Electrodermal Archives

Skin Deep: Using EDA to Measure Affective Response

We say something “gets under our skin” when it elicits an unpleasant or irritating emotional response. This connection between our skin and emotion runs deeper than a simple idiomatic expression, however. Along with performing several critical functions—protective, regulatory, and sensory—our skin provides a window into our physiological and emotional states as we respond to a range of stimuli. Electrodermal Activity (EDA) is the mechanism providing these insights.

EDA, also known as galvanic skin response (GSR), measures eccrine activity resulting from the sympathetic nervous system’s response to environmental stimulation. As a function of the autonomic nervous system, it is an involuntary response to a range of sensory inputs, including touch, sight, sound, odor, and taste. EDA regulates the rate of sweat produced by sweat glands in the extremities, particularly in the fingertips, palms, and soles of the feet.

EDA increases in conjunction with the level of stress or nervousness experienced by an individual. For this reason, it provides researchers with a valuable means of measuring affective response to external stimuli. As we explored in a previous post, affect is the measurable physiological expression of emotion. While there are numerous physiological signals that researchers can employ to measure affect, EDA in particular functions as an indicator of arousal. For this reason, EDA has become one of the most relied upon signals employed by researchers exploring psychophysiological phenomena.

A recent Slovakian study published in Adaptive Human Behavior and Physiology illustrates how EDA is commonly employed in such research. Researchers studying the influence of gender differences on reaction to violent imagery used skin conductivity response (SCR), the mechanism behind EDA, to measure levels of arousal when participants were shown images of war and sports. The goal of the study was to test the “male warrior hypothesis” (MWH). The theory suggests that men have evolved psychological mechanisms to form aggressive alliances with the goal of acquiring or protecting reproductive resources in war and that team sports stimulate that same impulse. EDA was measured using BIOPAC electrodes and leads feeding data to an MP36 data acquisition unit. While the study found that visual perception of team sports and war imagery stimulated different levels of excitement as measured by EDA in men and women, it was inconclusive in showing that sports provide a substitute for war in the sample of participants.

A study conducted at the University of Ottawa and published in the Journal of Behavior Therapy and Experimental Psychiatry used EDA to examine whether response-focused emotion regulation (RF-ER) strategies provided an effective way to control evoked emotions—specifically, does smiling make one feel better in times of heightened stress? EDA data was gathered from participants using a BIOPAC skin conductance transducer and amplifier connected to a BIOPAC data acquisition unit while participants were shown images designed to evoke both arousal and negative responses. Participants were asked to either suppress their emotional response to images or employ expressive dissonance (e.g., smile when disturbed). The results of the study shed doubt on previously held assumptions that RF-ER strategies were effective in controlling emotion.

These are just a sampling of the ways in which EDA is being used in psychophysiological research. For additional information on the background, tools, and techniques for using EDA in your studies, visit our EDA Resource Directory, read our EDA Introductory Guide. and watch Electrodermal Activity: Intro to Recording and Analysis or any of our EDA webinars.

For additional information on how BIOPAC can assist you with your research using EDA and a range of other physiological signals, contact your local sales representative.

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.

Electrodermal Activity (EDA)

Typically, EDA is measured as skin conductance and a small direct constant voltage (0.5 vdc) is used as excitation source across the skin electrodes.

By Alan Macy, BIOPAC Systems, Inc.

Electrodermal activity measurement is subject to electrically-related characteristics of the skin. There are two phenomena associated with this type of skin activity. One is skin potential, which is a self-generated potential intrinsic to the skin. This potential is a consequence associated with dissimilar skin layers placed in proximity coupled with the presence and movement of interstitial fluids. An evoked skin potential response is called the sympathetic skin response. This change in skin potential can be evoked by electrical, auditory or magnetic stimulation. The other phenomenon associated with skin electrical activity can be measured when a stimulation (excitation) current is injected through, or a voltage is applied across, attached skin electrodes. The current or voltage stimulation is typically at constant (DC) level, or at low frequency, because the skin impedance is high. The application of excitation current or voltage produces a corresponding voltage or current, respectively, that changes over time subject to physiological state. In these cases, the skin’s resistance, impedance, conductance or admittance is being measured, corresponding to the type of electrical stimulation used.

EDA Measurements – subject to electrical excitation type:

Skin Resistance – Direct Constant Current (not commonly used)

Skin Conductance – Direct Constant Voltage (most commonly used)

Skin Impedance – Alternating Constant Current (not commonly used)

Skin Admittance – Alternating Constant Voltage (sometimes used)

Typically, EDA is measured as skin conductance and a small direct constant voltage (0.5 vdc) is used as excitation source across the skin electrodes. The skin admittance method (alternating constant voltage excitation) may provide some advantages in measurement in that this method does not polarize the skin electrodes during EDA recording. Skin conductance is usually measured in units of “Siemens” although sometimes “mho” is used. The unit “mho” comes from the reverse spelling of “ohm”, the unit of resistance. One mho equals one Siemen. The conductivity of the skin is small, so values are given in microsiemens (uS) or micromhos (umho).

Changes in the electrically-related characteristics of the skin is correlated to eccrine sweat gland activity. Eccrine glands are in nearly all skin locations and are found, in highest concentrations, on the palms of hands, fingertips and soles of the feet. EDA, measured as skin conductance, is a physiological signal that indicates increased sympathetic nervous system (SNS) activity. This aspect of 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.

There are two aspects to skin conductance measurements, namely phasic and tonic. Tonic value is the average skin conductance level (SCL), that is relatively consistent over time, and is related to arousal. The phasic component of skin conductance is the change of the skin conductance, over a short time period, in reaction to a stimulus. For a skin conductance response (SCR), the skin conductance rises in a short time period and then returns to tonic levels. SCRs are characterized by four different parameters: the response peak amplitude, latency of response, rise time to the response peak, and recovery time after peak.

For more information on BIOPAC’s EDA research solutions, including real-time live raw EDA data as well as real-time filtering or calculation channels including High-pass filtered/AC Coupled EDA, visit BIOPAC’s EDA Analysis page or view BIOPAC’s full line of electrodes, amplifiers, and wearable, wireless transmitters and loggers.

Additionally, a link to a recently updated EDA SCR Analysis Guide for Psychological Experiments came be found here.