Screening for Peripheral Vascular Stiffness in Lipedema Patients by Automatic Electrocardiogram-Based Oscillometric Detection.

Body mass index (BMI) is seen as a predictor of cardiovascular disease (CVD) in lipedema patients. A valid predictor of CVD is increased aortic stiffness (IAS), and previous research described IAS in lipedema. However, it is not known if this applies to all patients. In this cross-sectional single-center cohort study, peripheral pulse wave velocity (PWV) as a non-invasive indicator of aortic stiffness was measured in 41 patients with lipedema, irrespective of stage and without pre-existing cardiovascular conditions or a history of smoking and a maximum body mass index (BMI) of 35 kg/m2. Automatically electrocardiogram-triggered oscillometric sensor technology by the Gesenius-Keller method was used. Regardless of the stage of lipedema disease, there was no significant difference in PWV compared to published standard values adjusted to age and blood pressure. BMI alone is not a predictor of cardiovascular risk in lipedema patients. Measuring other anthropometric factors, such as the waist-hip ratio or waist-height ratio, should be included, and the existing cardiovascular risk factors, comorbidities, and adipose tissue distribution for accurate risk stratification should be taken into account. Automated sensor technology recording the PWV represents a valid and reliable method for health monitoring and early detection of cardiovascular risks.

Automatic ECG-based detection of left ventricular hypertrophy and its predictive value in haemodialysis patients.

Objective.Left ventricular hypertrophy (LVH) is one of the most severe risk factors in patients with end-stage kidney disease (ESKD) regarding all-cause and cardiovascular mortality. It contributes to the risk of sudden cardiac death which accounts for approximately 25% of deaths in ESKD patients. Electrocardiography (ECG) is the least expensive way to assess whether a patient has LVH, but manual annotation is cumbersome. Thus, an automated approach has been developed to derive ECG-based LVH parameters. The aim of the current study is to compare automatic to manual measurements and to investigate their predictive value for cardiovascular and all-cause mortality.Approach.From the 12-lead 24 h ECG measurements of 301 ESKD patients undergoing haemodialysis, three different LVH parameters were calculated. Peguero-Lo Presti voltage, Cornell voltage, and Sokolow-Lyon voltage were automatically derived and compared to the manual annotations. To determine the agreement between manual and automatic measurements and their predictive value, Bland-Altman plots were created and Cox regression analysis for cardiovascular and all-cause mortality was performed.Main results.The median values for the automatic assessment were: Peguero-Lo Presti voltage 1.76 mV (IQR 1.29-2.55), Cornell voltage 1.14 mV (IQR 0.721-1.66), and Sokolow-Lyon voltage 1.66 mV (IQR 1.08-2.23). The mean differences when compared to the manual measurements were -0.027 mV (0.21 SD), 0.027 mV (0.13 SD) and -0.025 mV (0.24 SD) for Peguero-Lo Presti, Cornell, and Sokolow-Lyon voltage, respectively. The categorial LVH detection based on pre-defined thresholds differed in only 13 cases for all indices between manual and automatic assessment. Proportional hazard ratios only differed slightly in categorial LVH detection between manually and automatically determined LVH parameters; no differences could be found for continuous parameters.Significance.This study provides evidence that automatic algorithms can be as reliable in LVH parameter assessment and risk prediction as manual measurements in ESKD patients undergoing haemodialysis.

Handheld Device Measures Cardiovascular Effects of Cognitive and Physical Stress.

Stress is an increasing burden for our society and related to cardiovascular (CV) parameters and diseases. Effects of mental or physical stress were observed in CV parameters during task completion and recovery. These effects were measured using a novel handheld device, which can be incorporated in mHealth solutions.

Device-guided slow breathing with direct biofeedback of pulse wave velocity - acute effects on pulse arrival time and self-measured blood pressure.

