Unified Language for Knowledge Dissemination: The Vascular Ageing Glossary, an Initiative by VascAgeNet.

Objectives: In general, a terminology shared and agreed by different stakeholders is important to facilitate communication and cooperation. This holds true in the field of vascular ageing for the benefit of global cardiovascular health. The need to promote a common language and understanding across this area was recognised by VascAgeNet, a collaborative network with relevant and diverse expertise in the vascular ageing field, supported by the European Cooperation in Science and Technology. To contribute to the spread of unified terms in the vascular ageing field, a glossary was created by VascAgeNet and this paper describes the systematic process used for its development. Methods: An initial list of terms and preliminary definitions were collated from the network. A dedicated team was created to design the glossary development process, to facilitate its implementation and to maximise outreach and dissemination. The key steps of the process were to determine: (1) the target audience; (2) a list of priority terms; (3) a template structure for definitions; (4) methods for collecting feedback and (5) the dissemination plan. Results: An implementation strategy was provided for each key step and shared within the network; main decisions were agreed by all members of the glossary team. Small groups of definitions were released on a regular basis within a pilot phase including 19 terms (status: 05.09.2023) that were published openly at https://vascagenet.eu/official-glossary. Conclusions: The strategy for creating the first Vascular Ageing Glossary has been successfully designed and developed within VascAgeNet. A pilot phase covering the first publicly available terms was completed. The glossary is a living document, available to the scientific community, which aims to unify the vascular ageing language. Supplementary Information: The online version contains supplementary material available at 10.1007/s44200-023-00041-5.

Detection of contractility changes in the heart from arterial blood pressure data using symmetric Projection Attractor Reconstruction.

The potential for unintended drug induced changes in cardiac contractility is a major concern in medicines development. Whilst direct left ventricular pressure (LVP) measurement is the gold standard for measuring cardiac contractility in vivo, it is resource intensive and poses a welfare burden on research animals. In contrast, arterial blood pressure (BP) measurement has fewer challenges. Symmetric Projection Attractor Reconstruction (SPAR) is a signal processing technique which transforms physiological time-series signals into a corresponding visual image ('attractor'), amplifying morphology changes within physiological waveforms. It was hypothesized that SPAR analysis of BP signals would provide a surrogate measure of cardiac contractility by specifically amplifying the maximum slope of the systolic upstroke. BP (abdominal aorta) signals obtained from beagle dogs, treated with positive and negative inotropes, were retrospectively analysed to identify signal features that correlated with the maximum upslope of the LVP signal from simultaneously acquired LVP recordings. SPAR transformation of BP signals quantified drug induced changes in the maximum slope of the systolic upstroke. We identified key SPAR metrics that provided >0.8 correlation with the LVP maximum upslope, outperforming the BP systolic upstroke alone. This was observed for all 4 different drugs, doses and time points evaluated across studies. Thus, we conclude that the SPAR measures derived from the BP signal could be used as a first pass in vivo screen to flag any risk of drug induced changes in cardiac contractility during the conduct of non-clinical medicines development, potentially reducing or replacing the need to perform direct left ventricular measurements.

Advanced waveform analysis of the photoplethysmogram signal using complementary signal processing techniques for the extraction of biomarkers of cardiovascular function.

Introduction: Photoplethysmogram signals from wearable devices typically measure heart rate and blood oxygen saturation, but contain a wealth of additional information about the cardiovascular system. In this study, we compared two signal-processing techniques: fiducial point analysis and Symmetric Projection Attractor Reconstruction, on their ability to extract new cardiovascular information from a photoplethysmogram signal. The aim was to identify fiducial point analysis and Symmetric Projection Attractor Reconstruction indices that could classify photoplethysmogram signals, according to age, sex and physical activity. Methods: Three datasets were used: an in-silico dataset of simulated photoplethysmogram waves for healthy male participants (25-75 years old); an in-vivo dataset containing 10-min photoplethysmogram recordings from 57 healthy subjects at rest (18-39 or > 70 years old; 53% female); and an in-vivo dataset containing photoplethysmogram recordings collected for 4 weeks from a single subject, in daily life. The best-performing indices from the in-silico study (5/48 fiducial point analysis and 6/49 Symmetric Projection Attractor Reconstruction) were applied to the in-vivo datasets. Results: Key fiducial point analysis and Symmetric Projection Attractor Reconstruction indices, which showed the greatest differences between groups, were found to be consistent across datasets. These indices were related to systolic augmentation, diastolic peak positioning and prominence, and waveform variability. Both fiducial point analysis and Symmetric Projection Attractor Reconstruction techniques provided indices that supported the classification of age and physical activity, but not sex. Conclusions: Both fiducial point analysis and Symmetric Projection Attractor Reconstruction techniques demonstrated utility in identifying cardiovascular differences between individuals and within an individual over time. Future research should investigate the potential utility of these techniques for extracting information on fitness and disease, to support healthcare-decision making.

