Name: Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver (Video) | JoVE Journal
Uploaded: 2025-06-27T12:40:00.000+00:00
Duration: 14 min 28 s
Description: Learn to analyze ECG and blood pressure time-series data from the Valsalva maneuver using ValsalvaAnalyzer software. This computational tool extracts cardiovascular biomarkers for autonomic dysfunction diagnosis.

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This study was partially funded by the National Science Foundation awards (DMS-2051010) and NSA awards (H98230-21-1-0014 and H98230-20-1-0259). We want to thank Sanaa Elmajdoubi, Rigshospitalet, Denmark, Niloufar Mehrani and Jesper Mehlsen, Klinik Mehlsen, Denmark for testing the software. We want to thank E. Benjamin Randall, Applied Research Associates, Raleigh, NC, for discussing the mathematical model and Iryna Palamarchuk, University of Toronto, Canada, for the discussion of indices. Finally, we thank Sophie Carlson, University of California San Diego, for revising and editing the computational code. The software stores results locally on the computer and shares no information with outside entities. Developers of the ValsalvaAnalyzer software are not responsible for using and protecting patient data. Any user of the ValsalvaAnalyzer is responsible for protecting data and obtaining appropriate approvals before publishing results generated with this software.

<ol><li>Palamarchuk, I., Baker, J., Kimpinski, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+utility+of+Valsalva+maneuver+in+the+diagnoses+of+orthostatic+disorders%5BTitle%5D)+AND+%22Am+J+Physiol%22%5BJournal%5D)">The utility of Valsalva maneuver in the diagnoses of orthostatic disorders.</a> Am J Physiol. 310 (3), R243-R252 (2016).</li>
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<li>Kim, H., Yi, H., Hong, J., Lee, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Detailed+relationship+between+the+pattern+of+blood+pressure+change+during+the+Valsalva+maneuver+and+the+degree+of+orthostatic+hypotension+during+the+head-up+tilt+test+in+patients+with+orthostatic+intolerance%3A+a+retrospective+case-control+study%5BTitle%5D)+AND+%22Medicine+%28Baltimore%29%22%5BJournal%5D)">Detailed relationship between the pattern of blood pressure change during the Valsalva maneuver and the degree of orthostatic hypotension during the head-up tilt test in patients with orthostatic intolerance: a retrospective case-control study.</a> Medicine (Baltimore). 95 (19), e3608(2016).</li>
<li>Bingger, W., Mitchell, R., Harron, D., McKaigue, J., McAloney, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Real+time+analysis+of+Valsalva+maneuver%5BTitle%5D)+AND+%22Comput+BIol+Med%22%5BJournal%5D)">Real time analysis of Valsalva maneuver.</a> Comput BIol Med. 19 (5), 319-329 (1989).</li>
<li>Randall, E., Billeschou, A., Brinth, L., Mehlsen, J., Olufsen, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+model-based+analysis+of+autonomic+nervous+function+in+response+to+the+Valsalva+maneuver%5BTitle%5D)+AND+%22J+Appl+Physiol%22%5BJournal%5D)">A model-based analysis of autonomic nervous function in response to the Valsalva maneuver.</a> J Appl Physiol. 127 (5), 1386-1402 (2019).</li>
<li>Motamedi, M., Akbarzadeh, M., Safari, S., Shahhoseini, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Valsalva+maneuver+using+a+Handmade+Device+in+Supraventricular+Tachycardia+Reversion%3B+a+quasi+experimental+study%5BTitle%5D)+AND+%22Emerg+%28Tehran%29%22%5BJournal%5D)">Valsalva maneuver using a Handmade Device in Supraventricular Tachycardia Reversion; a quasi experimental study.</a> Emerg (Tehran). 5 (1), e81(2017).</li>
<li>Abdulhamid, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Modified+Valsalva+versus+standard+Valsalva+for+cardioversion+of+supraventricular+tachycardia%3A+systematic+review+and+meta-analysis%5BTitle%5D)+AND+%22Int+J+Arrhythmia%22%5BJournal%5D)">Modified Valsalva versus standard Valsalva for cardioversion of supraventricular tachycardia: systematic review and meta-analysis.</a> Int J Arrhythmia. 22, 2(2021).</li>
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<li>Hristovska, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Orthostatic+intolerance+after+acute+mild+hypovolemia%3A+incidence%2C+pathophysiologic+hemodynamics%2C+and+heart-rate+variability+analysis-a+prospective+observational+cohort+study%5BTitle%5D)+AND+%22Can+J+Anaesth%22%5BJournal%5D)">Orthostatic intolerance after acute mild hypovolemia: incidence, pathophysiologic hemodynamics, and heart-rate variability analysis-a prospective observational cohort study.</a> Can J Anaesth. 70 (10), 1587-1599 (2023).</li>
<li>Hristovska, A., Uldall-Hansen, B., Mehlsen, J., Kehlet, H., Foss, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Orthostatic+intolerance+after+intravenous+administration+of+morphine%3A+incidence%2C+haemodynamics+and+heart+rate+variability+analysis%5BTitle%5D)+AND+%22Anesthesia%22%5BJournal%5D)">Orthostatic intolerance after intravenous administration of morphine: incidence, haemodynamics and heart rate variability analysis.</a> Anesthesia. 78 (4), 526-528 (2022).</li>
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<li>Sandroni, P., Benarroch, E., Low, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Pharmacological+dissection+of+components+of+the+Valsalva+maneuver+in+adrenergic+failure%5BTitle%5D)+AND+%22J+Appl+Physiol%22%5BJournal%5D)">Pharmacological dissection of components of the Valsalva maneuver in adrenergic failure.</a> J Appl Physiol. 71 (4), 1563-1567 (1985).</li>
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<li>Novak, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Assessment+of+sympathetic+index+from+the+Valsalva+maneuver%5BTitle%5D)+AND+%22Neurology%22%5BJournal%5D)">Assessment of sympathetic index from the Valsalva maneuver.</a> Neurology. 76 (23), 2010-2016 (2011).</li>
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</ol>

