Short-term Heart Rate Turbulence Analysis Versus Variability and Baroreceptor Sensitivity in Patients With Dilated Cardiomyopathy

New methods for the analysis of arrhythmias and their hemodynamic consequences have been applied in risk stratification, in particular to patients after myocardial infarction. This study investigates the suitability of short-term heart rate turbulence (HRT) analysis in comparison to heart rate and blood pressure variability as well as baroreceptor sensitivity analyses to characterise the regulatory differences between patients with dilated cardiomyopathy (DCM) and healthy controls. In this study, 30 minutes data of non-invasive continuous blood pressure and ECGs of 37 DCM patients and 167 controls measured under standard resting conditions were analysed. The results show highly significant differences between DCM patients and controls in heart rate and blood pressure variability as well as in baroreceptor sensitivity parameters. Applying a combined heart rate-blood pressure trigger, ventricular premature beats were detected in 24.3% (9) of the DCM patients and 11.3% (19) of the controls. This fact demonstrates the limited applicability of short-term HRT analyses. However, the HRT parameters showed significant differences in this subgroup with ventricular premature beats (turbulence onset: DCM: 1.80±2.72, controls: - 4.34±3.10, p<0.001; turbulence slope: DCM: 6.75±5.50, controls: 21.30±17.72, p=0.021). Considering all (including HRT) parameters in the subgroup with ventricular beats, a discrimination rate between DCM patients and controls of 88.0% was obtained (max. 6 parameters). The corresponding value obtained for the total group was 86.3% (without HRT parameters). Comparable classification rates and high correlations between heart rate turbulence and variability and baroreflex parameters point to a more universal applicability of the latter methods

Optimal color channel combination across skin tones for remote heart rate measurement in camera-based photoplethysmography

Objective: The heart rate is an essential vital sign that can be measured remotely with camera-based photoplethysmography (cbPPG). Systems for cbPPG typically use cameras that deliver red, green, and blue (RGB) channels. The combination of these channels has been proven to increase signal-to-noise ratio (SNR) and heart rate measurement accuracy (ACC). However, many combinations remain untested, the comparison of proposed combinations on large datasets is insufficiently investigated, and the interplay with skin tone is rarely addressed. Methods: Eight regions of interest and eight color spaces with a total of 25 color channels were compared in terms of ACC and SNR based on the Binghamton-Pittsburgh-RPI Multimodal Spontaneous Emotion Database (BP4D+). Additionally, two systematic grid searches were performed to evaluate ACC in the space of linear combinations of the RGB channels. Results: Glabella and forehead regions of interest provided highest ACC (up to 74.1 %) and SNR (> -3 dB) with the hue channel H from HSV color space and the chrominance channel Q from NTSC color space. The grid searches revealed a global optimum of linear RGB combinations (ACC: 79.2 %). This optimum occurred for all skin tones, although ACC dropped for darker skin tones. Conclusion: Through systematic grid searches we were able to identify the skin tone independent optimal linear RGB color combination for measuring heart rate with cbPPG. Our results proved on a large dataset that the identified optimum outperformed conventionally used color channels. Significance: The presented findings provide useful evidence for future considerations of algorithmic approaches for cbPPG

T Wave Amplitude Correction of QT Interval Variability for Improved Repolarization Lability Measurement

Objectives: The inverse relationship between QT interval variability (QTV) and T wave amplitude potentially confounds QT variability assessment. We quantified the influence of the T wave amplitude on QTV in a comprehensive dataset and devised a correction formula. Methods: Three ECG datasets of healthy subjects were analyzed to model the relationship between T wave amplitude and QTV. To derive a generally valid correction formula, linear regression analysis was used. The proposed correction formula was applied to patients enrolled in the Evaluation of Defibrillator in Non-Ischemic Cardiomyopathy Treatment Evaluation trial (DEFINITE) to assess the prognostic significance of QTV for all-cause mortality in patients with non-ischemic dilated cardiomyopathy. Results: A strong inverse relationship between T wave amplitude and QTV was demonstrated, both in healthy subjects (R2 = 0.68, p < 0.001) and DEFINITE patients (R2 = 0.20, p < 0.001). Applying the T wave amplitude correction to QTV achieved 2.5-times better group discrimination between patients enrolled in the DEFINITE study and healthy subjects. Kaplan-Meier estimator analysis showed that T wave amplitude corrected QTVi is inversely related to survival (p < 0.01) and a significant predictor of all-cause mortality. Conclusion: We have proposed a simple correction formula for improved QTV assessment. Using this correction, predictive value of QTV for all-cause mortality in patients with non-ischemic cardiomyopathy has been demonstrated