Noninvasive hemodynamic indices of vascular aging: an in silico assessment.

Vascular aging (VA) involves structural and functional changes in blood vessels that contribute to cardiovascular disease. Several noninvasive pulse wave (PW) indices have been proposed to assess the arterial stiffness component of VA in the clinic and daily life. This study investigated 19 of these indices, identified in recent review articles on VA, by using a database comprising 3,837 virtual healthy subjects aged 25-75 yr, each with unique PW signals simulated under various levels of artificial noise to mimic real measurement errors. For each subject, VA indices were calculated from filtered PW signals and compared with the precise theoretical value of aortic Young's modulus (EAo). In silico PW indices showed age-related changes that align with in vivo population studies. The cardio-ankle vascular index (CAVI) and all pulse wave velocity (PWV) indices showed strong linear correlations with EAo (Pearson's rp > 0.95). Carotid distensibility showed a strong negative nonlinear correlation (Spearman's rs < -0.99). CAVI and distensibility exhibited greater resilience to noise compared with PWV indices. Blood pressure-related indices and photoplethysmography (PPG)-based indices showed weaker correlations with EAo (rp and rs < 0.89, |rp| and |rs| < 0.84, respectively). Overall, blood pressure-related indices were confounded by more cardiovascular properties (heart rate, stroke volume, duration of systole, large artery diameter, and/or peripheral vascular resistance) compared with other studied indices, and PPG-based indices were most affected by noise. In conclusion, carotid-femoral PWV, CAVI and carotid distensibility emerged as the superior clinical VA indicators, with a strong EAo correlation and noise resilience. PPG-based indices showed potential for daily VA monitoring under minimized noise disturbances.NEW & NOTEWORTHY For the first time, 19 noninvasive pulse wave indices for assessing vascular aging were examined together in a single database of nearly 4,000 subjects aged 25-75 yr. The dataset contained precise values of the aortic Young's modulus and other hemodynamic measures for each subject, which enabled us to test each index's ability to measure changes in aortic stiffness while accounting for confounding factors and measurement errors. The study provides freely available tools for analyzing these and additional indices.

Novel breathing pattern analysis: Symmetric Projection Attractor Reconstruction improves identification of impending COPD re-exacerbations - a retrospective cohort analysis.

Respiratory waveforms can be reduced to simple metrics, such as rate, but this may miss information about waveform shape and whole breathing pattern. A novel analysis method quantifying the whole waveform shape identifies AECOPD earlier. https://bit.ly/3M6uIEB.

Enhancing Techniques for Determining Inflammatory Edema Formation and Neutrophil Accumulation in Murine Skin.

Inflammatory edema formation and polymorphonuclear leukocyte (neutrophil) accumulation are common components of cutaneous vascular inflammation, and their assessment is a powerful investigative and drug development tool but typically requires independent cohorts of animals to assess each. We have established the use of a mathematical formula to estimate the ellipsoidal-shaped volume of the edematous wheal or bleb after intradermal injections of substances in mice pretreated intravenously with Evans blue dye (which binds to plasma albumin) to act as an edema marker. Whereas previous extraction of Evans blue dye with formamide is suitable for all strains of mice, we report this quicker and more reliable assessment of edema volume in situ. This therefore allows neutrophil accumulation to be assessed from the same mouse using the myeloperoxidase assay. Importantly, we examined the influence of Evans blue dye on the spectrometry readout at the wavelength at which myeloperoxidase activity is measured. The results indicate that it is feasible to quantify edema formation and neutrophil accumulation in the same mouse skin site. Thus, we show techniques that can assess edema formation and neutrophil accumulation at the same site in the same mouse, allowing paired measurements and reducing the total use of mice by 50%.

Cardiovascular waveforms - can we extract more from routine signals?