BACKGROUND: There isevidence that device-guided slow breathing using biofeedback acutely reduces blood pressure (BP) and pulse wave velocity [i.e. increased pulse arrival time (PAT)]. OBJECTIVES: The objectives of the study presented here were to test whether the results of changes observed in PAT in earlier studies are reproducible over 1 week and how changes in pulse wave velocity/PAT translate into absolute self-measured BP changes. METHODS: Patients with a systolic BP 130-160 mmHg or treated essential hypertension (21 females/23 males) were trained to perform unattended device-guided slow breathing exercises for 10 min daily over 5 days. Furthermore, they were skilled to perform self-measurement of BP before and after the breathing exercise using a validated upper-arm device. RESULTS: Office BP at screening [median (1, 3. Q)] was 137 (132, 142)/83 (79, 87) mmHg. We observed a significant ( P < 0.05) increase in PAT of 5 ms (SD 12.5 ms) on average after 10 min of guided breathing and an additional 1 ms ( P < 0.05, SD 8 ms) during the following 5 min of spontaneous breathing compared to baseline. PAT before the exercise remained constant over 5 days paralleled by constant self-measured BP before the exercise. Device-guided breathing was associated with a significant reduction of self-measured SBP of 5 mmHg ( P < 0.01, SD 8 mmHg). Data furthermore demonstrated that these changes were highly reproducible over 1 week. CONCLUSIONS: Device-guided slow breathing and biofeedback lead to reproducible and favorable changes (increase) in PAT and SBP (decrease).

Attractor Reconstruction for Quantifying the Arterial Pulse Wave Morphology During Device-Guided Slow Breathing.

Attractor reconstruction is a new way to quantify the morphology of a cardiovascular waveform by plotting all data points in the three-dimensional phase space, generating a trajectory of overlapping loops. The aim of this study is to show the feasibility of an automatic approach to quantify pulse wave attractors from a device-guided breathing study, and to link attractor features to pulse waveform features. The recently developed feature extraction technique is applied to arterial pulse waveform data of 30 patients with treated hypertension. The patients performed a device-guided slow breathing exercise. The generated attractors were categorized into three different shapes: triangular attractors, bent attractors and attractors with overlapping arms. The average height of the attractors continuously and progressively dropped from 41.8 [35.4, 55.1] AU to 34.5 [25.4, 47.3] AU (p < 0.001) during the breathing exercise. We have shown that the novel approach to quantify pulse wave attractors is feasible and can be used to detect changes in the morphology of arterial pulse waveforms. Device-guided slow breathing exercise has a shrinking effect on the average height of the attractors, which may indicate a reduction in blood pressure.

Impact of the COVID-19 lockdown on system usage of an innovative care support system and the mood of older adults.

BACKGROUND: Older age is a substantial risk factor for serious illness from COVID-19. Moreover, isolation and quarantine are more likely to cause physical, mental and social deprivation in older age. Information and Communication Tools are means to prevent such consequences. OBJECTIVE: This study aimed therefore to investigate the impact of the COVID-19 lockdown measures on the usage of an innovative technical support system deployed in Austria (AT) and Luxembourg (LU) consisting of several tools that allow independent living in older age. METHODS: Thirty-nine older adults (11 male; 28 female) with a mean age of 74.3 (SD 7.3) years were included in the study. In total, 18 older people were recruited in AT and 21 in LU. Descriptive statistics were computed, and longitudinal models were fitted for technology use and self-reported mood. RESULTS: The number of older adults using the system significantly decreased from the time before lockdown (39 [100%]) to during lockdown (26 [67%]) and thereafter (23 [59%]; p < 0.001). Multiple comparisons revealed a significant reduction in the average number of events for calendar and medication tools, but a substantial increase in communication and messaging events. Self-reported well-being declined during the lockdown and increased afterwards back to baseline levels. CONCLUSION: Communication was the main reason for using the support system. In addition, strategies and interventions are essential to support older adults when using information technology in the prolonged phases of the pandemic to sustain independent living. CLINICAL TRIAL REGISTRATION: The DAPAS protocol was published at www.researchgate.net. DOI: 10.13140/RG.2.2.24233.34401.

Assessing hemodynamics from the photoplethysmogram to gain insights into vascular age: a review from VascAgeNet.

The photoplethysmogram (PPG) signal is widely measured by clinical and consumer devices, and it is emerging as a potential tool for assessing vascular age. The shape and timing of the PPG pulse wave are both influenced by normal vascular aging, changes in arterial stiffness and blood pressure, and atherosclerosis. This review summarizes research into assessing vascular age from the PPG. Three categories of approaches are described: 1) those which use a single PPG signal (based on pulse wave analysis), 2) those which use multiple PPG signals (such as pulse transit time measurement), and 3) those which use PPG and other signals (such as pulse arrival time measurement). Evidence is then presented on the performance, repeatability and reproducibility, and clinical utility of PPG-derived parameters of vascular age. Finally, the review outlines key directions for future research to realize the full potential of photoplethysmography for assessing vascular age.

A comparison between left ventricular ejection time measurement methods during physiological changes induced by simulated microgravity.

