wave travelling from the heart to the peripheral arteries, has been proposed as a surrogate measure of ABP. The relationship between PTT and ABP in SAH patients remains unknown. • Cerebrovascular reactivity (CR) assessment through PTT has advantages over invasive ABP, as it avoids bleeding and infection risk, and can be used outside of the ICU. • We introduced a new method to assess CR using PTT and ICP through correlation based method and wavelet based method. • We found that beat-to-beat PTT was negatively related with invasive ABP in SAH patients. A significant linear relationship exists between PTT-based CR parameter and a well validated method, PRx. PTT demonstrates great potential as a useful tool for CR assessment when invasive ABP is unavailable in SAH patients.
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Physiological measurement · Nov 2018
Efficient sleep classification based on entropy features and a support vector machine classifier.
Sleep quality helps to reflect on the physical and mental condition, and efficient sleep stage scoring promises considerable advantages to health care. The aim of this study is to propose a simple and efficient sleep classification method based on entropy features and a support vector machine classifier, named SC-En&SVM. ⋯ We propose a novel sleep stage scoring method, SC-En&SVM, with easily accessible features and a simple classification algorithm, without reducing the classification performance compared with other approaches.
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Physiological measurement · Sep 2018
Ranking of the most reliable beat morphology and heart rate variability features for the detection of atrial fibrillation in short single-lead ECG.
This study participated in the 2017 PhysioNet/CinC Challenge dedicated to the classification of atrial fibrillation (AF), normal sinus rhythm (Normal), other arrhythmia (Other) and strong noise, using single-lead electrocardiogram (ECG) recordings with a duration <60 s. The aim is to apply a linear threshold-based strategy for arrhythmia classification, ranking the most powerful time domain ECG features that could be easily reproduced on any platform. ⋯ The top five features, which together contributed to about 94% of the maximal F1 score were ranked: (1) proportion of RR intervals differing by >50 ms from the preceding RR interval; (2) Poincaré plot geometry estimated by the ratio of the minor-to-major semi-axes of the fitted ellipse; (3) P-wave presence in the average beat; (4) mean percentage of the RR interval first differences; and (5) mean correlation of all beats against the average beat. The global rank of feature extraction methods highlighted that HRV alone was able to provide 92.5% of the maximal F1 score (0.74 versus 0.8). The added value of more complex ECG morphology analysis was less significant for Normal, AF, and Other rhythms (+0.02 to 0.08 points) than for Noise (+0.19 points); however, these were indispensable for wearable ECG recording devices with frequent artefact disturbance.