TREV Q&A: Unpacking Trans-radial Electrical Bioimpedance Velocimetry

As researchers look for cleaner, more direct ways to capture sympathetic nervous system (SNS) activity, Trans-radial Electrical Bioimpedance Velocimetry (TREV) has emerged as a powerful new approach for measuring beat-by-beat changes in cardiac contractility to index sympathetic drive.headshot To explain how the technique works and where it fits alongside more established measures, we sat down with Viktoriya Babenko, PhD, BIOPAC’s in-house TREV expert and research specialist. Babenko helps researchers implement advanced cardiovascular and autonomic measurements, combining her extensive hands-on experience with bioimpedance technologies and a strong grounding in the interpretation of physiological signals. In the Q&A below, she describes the physiological principles behind TREV, how it differs from traditional electrodermal activity (EDA), electrocardiogram (ECG), and impedance cardiography (ICG) approaches, and why it offers a uniquely direct and practical window into sympathetic drive for both laboratory and neuroimaging research.

At a high level, what is Trans-radial Electrical Bioimpedance Velocimetry (TREV), and what does it measure?

TREV is a noninvasive method for estimating cardiac contractility as a continuous, beat-by-beat index of SNS activity. Rather than measuring bioimpedance across the chest like traditional ICG, TREV measures impedance changes across the radial and ulnar arteries of the forearm.

As the heart contracts, it generates a pressure wave that travels through the arterial system and causes red blood cells to momentarily align. This alignment reduces electrical resistance in the blood, which TREV continuously tracks. The impedance signal measured by TREV provides velocity, acceleration, and ultimately a contractility index, where stronger contractions reflect greater sympathetic drive.

Why is cardiac contractility such a useful index of SNS activity?

Cardiac contractility reflects the vigor with which the heart contracts during each heartbeat and is strongly modulated by sympathetic tone, either through direct neural innervation or circulating catecholamines like epinephrine. Increased sympathetic activation leads to stronger, faster contractions, while reduced sympathetic drive results in weaker contractile force.

Because of this close physiological relationship, contractility is considered one of the most direct and objective noninvasive measures of SNS activity. Unlike heart rate alone, which reflects both sympathetic and parasympathetic influences, contractility provides a more targeted window into sympathetic drive specifically.

How does TREV differ from traditional ICG- or ECG-based approaches?

Traditional approaches for indexing sympathetic drive, such as combining ECG and thoracic ICG to extract the pre-ejection period (PEP), are powerful but complex. They typically require 10 electrodes placed across the neck, chest, and torso, along with careful preprocessing and time-based feature extraction between both ICG and ECG to get PEP.waveform

TREV dramatically simplifies this process by using just four strip electrodes placed on the forearm. The resulting contractility waveform produces a single sharp peak per heartbeat, where the amplitude directly reflects contractile strength. Analysis is as simple as extracting peak amplitudes, rather than identifying precise timing relationships across ECG and ICG signals, making TREV faster to set up and easier to analyze.

What is the physiological rationale for using the forearm and radial and ulnar arteries as the measurement site?

The radial and ulnar arteries provide a relatively simple and accessible vascular model that is well-suited for bioimpedance measurements. When the heart contracts, a pressure wave propagates rapidly through the arterial tree and reaches the forearm, aligning red blood cells even before bulk blood flow arrives.

This pressure-wave-driven alignment is sufficient to cause measurable drops in impedance, allowing TREV to estimate cardiovascular dynamics without the anatomical and physiological complexity of the thorax. Measuring at the forearm also reduces sensitivity to respiratory and pulmonary effects that complicate thoracic impedance measurements.

What cardiovascular or hemodynamic parameters can be derived from TREV?

TREV provides estimates of blood velocity, acceleration, and the integral of velocity (blood position) derived from the impedance waveform. Most importantly, the second derivative of the impedance signal yields a contractility index (blood flow “jerk”) that reflects sympathetic modulation of the heart on a beat-by-beat basis.