NEW FINDINGS: What is the central question of this study? First, we validated easy-to-use oscillometric left ventricular ejection time (LVET) against echocardiographic LVET. Second, we investigated progression of left ventricular ejection time index (LVETI), pre-ejection period index (PEPI), total electromechanical systole index (QS2I) and PEP/LVET ratio during 60 days of head-down tilt (HDT). What is the main finding and its importance? The LVETosci and LVETecho showed good agreement in effect direction. Hence, LVETosci might be useful to evaluate cardiovascular responses during space flight. Moreover, the approach might be useful for individual follow-up of patients with altered ejection times. Furthermore, significant effects of 60 days of HDT were captured by measurements of LVETI, PEPI, QS2I and PEP/LVET ratio. ABSTRACT: Systolic time intervals that are easy to detect might be used as parameters reflecting cardiovascular deconditioning. We compared left ventricular ejection time (LVET) measured via ultrasound Doppler on the left ventricular outflow tract with oscillometrically measured LVET, measured at the brachialis. Furthermore, we assessed the progression of the left ventricular ejection time index (LVETI), the pre-ejection period index (PEPI), the Weissler index (PEP/LVET) and the total electromechanical systole index (QS2I) during prolonged strict head-down tilt (HDT) bed rest, including 16 male and eight female subjects. Simultaneous oscillometric and echocardiographic LVET measurements showed significant correlation (r = 0.53 with P = 0.0084 before bed rest and r = 0.73 with P < 0.05 on the last day of bed rest). The shortening of LVET during HDT bed rest measured with both approaches was highly concordant in their effect direction, with a concordance rate of 0.96. Our results also demonstrated a significant decrease of LVETI (P < 0.0001) and QS2I (P = 0.0992) and a prolongation of PEPI (P = 0.0049) and PEP/LVET (P = 0.0003) during HDT bed rest over 60 days. Four days after bed rest, LVETI recovered completely to its baseline value. Owing to the relationship between shortening of LVETI and heart failure progression, the easy-to-use oscillometric method might not only be a useful way to evaluate the cardiovascular system during space flights, but could also be of high value in a clinical setting.

Limited Effect of 60-Days Strict Head Down Tilt Bed Rest on Vascular Aging.

BACKGROUND: Cardiovascular risk may be increased in astronauts after long term space flights based on biomarkers indicating premature vascular aging. We tested the hypothesis that 60 days of strict 6° head down tilt bed rest (HDTBR), an established space analog, promotes vascular stiffening and that artificial gravity training ameliorates the response. METHODS: We studied 24 healthy participants (8 women, 24-55 years, BMI = 24.3 ± 2.1 kg/m2) before and at the end of 60 days HDTBR. 16 subjects were assigned to daily artificial gravity. We applied echocardiography to measure stroke volume and isovolumetric contraction time (ICT), calculated aortic compliance (stroke volume/aortic pulse pressure), and assessed aortic distensibility by MRI. Furthermore, we measured brachial-femoral pulse wave velocity (bfPWV) and pulse wave arrival times (PAT) in different vascular beds by blood pressure cuffs and photoplethysmography. We corrected PAT for ICT (cPAT). RESULTS: In the pooled sample, diastolic blood pressure (+8 ± 7 mmHg, p < 0.001), heart rate (+7 ± 9 bpm, p = 0.002) and ICT (+8 ± 13 ms, p = 0.036) increased during HDTBR. Stroke volume decreased by 14 ± 15 ml (p = 0.001). bfPWV, aortic compliance, aortic distensibility and all cPAT remained unchanged. Aortic area tended to increase (p = 0.05). None of the parameters showed significant interaction between HDTBR and artificial gravity training. CONCLUSION: 60 days HDTBR, while producing cardiovascular deconditioning and cephalad fluid shifts akin to weightlessness, did not worsen vascular stiffness. Artificial gravity training did not modulate the response.

Non-invasive quantification of the effect of device-guided slow breathing with direct feedback to the patient to reduce blood pressure.