The authors have nothing to disclose.

The ValsalvaAnalyzer software demonstrated in this study provides functionality to analyze clinical ECG and BP data recorded during the Valsalva maneuver. The software offers the ability to clean noisy signals, making it feasible to get consistent measures across a population. Using the corrected data, the software computes more than 35 markers that the user can interpret. The software aims to include all known quantities reported during the Valsalva maneuver reported in several studies1,</su...

The Valsalva Maneuver is a low-risk, non-invasive, inexpensive, and highly accessible test to measure the autonomic nervous system function through forced expiratory exercises1,2. The maneuver is performed by patients exhaling into a positive end-expiratory pressure (PEP) device connected to a manometer, holding an intrathoracic pressure of 40 mmHg for 15 s, typically&#160;in a supine or seated position2,3. This maneuver simultaneously challenges the autonomic and cardiovascular systems, mimicking the physiological response to stressors like straining while lifting heavy objects or equilibrating pressure when flying4. This test is used frequently in clinical settings2,5, but more tools are needed to analyze data quantifying the underlying physiological mechanisms. Neurological modeling applied to the VM may facilitate the identification of improved diagnostic criteria and causal mechanisms for autonomic dysfunction5.
The VM has four phases6. It is facilitated by a breath hold, which increases intrathoracic pressure, compressing the cardiac chambers and the thoracic aorta and emptying blood in the systematic circulation, thereby causing a transitory increase in BP. Phase I is characterized by a continuous increase in intrathoracic pressure, reducing the venous blood flow to the heart, the stroke volume, and the mean arterial BP. In response, the high-pressure arterial baroreceptors are activated. The decrease in BP during the early part of Phase II causes a parasympathetic withdrawal, increasing HR. During the late part of Phase II, sympathetic excess mediates vasoconstriction, increasing BP and HR. In healthy patients, BP recovery is the resting value before releasing the breath hold. Phase III is reciprocal to Phase I. This phase is initiated when the patient releases their breath hold, which causes sharp decreases in intrathoracic pressure and arterial BP, usually followed by an HR increase. In Phase IV, increased venous return to the heart and persisting vasoconstriction from late Phase II results in a marked BP increase called an overshoot. Stimulation of high-pressure arterial baroreceptors by the overshoot activates the vagal nerve to reduce HR. The patient is expected to recover to pretest values approximately 10-30 s after the VM onset2,5.
The VM is used for bedside evaluation of autonomic and cardiovascular function7. The most common VM biomarker, the Valsalva ratio (VR)8,9,10, measures parasympathetic function as the ratio between the longest RR interval after the breath-hold onset and the shortest RR interval. It has previously been established that postural orthostatic tachycardia (POTS) is associated with a high VR and a notable BP overshoot in Phase IV11, also called N-pattern response1. Another metric is the vagal baroreflex sensitivity. This metric is estimated in the early part of Phases II and IV as the regression slope between RR intervals and characteristic BP changes3,10,12,13,14. Qualitative analysis of BP responses to the VM can identify different heart murmurs9, and a distinctive square-wave response is a bedside indicator of impaired ventricular function and heart failure15,16. The absence of BP overshoot and the presence of bradycardia after breath-hold release is indicative of dysautonomia13. The V-pattern response with progressive BP decline in late Phase II and slow recovery in Phase IV is characteristic of neurogenic orthostatic hypotension, indicating alpha-adrenergic baroreflex failure1. Other studies have demonstrated the efficacy of using the VM to supplement head-up tilt testing in screening for orthostatic disorders1,17,18.
Numerous studies have examined autonomic function by analyzing HR and BP responses during the VM1, but no open-source automated systems are available to quantify the baroreflex function. Many studies have analyzed data from the VM19,20,21,22, and a few software specialize in autonomic function, including VitalScan by Medeia23 and Kubios24. VitalScan utilizes ECG and BP signals, but Kubios only analyzes ECG signals. The VitalScan website notes that this software assesses autonomic function but lacks a detailed description of calculated quantities. Kubios determines HR variability (HRV) and the VR25. To address these gaps, this study develops a new open-source software that calculates the most common VM indices1,25.