While multiple parameters are available, BIOPAC primarily recommends TREV as a tool for tracking cardiac contractility over time, particularly in studies interested in stress, arousal, motivation, and cognitive or emotional processes linked to sympathetic activation.

What does a typical TREV measurement session look like, from setup to data output?equipment

Once the arm is clean and dry, four hydrogel strip electrodes (EL526) are placed on the forearm and connected via the CBL246 adapter to the NICO100D system. I recommend watching the TREV Webinar titled “A Simple Next-Gen Method for Stress Research: TREV” for step-by-step guidance on electrode placement.

During data collection, the participant’s arm must remain fully supported and relaxed, ideally with the elbow and forearm stabilized through the wrist to minimize muscle activity. When collected under proper conditions, TREV produces a clean, continuous contractility waveform with one peak per heartbeat, allowing for straightforward beat-by-beat analysis of sympathetic drive.

What advantages does TREV offer compared to ECG, EDA, or other stress-related measures?

Many commonly used physiological signals, such as heart rate, blood pressure, or heart rate variability, are influenced by multiple factors, including hydration, temperature, respiration, and both branches of the autonomic nervous system (parasympathetic and sympathetic nervous systems). EDA provides a sympathetic index, but it is relatively slow, delayed, and indirect, reflecting eccrine sweat gland activity modulated by the SNS rather than cardiovascular dynamics.

TREV fills an important gap by offering a fast, dynamic, and more direct measure of sympathetic drive through cardiac contractility. It combines the physiological specificity of ICG-derived measures with a much simpler setup and analysis pipeline, making it especially attractive for experimental and applied research settings

What are the main challenges in acquiring clean, interpretable TREV data?

The primary challenge with TREV is its sensitivity to motion artifact. Muscle activity in the forearm generates electromyography (EMG) signals that are much larger than the impedance changes of interest and can easily overwhelm the TREV signal.

For this reason, careful experimental control is essential. The participant’s arm should be fully supported, relaxed, and free from movement or strain, while other body movements are generally permissible. When these conditions are met, TREV data quality is excellent, but the method does demand attention to posture and comfort.

In what research or applied settings is TREV showing the most promise?

TREV is particularly well-suited for research at the intersection of stress, cognition, emotion, and autonomic physiology. It has been successfully used in laboratory studies examining sympathetic responses to cognitive and emotional stressors, as well as in MRI environments to enable the simultaneous study of neural activity and SNS dynamics.

Across both standard laboratory settings and neuroimaging environments, TREV provides a continuous, beat-by-beat index of sympathetic activity, making it especially valuable for event-related experimental designs where precise timing and dynamic changes in autonomic responses are of interest. In the MRI specifically, this temporal resolution allows researchers to directly link moment-to-moment fluctuations in sympathetic drive with neural processes measured using functional MRI (fMRI), offering a powerful framework for studying how brain activity and cardiovascular sympathetic responses interact during task performance, affective processing, or stress-related appraisals. As with most MRI-based physiological measurements, specific hardware configurations and safety considerations apply, and researchers should contact the BIOPAC support team before data collection to ensure proper setup and compliance.

How does TREV perform in dynamic or real-world conditions, such as movement or exercise?

At present, TREV performs best in controlled conditions where the forearm can remain fully supported and at rest. Simple movements while seated may be permissible, provided that the arm containing the TREV electrodes remains immobile and relaxed. Due to its sensitivity to motion, TREV is not currently recommended for continuous data collection during active movement or exercise.

That said, TREV can still be extremely valuable in movement- or exercise-related research by comparing pre- and post-task states. This approach allows researchers to quantify sympathetic changes associated with physical or psychological challenges without collecting data during movement itself.

Looking ahead, how do you see the TREV method evolving over the next five to ten years?

As validation studies continue and more researchers adopt the method, TREV is likely to become a standard tool for indexing sympathetic drive in both basic and applied research. Ongoing work, including peer-reviewed publications, will further refine interpretation, best practices, and experimental design considerations.