OBJECTIVE: Slow breathing is a relaxation exercise recommended for lowering blood pressure (BP). Biofeedback may improve patient adherence and enhance BP lowering effects. Since the pulse arrival time (PAT) is inversely proportional to BP, it can be used to estimate BP changes. APPROACH: In this pilot study, 30 patients (age 62.9 (SD 7.7) years, 11 F/19 M, Sys. BP 133.0 (SD 17.1) mmHg, Dia. BP 83.8 (SD 10.6) mmHg) performed a device-guided slow breathing exercise. PAT was measured by ECG and plethysmography and immediately presented to the patient, and respiratory sinus arrhythmia (RSA) was calculated retrospectively to measure the adherence to the instructed respiratory rate. MAIN RESULTS: Respiratory rate was 13.6 (SD 1.9) bpm at baseline and 5.4 (SD 1.0) bpm during guided breathing. PAT continuously and progressively increased from 231.5 (SD 20.3) to 237.3 (SD 18.5) ms (p [Formula: see text] 0.001). The median deviation of RSA from the guided respiratory rate was 0.06 (IQR 0.19) bpm. In three patients, a deviation of > 0.20 bpm was detected, and two of them showed no increase in PAT. In total, 25 patients responded with increase in PAT. SIGNIFICANCE: In this pilot study we have shown that biofeedback of PAT and RSA are feasible and can further improve motivation and adherence. Furthermore, we have shown that the exercise increased PAT, which indicates a reduction in BP. Due to its ease of use, this method is ideal for home use and self-monitoring.

Measuring Arterial Stiffness in a Head-Down Tilt Bed Rest Study: A Multisensor Approach.

Arterial stiffness is an important indicator for vascular aging and an independent predictor for cardiovascular diseases. During space flights or simulated space flights by prolonged head-down tilt bed rest, major cardiovascular alterations occur. However, the changes in arterial stiffness are not fully understood yet. Thus, we aimed to develop a setup for the measurement of arterial stiffness during prolonged head-down tilt bed rest, which incorporates several combinations of biosignals and measurement locations for the determination of pulse transit times. By performing measurements using this setup on female and male subjects, we intend to deepen the understanding of changes in arterial stiffness during prolonged head-down tilt bed rest. This work describes and visualizes the complete setup as well as our measurement protocols and algorithms used. The result section shows the successful recording of baseline signals before the bed rest study and visualizes the synchronized recordings of pulse waves measured on different sides of the body. Thus, it is feasible to use the presented setup in bed rest studies.

Implementation and verification of an enhanced algorithm for the automatic computation of RR-interval series derived from 24 h 12-lead ECGs.

An important tool in early diagnosis of cardiac dysfunctions is the analysis of electrocardiograms (ECGs) obtained from ambulatory long-term recordings. Heart rate variability (HRV) analysis became a significant tool for assessing the cardiac health. The usefulness of HRV assessment for the prediction of cardiovascular events in end-stage renal disease patients was previously reported. The aim of this work is to verify an enhanced algorithm to obtain an RR-interval time series in a fully automated manner. The multi-lead corrected R-peaks of each ECG lead are used for RR-series computation and the algorithm is verified by a comparison with manually reviewed reference RR-time series. Twenty-four hour 12-lead ECG recordings of 339 end-stage renal disease patients from the ISAR (rISk strAtification in end-stage Renal disease) study were used. Seven universal indicators were calculated to allow for a generalization of the comparison results. The median score of the indicator of synchronization, i.e. intraclass correlation coefficient, was 96.4% and the median of the root mean square error of the difference time series was 7.5 ms. The negligible error and high synchronization rate indicate high similarity and verified the agreement between the fully automated RR-interval series calculated with the AIT Multi-Lead ECGsolver and the reference time series. As a future perspective, HRV parameters calculated on this RR-time series can be evaluated in longitudinal studies to ensure clinical benefit.

Long-term monitoring of cardiorespiratory patterns in drug-resistant epilepsy.

OBJECTIVE: Sudden unexplained death in epilepsy (SUDEP) during inpatient electroencephalography (EEG) monitoring has been a rare but potentially preventable event, with associated cardiopulmonary markers. To date, no systematic evaluation of alarm settings for a continuous pulse oximeter (SpO2 ) has been performed. In addition, evaluation of the interrelationship between the ictal and interictal states for cardiopulmonary measures has not been reported. METHODS: Patients with epilepsy were monitored using video-EEG, SpO2 , and electrocardiography (ECG). Alarm thresholds were tested systematically, balancing the number of false alarms with true seizure detections. Additional cardiopulmonary patterns were explored using automated ECG analysis software. RESULTS: One hundred ninety-three seizures (32 generalized) were evaluated from 45 patients (7,104 h recorded). Alarm thresholds of 80-86% SpO2 detected 63-73% of all generalized convulsions and 20-28% of all focal seizures (81-94% of generalized and 25-36% of focal seizures when considering only evaluable data). These same thresholds resulted in 25-146 min between false alarms. The sequential probability of ictal SpO2 revealed a potential common seizure termination pathway of desaturation. A statistical model of corrected QT intervals (QTc), heart rate (HR), and SpO2 revealed close cardiopulmonary coupling ictally. Joint probability maps of QTc and SpO2 demonstrated that many patients had baseline dysfunction in either cardiac, pulmonary, or both domains, and that ictally there was dissociation-some patients exhibited further dysfunction in one or both domains. SIGNIFICANCE: Optimal selection of continuous pulse oximetry thresholds involves a tradeoff between seizure detection accuracy and false alarm frequency. Alarming at 86% for patients that tend to have fewer false alarms and at 80% for those who have more, would likely result in a reasonable tradeoff. The cardiopulmonary findings may lead to SUDEP biomarkers and early seizure termination therapies.