Cardiovascular waveforms such as blood pressure, ECG and photoplethysmography (PPG), are routinely acquired by specialised monitoring devices. Such devices include bedside monitors, wearables and radiotelemetry which sample at very high fidelity, yet most of this numerical data is disregarded and focus tends to reside on single point averages such as the maxima, minima, amplitude, rate and intervals. Whilst, these measures are undoubtedly of value, we may be missing important information by simplifying the complex waveform signal in this way. This Special Collection showcases recent advances in the appraisal of routine signals. Ultimately, such approaches and technologies may assist in improving the accuracy and sensitivity of detecting physiological change. This, in turn, may assist with identifying efficacy or safety signals for investigational new drugs or aidpatient diagnosis and management, supporting scientific and clinical decision making.

The glucose tolerance test in mice: Sex, drugs and protocol.

AIM: To establish the impact of sex, dosing route, fasting duration and acute habituation stress on glucose tolerance test (GTT) measurements used in the preclinical evaluation of potential glucose-modulating therapeutics. METHODS: Adult male and female C57Bl/6J mice, implanted with HD-XG glucose telemetry devices, were fasted for 16 hours or 6 hours following acute habituation stress due to whole cage change, cage change with retention of used bedding or no cage change prior to intraperitoneal (IP) GTTs. To evaluate protocol refinement and sex on the ability of the GTT to detect drug effects, we administered 250 mg/kg oral metformin or 10 nmol/kg IP exendin-4 using optimized protocols. RESULTS: Female mice were less sensitive to human intervention when initiating fasting. Following a 6-hour fast, retention of bedding whilst changing the cage base promotes quicker stabilization of basal blood glucose in both sexes. Prolonged fasting for 16 hours resulted in an exaggerated GTT response but induced pronounced basal hypoglycaemia. Following GTT protocol optimization the effect of exendin-4 and metformin was equivalent in both sexes, with females showing a more modest but more reproducible GTT response. CONCLUSIONS: Variations in GTT protocol have profound effects on glucose homeostasis. Protocol refinement and/or the use of females still allows for detection of drug effects, providing evidence that more severe phenotypes are not an essential prerequisite when characterizing/validating new drugs.

Detecting paroxysmal atrial fibrillation from normal sinus rhythm in equine athletes using Symmetric Projection Attractor Reconstruction and machine learning.

Background: Atrial fibrillation (AF) is a common cardiac arrhythmia in both human and equine populations. It is associated with adverse outcomes in humans and decreased athletic performance in both populations. Paroxysmal atrial fibrillation (PAF) presents with intermittent, self-terminating AF episodes, and is difficult to diagnose once sinus rhythm resumes. Objective: We aimed to detect PAF subjects from normal sinus rhythm equine electrocardiograms (ECGs) using the Symmetric Projection Attractor Reconstruction (SPAR) method to encapsulate the waveform morphology and variability as the basis of a machine learning classification. Methods: We obtained ECG signals from 139 active equine athletes (120 control, 19 with a PAF diagnosis). The SPAR method was applied to 9 short (20-second) ECG strips for each subject. An optimal SPAR feature set was determined by forward feature selection for input to a machine learning model ensemble of 3 different classifiers (k-nearest neighbors, linear support vector machine, and radial basis function kernel support vector machine). Imbalanced data were handled by upsampling the minority (PAF) class. A final subject classification was made by taking a majority vote over results from the 9 ECG strips. Results: Our final cross-validated classification for a subject gave an accuracy of 89.0%, sensitivity of 94.8%, specificity of 87.1%, and receiver operating characteristic area under the curve of 0.98, taking PAF as the positive class. Conclusion: The SPAR method and machine learning generated a final model with high sensitivity, suggesting that PAF can be discriminated from short equine ECG strips. This preliminary study indicated that SPAR analysis of human ECG could support patient monitoring, risk stratification, and clinical decision-making.

Symmetric Projection Attractor Reconstruction: Sex Differences in the ECG.