The software analyzes ECG and BP data measured during a VM maneuver holding an intrathoracic pressure of 40 mmHg for 15 s. We recommend including at least 30 s stable data before and after the VM. After identifying HR and systolic BP, the VM onset and release, a set of clinical markers are extracted. In addition, this software uses the mathematical model by Randall et al.20 to predict sympathetic and parasympathetic signaling along with parameters characterizing the baroreflex sensitivity. Two critical features are the ability to read data from noisy signals, to identify and remove artifacts, and the automatic detection with manual correction of VM markers. The latter is vital for patients with autonomic dysfunction, where purely automatic detection fails. This exposition includes all results for subject 1 and a protocol to extract results for subjects 2-8. Results for subject 1 is included in the code, text, and figures, and results for all subjects are shown in Supplementary Figure&#160;1, Supplementary Figure 2,&#160;Supplementary Figure 3,&#160;Supplementary Figure 4,&#160;Supplementary Figure 5,&#160;Supplementary Figure 6,&#160;Supplementary Figure 7, and&#160;Supplementary Figure 8.
The Valsalva Analyzer software calculates adrenergic and vagal indices characterizing the response to the Valsalva maneuver (VM) from continuous ECG and BP measurements. To demonstrate the software, we provide a brief description of the experimental setup followed by a detailed description of the software. The software reads data extracted from patient records stored in LabChart. The analysis is demonstrated on a healthy control patient, but the software includes data from eight subjects with a range of autonomic responses. Below, we discuss patient examples and describe the protocol to install and run the software. The protocol includes references to figures generated within MATLAB. To distinguish these from figures included in the representative results, these are all referred to as MFigure #.

<table><tbody><tr><td>LabChart</td><td>ADInstruments</td><td></td><td>Software that the data analyzed are exported from</td></tr><tr><td>MATLAB</td><td>Mathworks</td><td></td><td>Software used for the ValsalvaAnalyzer program</td></tr></tbody></table>

software for analysis of heart rate and blood pressure time-series data from the valsalva maneuver

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

The Valsalva Maneuver (VM) is a low-risk highly accessible test that measures the baroreflex-induced heart rate (HR) and blood pressure (BP) response to forced breathing against 40 mmHg intrathoracic pressure for 15 s. This study demonstrates the ValsalvaAnalyzer software, which combines modeling and data analysis to extract biomarkers from time-series BP and electrocardiogram (ECG) data. The software, programmed in MATLAB, incorporates a graphic user interface, making data analysis and mathematical modeling predictions accessible to clinicians. The software&#160;calibrated for PCs and Macs&#160;reads ECG and BP data measured during the VM. It automatically identifies R and S peaks in the ECG signal, with integrated user verification to ensure the accuracy of the captured signals. The RR intervals are used to predict HR, and the QRS complex magnitude changes are used to predict respiration. Systolic and diastolic BP are captured, and the user identifies the onset and VM duration from the SBP. The software automatically detects the four VM phases and the intrathoracic pressure. The latter is obtained by merging the respiratory signal at rest with the 40 mmHg pressure the subject breathes against during the VM. The most commonly reported clinical VM markers computed from the HR and BP data are reported along with estimates of patient-specific parameters obtained using a differential equations model, which predicts sympathetic and parasympathetic dynamics. The final output, over 35 metrics, includes BP and HR, maximum and minimum HR, the Valsalva ratio, and measures of baroreflex sensitivity, all saved to a spreadsheet. The software is intended to analyze the VM data, but the methodology can be extended to other autonomic tests. Its strength lies in combining quantities extracted from raw data with model outputs, augmenting clinical data with a mathematical model providing insight into autonomic immeasurable quantities.