In the longer term, improvements in signal processing, hardware integration, and multimodal data collection may expand TREV’s use into more naturalistic settings, helping bridge the gap between controlled laboratory studies and real-world physiological monitoring.


If you are planning a study and would like to learn more about integrating TREV, our team of experts can help guide you to the right equipment and strategies.

Related posts: Body Electrictric: Bioimpedance in Physiology Research and ‘Tis the Season for Stress: Research Tools for Anxious Times

Circumplex Model of Affect and Motivational State

By Alan Macy, BIOPAC Systems, Inc.

The Circumplex Model of Affect was first described in 1980 by James Russell. Affective states arise from the behavior of two independent neurophysiological systems, the arousal and valence systems. Affective states are a function of these two systems. The circumplex model is two-dimensional, with arousal and valence defined as orthogonal (perpendicular) axes. The arousal axis, plotted vertically, ranges from zero arousal to high arousal.The valence axis, plotted horizontally, ranges from negative to positive. Objective physiological indexes of affect or emotion are available. As valence examples, positive affect is indicated by increasing zygomaticus activity and negative affect is indicated by increasing corrugator activity. Physiological example indices for arousal include heart rate and electrodermal activity.

Perhaps even more fundamental to emotional state is the concept of motivational state. Motivational state is indexed by specific, bodily expressed, physiological states that can easily be measured. Motivational state is based on the concept of core relational themes, called “challenge” and “threat”.  During the course of living, humans relate to difficult environmental circumstances as a combination of challenge and threat. A challenge response is similar to the aerobic physiological response and involves increased stroke volume and cardiac output, unchanged or increased heart rate, decreased vascular resistance and relatively unchanged blood pressure. This response is indicative of efficient mobilization of available energy for coping with circumstances. A threat response is characterized by increased heart rate and blood pressure, increased or little changed vascular resistance, decreased or unchanged stroke volume and relatively unchanged cardiac output. A challenge response occurs when the subject experiences sufficient resources to meet circumstantial demands in a performance situation where goals are important. A threat response occurs when the subject experiences insufficient resources to meet those same circumstantial demands. If a circumstance is determined to be challenging, then subject performance is usually adequate. If a circumstance is determined to be threatening, then subject performance tends to worsen. Motivational state information can be used to better reflect objective differences between similar circumplex model defined emotions, such as anger and fear.

Electrodermal activity (EDA) is a physiological signal that indicates increased SNS activity. EDA is representative of changes in the electrical conductance of the skin due to eccrine (sweat) gland activity. SNS activity increases sweat gland secretions. Eccrine glands only receive activation signals from the SNS, so increased EDA is an indicator of increased arousal.

Skin temperature (SKT) changes are primarily driven by variations in blood flow. These local variations are mainly caused by changes in vascular resistance or arterial blood pressure. Local vascular resistance is modulated by smooth muscle activity, which is mediated by the SNS. SKT variation reflects SNS activity, and is an indicator of emotional state.  In particular, fingertip temperature is a marker for sympathetic induced changes in microcirculation.

Blood Volume Pulse (BVP), also referred to as the Pulse Plethysmogram (PPG), is reflective of variations in microcirculation. As vasculature resistance to flow increases, subject to increased SNS, microcirculation decreases. Accordingly a reduction in PPG (BVP) amplitude reflects increased SNS activity.

The heart and brain are connected bidirectionally via the vagus nerve. Vagal PsNS stimulation, from the brain, influences the heart via the sino-atrial (SA) node. Baroreceptor signals, from the heart, travel back along the vagus nerve to affect the brain. The SA node is the pacemaker of the heart. The SA node receives inputs from both the SNS and PsNS. The SA node can be considered to be a spike-train generator whose inter-spike (firing) interval is modulated by both SNS and PsNS activity levels. Because both SNS and PsNS activity influence SA node spike firing, heart rate behavior can be considered to be dependent on a range of emotional states. SNS activity increases heart rate and PsNS activity decreases heart rate.