Spatio-temporal analysis of blood perfusion by imaging photoplethysmography

Imaging photoplethysmography (iPPG) has attracted much attention over the last years. The vast majority of works focuses on methods to reliably extract the heart rate from videos. Only a few works addressed iPPGs ability to exploit spatio-temporal perfusion pattern to derive further diagnostic statements. This work directs at the spatio-temporal analysis of blood perfusion from videos. We present a novel algorithm that bases on the two-dimensional representation of the blood pulsation (perfusion map). The basic idea behind the proposed algorithm consists of a pairwise estimation of time delays between photoplethysmographic signals of spatially separated regions. The probabilistic approach yields a parameter denoted as perfusion speed. We compare the perfusion speed versus two parameters, which assess the strength of blood pulsation (perfusion strength and signal to noise ratio). Preliminary results using video data with different physiological stimuli (cold pressure test, cold face test) show that all measures are in fluenced by those stimuli (some of them with statistical certainty). The perfusion speed turned out to be more sensitive than the other measures in some cases. However, our results also show that the intraindividual stability and interindividual comparability of all used measures remain critical points. This work proves the general feasibility of employing the perfusion speed as novel iPPG quantity. Future studies will address open points like the handling of ballistocardiographic effects and will try to deepen the understanding of the predominant physiological mechanisms and their relation to the algorithmic performance

Challenges to QT Interval Variability Analysis in Mobile Applications

The QT interval in an electrocardiogram (ECG) reflects complex processes affecting the repolarization of ventricular myocardium. Increased QT interval variability (QTV) is thought to be caused by ventricular repolarization lability and has been associated with cardiac mortality. Recent publications have shown that template-based methods are more robust than traditional methods for QT interval extraction on a beat-to-beat basis. However, most studies are limited to non-movement ECG recordings, we want to analyze in this study the power of QT interval extraction for mobile non-stationary ECG recordings. The records of 7 test subjects are at least 65 min long and contain about 25 minutes of sport exercise such as running, cycling, sport climbing or acrobatic training. 2DSW was used to extract QT interval and best-fit distance of matched template for signal quality evaluation for each beat. Potential relations between QTV, motion and signal quality are segmentally compared. To determine motion activity we calculated normalized signal magnitude area (SMA). QTV was increased in patients during sport exercise, possibly reflects sympathetic activity in these specific physiological conditions. However, increased QTV could also be caused by low signal quality

The effect of body posture on cognitive performance: a question of sleep quality

Nearly all functional magnetic resonance imaging (fMRI) studies are conducted in the supine body posture, which has been discussed as a potential confounder of such examinations. The literature suggests that cognitive functions, such as problem solving or perception, differ between supine and upright postures. However, the effect of posture on many cognitive functions is still unknown. Therefore, the aim of the present study was to investigate the effects of body posture (supine vs. sitting) on one of the most frequently used paradigms in the cognitive sciences: the N-back working memory paradigm. Twenty-two subjects were investigated in a randomized within-subject design. Subjects performed the N-back task on two consecutive days in either the supine or the upright posture. Subjective sleep quality and chronic stress were recorded as covariates. Furthermore, changes in mood dimensions and heart rate variability (HRV) were assessed during the experiment. Results indicate that the quality of sleep strongly affects reaction times when subjects performed a working memory task in a supine posture. These effects, however, could not be observed in the sitting position. The findings can be explained by HRV parameters that indicated differences in autonomic regulation in the upright vs. the supine posture. The finding is of particular relevance for fMRI group comparisons when group differences in sleep quality cannot be ruled out