The eight example datasets are selected to represent a diverse range of responses. Figure 3, Figure 4, Figure 5, Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, and Figure 11 present the results from a representative healthy control subject for each ste...

The ValsalvaAnalyzer software includes functions to analyze continuous beat-to-beat electrocardiogram and blood pressure (BP) measurements recorded during the Valsalva maneuver (VM). The computed clinical biomarkers and estimated model outputs provide insight into sympathetic and parasympathetic regulation of heart rate and BP during the VM.

The Valsalva Maneuver (VM) is a low-risk highly accessible test that measures the baroreflex-induced heart rate (HR) and blood pressure (BP) response to ...

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We have developed a Semi-automated Optical Heartbeat Analysis method (SOHA) for analyzing high speed optical recordings from Drosophila, zebrafish and embryonic mouse hearts. We demonstrate the application of our methodology to the analysis of heart function in fruit fly and embryonic mouse hearts.

Semi-automated Optical Heartbeat Analysis of Small Hearts

Standardized, comprehensive and fully quantitative testing of autonomic functions is described. The autonomic tests consist of evaluation of all three major autonomic domains including cardiovagal, adrenergic and sudomotor. The severity and distribution of dysautonomia is quantitated using Composite Autonomic Severity Scores.

Quantitative Autonomic Testing

Here, we show the generation of human engineered heart tissue from induced pluripotent stem cells (hiPSC)-derived cardiomyocytes. We present a method to analyze contraction force and exemplary alteration of contraction pattern by the hERG channel inhibitor E-4031. This method shows high level of robustness and suitability for cardiac drug screening.

Automated Contraction Analysis of Human Engineered Heart Tissue for Cardiac Drug Safety Screening

We demonstrate a 24 h heart rate recording methodology to evaluate the influence of concussion across the recovery trajectory in youth athletes, within an ecologically valid context.

Autonomic Function Following Concussion in Youth Athletes: An Exploration of Heart Rate Variability Using 24-hour Recording Methodology

This protocol describes a method for calculating Heart Rate Variability (HRV) from electrocardiogram (ECG) waveforms. Waveforms from continuous heart rate (HR) recordings during active video game (AVG) sessions were used to measure the aerobic performance of youth with cerebral palsy (CP).

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions

The goal of the protocol is to guide researchers in conducting experiments that are intended to measure changes in self-reported emotional response and heart rate variability following art making with different materials. The protocol can easily be adapted for use in a variety of behavioral conditions and activities.

Examining Changes in HRV and Emotion Following Artmaking with Three Different Art Materials

We present protocols and methods of analyses to build co-adaptive interfaces that stream, parameterize, analyze, and modify human body and heart signals in close-loop. This setup interfaces signals derived from the peripheral and central nervous systems of the person with external sensory inputs to help track biophysical change.

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

The baroreflex is a heart-rate regulation mechanism by the autonomic nervous system in response to blood-pressure changes. We describe a surgical technique to implant telemetry transmitters for continuous and simultaneous measurement of electrocardiogram and blood pressure in mice. This can determine spontaneous baroreflex sensitivity, an important prognostic marker for cardiovascular disease.

Implantation of Combined Telemetric ECG and Blood Pressure Transmitters to Determine Spontaneous Baroreflex Sensitivity in Conscious Mice

This study describes a comprehensive cardiovascular magnetic resonance imaging (CMR) protocol to quantify the left ventricular functional parameters of the mouse heart. The protocol describes the acquisition, post-processing, and analysis of the CMR images as well as assessment of different cardiac functional parameters.

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging

Electrocardiogram (ECG) is the key variable to understanding cardiac electrophysiology. Physical exercise has beneficial effects but may also be harmful in the context of cardiovascular diseases. This manuscript provides a method of recording real-time ECG during exercise, which can serve to investigate its effects on cardiac electrophysiology in mice.

Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice

The BrainBeats toolbox is an open-source EEGLAB plugin designed to jointly analyze EEG and cardiovascular (ECG/PPG) signals. It includes heartbeat-evoked potentials (HEP) assessment, feature-based analysis, and heart artifact extraction from EEG signals. The protocol will aid in studying brain-heart interplay through two lenses (HEP and features), enhancing reproducibility and accessibility.

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

Learn to analyze ECG and blood pressure time-series data from the Valsalva maneuver using ValsalvaAnalyzer software. This computational tool extracts cardiovascular biomarkers for autonomic dysfunction diagnosis.

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

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