Background: The electrocardiogram (ECG) is a key tool in patient management. Automated ECG analysis supports clinical decision-making, but traditional fiducial point identification discards much of the time-series data that captures the morphology of the whole waveform. Our Symmetric Projection Attractor Reconstruction (SPAR) method uses all the available data to provide a new visualization and quantification of the morphology and variability of any approximately periodic signal. We therefore applied SPAR to ECG signals to ascertain whether this more detailed investigation of ECG morphology adds clinical value. Methods: Our aim was to demonstrate the accuracy of the SPAR method in discriminating between two biologically distinct groups. As sex has been shown to influence the waveform appearance, we investigated sex differences in normal sinus rhythm ECGs. We applied the SPAR method to 9,007 10 second 12-lead ECG recordings from Physionet, which comprised; Dataset 1: 104 subjects (40% female), Dataset 2: 8,903 subjects (54% female). Results: SPAR showed clear visual differences between female and male ECGs (Dataset 1). A stacked machine learning model achieved a cross-validation sex classification accuracy of 86.3% (Dataset 2) and an unseen test accuracy of 91.3% (Dataset 1). The mid-precordial leads performed best in classification individually, but the highest overall accuracy was achieved with all 12 leads. Classification accuracy was highest for young adults and declined with older age. Conclusions: SPAR allows quantification of the morphology of the ECG without the need to identify conventional fiducial points, whilst utilizing of all the data reduces inadvertent bias. By intuitively re-visualizing signal morphology as two-dimensional images, SPAR accurately discriminated ECG sex differences in a small dataset. We extended the approach to a machine learning classification of sex for a larger dataset, and showed that the SPAR method provided a means of visualizing the similarities of subjects given the same classification. This proof-of-concept study therefore provided an implementation of SPAR using existing data and showed that subtle differences in the ECG can be amplified by the attractor. SPAR's supplementary analysis of ECG morphology may enhance conventional automated analysis in clinically important datasets, and improve patient stratification and risk management.

The use of mice in diabetes research: The impact of experimental protocols.

Mice are used extensively in preclinical diabetes research to model various aspects of blood glucose homeostasis. Careful experimental design is vital for maximising welfare and improving reproducibility of data. Alongside decisions regarding physiological characteristics of the animal cohort (e.g., sex, strain and age), experimental protocols must also be carefully considered. This includes choosing relevant end points of interest and understanding what information they can provide and what their limitations are. Details of experimental protocols must, therefore, be carefully planned during the experimental design stage, especially considering the impact of researcher interventions on preclinical end points. Indeed, in line with the 3Rs of animal research, experiments should be refined where possible to maximise welfare. The role of welfare may be particularly pertinent in preclinical diabetes research as blood glucose concentrations are directly altered by physiological stress responses. Despite the potential impact of variations in experimental protocols, there is distinct lack of standardisation and consistency throughout the literature with regards to several experimental procedures including fasting, cage changing and glucose tolerance test protocol. This review firstly highlights practical considerations with regard to the choice of end points in preclinical diabetes research and the potential for novel technologies such as continuous glucose monitoring and glucose clamping techniques to improve data resolution. The potential influence of differing experimental protocols and in vivo procedures on both welfare and experimental outcomes is then discussed with focus on standardisation, consistency and full disclosure of methods.

Rethinking animal models of sepsis - working towards improved clinical translation whilst integrating the 3Rs.

Sepsis is a major worldwide healthcare issue with unmet clinical need. Despite extensive animal research in this area, successful clinical translation has been largely unsuccessful. We propose one reason for this is that, sometimes, the experimental question is misdirected or unrealistic expectations are being made of the animal model. As sepsis models can lead to a rapid and substantial suffering - it is essential that we continually review experimental approaches and undertake a full harm:benefit impact assessment for each study. In some instances, this may require refinement of existing sepsis models. In other cases, it may be replacement to a different experimental system altogether, answering a mechanistic question whilst aligning with the principles of reduction, refinement and replacement (3Rs). We discuss making better use of patient data to identify potentially useful therapeutic targets which can subsequently be validated in preclinical systems. This may be achieved through greater use of construct validity models, from which mechanistic conclusions are drawn. We argue that such models could provide equally useful scientific data as face validity models, but with an improved 3Rs impact. Indeed, construct validity models may not require sepsis to be modelled, per se. We propose that approaches that could support and refine clinical translation of research findings, whilst reducing the overall welfare burden on research animals.

Extracting new information from old waveforms: Symmetric projection attractor reconstruction: Where maths meets medicine.