Associations of Novel and Traditional Vascular Biomarkers of Arterial Stiffness: Results of the SAPALDIA 3 Cohort Study.

BACKGROUND AND OBJECTIVES: There is a lack of evidence concerning associations between novel parameters of arterial stiffness as cardiovascular risk markers and traditional structural and functional vascular biomarkers in a population-based Caucasian cohort. We examined these associations in the second follow-up of the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA 3). METHODS: Arterial stiffness was measured oscillometrically by pulse wave analysis to derive the cardio-ankle vascular index (CAVI), brachial-ankle (baPWV) and aortic pulse wave velocity (aPWV), and amplitude of the forward and backward wave. Carotid ultrasonography was used to measure carotid intima-media thickness (cIMT) and carotid lumen diameter (LD), and to derive a distensibility coefficient (DC). We used multivariable linear regression models adjusted for several potential confounders for 2,733 people aged 50-81 years. RESULTS: CAVI, aPWV and the amplitude of the forward and backward wave were significant predictors of cIMT (p < 0.001). All parameters were significantly associated with LD (p < 0.001), with aPWV and the amplitude of the forward wave explaining the highest proportion of variance (2%). Only CAVI and baPWV were significant predictors of DC (p < 0.001), explaining more than 0.3% of the DC variance. CONCLUSION: We demonstrated that novel non-invasive oscillometric arterial stiffness parameters are differentially associated with specific established structural and functional local stiffness parameters. Longitudinal studies are needed to follow-up on these cross-sectional findings and to evaluate their relevance for clinical phenotypes.

Feasibility of oscillometric aortic pressure and stiffness assessment using the VaSera VS-1500: comparison with a common tonometric method.

OBJECTIVES: A number of operator-independent oscillometric devices to measure hemodynamics and arterial stiffness became available recently, but some and in particular VaSera VS-1500 do not provide estimates of aortic pressures and aortic pulse wave velocity (aPWV). The aim of this work was the retrospective application of the ARCSolver algorithm to pulse wave signals acquired with the VaSera VS-1500 device to estimate central systolic blood pressure (cSBP) and aPWV. MATERIALS AND METHODS: ARCSolver estimates of cSBP and aPWV, on the basis of brachial cuff measurements, were compared pair-wise with results from the tonometric SphygmoCor device in 68 individuals (mean age 51±18 years). We used variation estimates, correlation coefficients, age group-related t-tests, and the Bland-Altman method to analyze the reproducibility and agreement of the two methods. RESULTS: cSBP reproducibility expressed as variability was 14.9% for ARCSolver and 11.6% for SphygmoCor. PWV reproducibility was better for ARCSolver, with a variation estimate of 6.5%, compared with 20.9% using SphygmoCor. The mean cSBP difference was 0.5 mmHg (SD 6.9 mmHg) and 0.32 m/s (SD 1.20 m/s) for PWV, respectively. The age-related differences between ARCSolver and SphygmoCor are in line with previous studies. Bland-Altman plots showed considerable agreement between the two methods without signs of systematic bias. CONCLUSION: These results show that the combined application of the ARCSolver method with the VaSera VS-1500 device is feasible and the results are comparable with tonometric determination of cSBP and aPWV. This successful application of the ARCSolver may potentially help to improve cardiovascular risk stratification and prevention at an early stage in a community setting.

Determinants and covariates of central pressures and wave reflections in systolic heart failure.