Heart rate variability (HRV) is a measure of heart rate changes over time. HRV has a frequency range of 0.003 to 0.4 Hz and is considered to have four sub-bands:  HF, LF, VLF and ULF. High frequency HRV (HF-HRV) band power is in the range of 0.18 to 0.4 Hz and reflects primarily PsNS influences. HF-HRV band power reflects modulation of vagus nerve activity, as driven by respiration. This modulation is called respiratory sinus arrhythmia (RSA). Low frequency HRV (LF-HRV) band power is in the range of 0.05-0.15 Hz and appears to reflect both SNS and PsNS influences. Very low frequency HRV (VLF-HRV) band power is in the range of 0.003-0.05 Hz and may reflect cardiovascular disease, thermo-regulatory cycles and blood plasma renin activity. Ultra low frequency HRV (ULF-HRV) band power is in the range of DC-0.003 Hz and may reflect circadian rhythm activity.

PsNS influences occur over the LF and HF frequency ranges of HRV. SNS influences drop off at about 0.15 Hz and higher. PsNS influences can affect heart rate in a fraction of a second, but SNS influences can only affect the heart rate after a few seconds. Accordingly, PsNS influences are uniquely capable of producing high speed changes in the heart rate. PsNS innervation of the heart is controlled by the right vagus nerve via the SA node. PsNS induced changes in heart rate are associated with vagal nerve activity that is modulated by respiration. Expiration causes an increase in vagal nerve activity, so heart rate decreases. Inspiration causes suppression of vagal nerve activity, so heart rate climbs back up. This combined action is known as respiratory sinus arrhythmia (RSA). RSA is considered, in part, to be a marker for vagal control of heart rate and also for emotional regulation. Total HRV appears to be positively correlated with valence.

When attention increases, there is a short term deceleration of heart rate. Arousal is also correlated to a long term acceleration in heart rate. Heart rate also provides an indication of valence. Compared to neutral stimuli, both positive and negative stimuli first exhibit a short term decrease in heart rate. Over the long term, positive stimuli are correlated with an increase in heart rate while negative stimuli usually are correlated to a decrease in heart rate.

Respiratory activity occurs via periodic contraction and relaxation of respiratory muscles, including the diaphragm, intercostal and abdominal muscles. The motor outputs for controlling respiration are generated by efferent neurons in the spinal cord.  There are autonomic and voluntary breathing pathways to these respiratory-related efferent neurons. A variety of afferent (sensory) inputs influence respiratory rate and tidal volume in support of the body’s metabolic demands. SNS activity increases respiratory rate and PsNS activity reduces respiratory rate.

Several EEG studies suggest that emotional valence is linked to frontal lobe activation, typically indexed by alpha power. Positive valence is correlated to increased activation of  the left frontal lobe and negative valence is correlated to increased activation of the right frontal lobe.  Other studies have suggested that frontal lobe EEG activation asymmetry reflects the relative balance of motivational state, more so than emotional valence.  In this work, enhanced left frontal lobe activation predicted dispositional states towards challenge and enhanced right frontal lobe activation predicted dispositional states towards threat.

Artwork adapted from from Russell, J. A. (1980). A circumplex model of affect.Journal of Personality and Social Psychology, 39, 1161–1178.

For more information on BIOPAC’s wide range of tools for recording, displaying, classifying, and analyzing psychophysiological measurements—including EEG, ECG, EDA, PPG, and emotional states—visit BIOPAC’s applications pages and view BIOPAC’s full line of physiology data acquisition and analysis systems, electrodes, amplifiers, and wearable, wireless transmitters and loggers.

BIOPAC Systems, Inc. provides life science researchers and educators with data acquisition and analysis systems that inspire people and enable greater discovery about life. Visit us at www.biopac.com.

 

error: Content is protected !!