NEW FINDINGS: What is the topic of this review? Symmetric Projection Attractor Reconstruction (SPAR) is a relatively new mathematical method that can extract additional information pertaining to the morphology and variability of physiological waveforms, such as arterial pulse pressure. Herein, we describe the potential utility of the method for more sensitive quantification of cardiovascular changes. What advances does it highlight? We use a simple example of a human tilt table to illustrate these concepts. SPAR can be used on any approximately periodic waveform and may add value to experimental and clinical settings, where such signals are collected routinely. ABSTRACT: Periodic physiological waveform data, such as blood pressure, pulse oximetry and ECG, are routinely sampled between 100 and 1000 Hz in preclinical research and in the clinical setting from a wide variety of implantable, bedside and wearable monitoring devices. Despite the underlying numerical waveform data being captured at such high fidelity, conventional analysis tends to reside in reporting only averages of minimum, maximum, amplitude and rate, as single point averages. Although these averages are undoubtedly of value, simplification of the data in this way means that most of the available numerical data are discarded. In turn, this may lead to subtle physiological changes being missed when investigating the cardiovascular system over time. We have developed a mathematical method (symmetric projection attractor reconstruction) that uses all the numerical data, replotting and revisualizing them in a manner that allows unique quantification of multiple changes in waveform morphology and variability. We propose that the additional quantification of these features will allow the complex behaviour of the cardiovascular system to be mapped more sensitively in different physiological and pathophysiological settings.

CN128: A New Orally Active Hydroxypyridinone Iron Chelator.

Deferoxamine, deferiprone, and deferasirox are used for the treatment of systemic iron overload, although they possess limitations due to lack of oral activity, lower efficacy, and side effects. These limitations led to a search for an orally active iron chelator with an improved therapeutic index. The lower efficacy of deferiprone is due to rapid glucuronidation, leading to the formation of a nonchelating metabolite. Here, we demonstrate that the influence of metabolism can be reduced by introducing a sacrificial site for glucuronidation. A log P-guided investigation of 20 hydroxpyridinones led to the identification of CN128. The Fe(III) affinity and metal selectivity of CN128 are similar to those of deferiprone, the log P value is more lipophilic, and its iron scavenging ability is superior. Overall, CN128 was demonstrated to be safe in a range of toxicity assessments and is now in clinical trials for the treatment of ß-thalassemia after regular blood transfusion.

Continuous Glucose Monitoring in Conscious Unrestrained Mice.

Measurement of blood glucose concentration is a common end point in studies using animal models of diabetes. Usually a blood glucose meter is used to measure non-fasted blood glucose concentrations, typically at frequencies of between 1 and 7 times per week. This process involves pricking the tip of the tail to collect a small blood sample (0.5-5 µL), which could potentially cause a stress response and affect blood glucose concentrations. Moreover, with blood glucose concentrations constantly fluctuating in response to feeding and activity, a single-point measurement can easily misrepresent the actual glycemic control of the animal. In this chapter, we discuss the use of continuous glucose monitoring in mice by radio-telemetry which allows second-by-second changes in blood glucose to be captured without restraining the mouse. Glucose excursions rather than single-point measurements may prove more useful in detecting effects of treatments, and lack of handling may avoid stress responses causing artefacts. We outline what is involved in implanting such devices into mice including some practical tips to maximize success.

Symmetric Projection Attractor Reconstruction analysis of murine electrocardiograms: Retrospective prediction of Scn5a+/- genetic mutation attributable to Brugada syndrome.

BACKGROUND: Life-threatening arrhythmias resulting from genetic mutations are often missed in current electrocardiogram (ECG) analysis. We combined a new method for ECG analysis that uses all the waveform data with machine learning to improve detection of such mutations from short ECG signals in a mouse model. OBJECTIVE: We sought to detect consequences of Na+ channel deficiencies known to compromise action potential conduction in comparisons of Scn5a+/- mutant and wild-type mice using short ECG signals, examining novel and standard features derived from lead I and II ECG recordings by machine learning algorithms. METHODS: Lead I and II ECG signals from anesthetized wild-type and Scn5a+/- mutant mice of length 130 seconds were analyzed by extracting various groups of features, which were used by machine learning to classify the mice as wild-type or mutant. The features used were standard ECG intervals and amplitudes, as well as features derived from attractors generated using the novel Symmetric Projection Attractor Reconstruction method, which reformulates the whole signal as a bounded, symmetric 2-dimensional attractor. All the features were also combined as a single feature group. RESULTS: Classification of genotype using the attractor features gave higher accuracy than using either the ECG intervals or the intervals and amplitudes. However, the highest accuracy (96%) was obtained using all the features. Accuracies for different subgroups of the data were obtained and compared. CONCLUSION: Detection of the Scn5a+/- mutation from short mouse ECG signals with high accuracy is possible using our Symmetric Projection Attractor Reconstruction method.