BACKGROUND: In general, higher blood pressure levels and increased central pulsatility are indicators for increased cardiovascular risk. However, in systolic heart failure (SHF), this relationship is reversed. Therefore, the aim of this work is to compare pulsatile hemodynamics between patients with SHF and controls and to clarify the relationships between measures of cardiac and arterial function in the two groups. METHODS: We used parameters derived from angiography, echocardiography, as well as from pulse wave analysis (PWA) and wave separation analysis (WSA) based on non-invasively assessed pressure and flow waves to quantify cardiac function, aortic stiffness and arterial wave reflection in 61 patients with highly reduced (rEF) and 122 matched control-patients with normal ejection fraction (nEF). RESULTS: Invasively measured pulse wave velocity was comparable between the groups (8.6/8.05 m/s rEF/nEF, P = 0.24), whereas all measures derived by PWA and WSA were significantly decreased (augmentation index: 18.1/24.8 rEF/nEF, P < 0.01; reflection magnitude: 56.3/62.1 rEF/nEF, P < 0.01). However, these differences could be explained by the shortened ejection duration (ED) in rEF (ED: 269/308 ms rEF/nEF, P < 0.01; AIx: 22.2/22.8 rEF/nEF, P = 0.7; RM: 59.3/60.6 rEF/nEF, P = 0.47 after adjustment for ED). Ventricular function was positively associated with central pulse pressures in SHF in contrast to no or even a slightly negative association in controls. CONCLUSIONS: The results suggest that the decreased measures of pulsatile function may be caused by impaired systolic function and altered interplay of left ventricle and vascular system rather than by a real reduction of wave reflections or aortic stiffness in SHF.

Non-invasive wave reflection quantification in patients with reduced ejection fraction.

The non-invasive quantification of arterial wave reflection is an increasingly important concept in cardiovascular research. It is commonly based on pulse wave analysis (PWA) of aortic pressure. Alternatively, wave separation analysis (WSA) considering both aortic pressure and flow waveforms can be applied. Necessary estimates of aortic flow can be measured by Doppler ultrasound or provided by mathematical models. However, this approach has not been investigated intensively up to now in subjects developing systolic heart failure characterized by highly reduced ejection fraction (EF). We used non-invasively generated aortic pressure waveforms and Doppler flow measurements to derive wave reflection parameters in 61 patients with highly reduced and 122 patients with normal EF. Additionally we compared these readings with estimates from three different flow models known from literature (triangular, averaged, Windkessel). After correction for confounding factors, all parameters of wave reflection (PWA and WSA) were comparable for patients with reduced and normal EF. Wave separations assessed with the Windkessel based model were similar to those derived from Doppler flow in both groups. The averaged waveform performed poorer in reduced than in normal EF, whereas triangular flow represented a better approximation for reduced EF. Overall, the non-invasive assessment of WSA parameters based on mathematical models compared to ultrasound seems feasible in patients with reduced EF.

Selection of entropy-measure parameters for knowledge discovery in heart rate variability data.

BACKGROUND: Heart rate variability is the variation of the time interval between consecutive heartbeats. Entropy is a commonly used tool to describe the regularity of data sets. Entropy functions are defined using multiple parameters, the selection of which is controversial and depends on the intended purpose. This study describes the results of tests conducted to support parameter selection, towards the goal of enabling further biomarker discovery. METHODS: This study deals with approximate, sample, fuzzy, and fuzzy measure entropies. All data were obtained from PhysioNet, a free-access, on-line archive of physiological signals, and represent various medical conditions. Five tests were defined and conducted to examine the influence of: varying the threshold value r (as multiples of the sample standard deviation σ, or the entropy-maximizing rChon), the data length N, the weighting factors n for fuzzy and fuzzy measure entropies, and the thresholds rF and rL for fuzzy measure entropy. The results were tested for normality using Lilliefors' composite goodness-of-fit test. Consequently, the p-value was calculated with either a two sample t-test or a Wilcoxon rank sum test. RESULTS: The first test shows a cross-over of entropy values with regard to a change of r. Thus, a clear statement that a higher entropy corresponds to a high irregularity is not possible, but is rather an indicator of differences in regularity. N should be at least 200 data points for r = 0.2 σ and should even exceed a length of 1000 for r = rChon. The results for the weighting parameters n for the fuzzy membership function show different behavior when coupled with different r values, therefore the weighting parameters have been chosen independently for the different threshold values. The tests concerning rF and rL showed that there is no optimal choice, but r = rF = rL is reasonable with r = rChon or r = 0.2σ. CONCLUSIONS: Some of the tests showed a dependency of the test significance on the data at hand. Nevertheless, as the medical conditions are unknown beforehand, compromises had to be made. Optimal parameter combinations are suggested for the methods considered. Yet, due to the high number of potential parameter combinations, further investigations of entropy for heart rate variability data will be necessary.