Nitric Oxide Modulates Metabolic Remodeling in Inflammatory Macrophages through TCA Cycle Regulation and Itaconate Accumulation.

Classical activation of macrophages (M(LPS+IFNγ)) elicits the expression of inducible nitric oxide synthase (iNOS), generating large amounts of NO and inhibiting mitochondrial respiration. Upregulation of glycolysis and a disrupted tricarboxylic acid (TCA) cycle underpin this switch to a pro-inflammatory phenotype. We show that the NOS cofactor tetrahydrobiopterin (BH4) modulates IL-1ß production and key aspects of metabolic remodeling in activated murine macrophages via NO production. Using two complementary genetic models, we reveal that NO modulates levels of the essential TCA cycle metabolites citrate and succinate, as well as the inflammatory mediator itaconate. Furthermore, NO regulates macrophage respiratory function via changes in the abundance of critical N-module subunits in Complex I. However, NO-deficient cells can still upregulate glycolysis despite changes in the abundance of glycolytic intermediates and proteins involved in glucose metabolism. Our findings reveal a fundamental role for iNOS-derived NO in regulating metabolic remodeling and cytokine production in the pro-inflammatory macrophage.

A novel method to quantify arterial pulse waveform morphology: attractor reconstruction for physiologists and clinicians.

Current arterial pulse monitoring systems capture data at high frequencies (100-1000 Hz). However, they typically report averaged or low frequency summary data such as heart rate and systolic, mean and diastolic blood pressure. In doing so, a potential wealth of information contained in the high-fidelity waveform data is discarded, data which has long been known to contain useful information on cardiovascular performance. Here we summarise a new mathematical method, attractor reconstruction, which enables the quantification of arterial waveform shape and variability in real-time. The method can handle long streams of non-stationary data and does not require preprocessing of the raw physiological data by the end user. Whilst the detailed mathematical proofs have been described elsewhere (Aston et al 2008 Physiol. Meas. 39), the authors were motivated to write a summary of the method and its potential utility for biomedical researchers, physiologists and clinician readers. Here we illustrate how this new method may supplement and potentially enhance the sensitivity of detecting cardiovascular disturbances, to aid with biomedical research and clinical decision making.

l-Phenylalanine Restores Vascular Function in Spontaneously Hypertensive Rats Through Activation of the GCH1-GFRP Complex.

Reduced nitric oxide (NO) bioavailability correlates with impaired cardiovascular function. NO is extremely labile and has been challenging to develop as a therapeutic agent. However, NO bioavailability could be enhanced by pharmacologically targeting endogenous NO regulatory pathways. Tetrahydrobiopterin, an essential cofactor for NO production, is synthesized by GTP cyclohydrolase-1 (GCH1), which complexes with GCH1 feedback regulatory protein (GFRP). The dietary amino acid l-phenylalanine activates this complex, elevating vascular BH4. Here, the authors demonstrate that l-phenylalanine administration restores vascular function in a rodent model of hypertension, suggesting the GCH1-GFRP complex represents a rational therapeutic target for diseases underpinned by endothelial dysfunction.

Beyond HRV: attractor reconstruction using the entire cardiovascular waveform data for novel feature extraction.

Advances in monitoring technology allow blood pressure waveforms to be collected at sampling frequencies of 250-1000 Hz for long time periods. However, much of the raw data are under-analysed. Heart rate variability (HRV) methods, in which beat-to-beat interval lengths are extracted and analysed, have been extensively studied. However, this approach discards the majority of the raw data. OBJECTIVE: Our aim is to detect changes in the shape of the waveform in long streams of blood pressure data. APPROACH: Our approach involves extracting key features from large complex data sets by generating a reconstructed attractor in a three-dimensional phase space using delay coordinates from a window of the entire raw waveform data. The naturally occurring baseline variation is removed by projecting the attractor onto a plane from which new quantitative measures are obtained. The time window is moved through the data to give a collection of signals which relate to various aspects of the waveform shape. MAIN RESULTS: This approach enables visualisation and quantification of changes in the waveform shape and has been applied to blood pressure data collected from conscious unrestrained mice and to human blood pressure data. The interpretation of the attractor measures is aided by the analysis of simple artificial waveforms. SIGNIFICANCE: We have developed and analysed a new method for analysing blood pressure data that uses all of the waveform data and hence can detect changes in the waveform shape that HRV methods cannot, which is confirmed with an example, and hence our method goes 'beyond HRV'.