You’re crawling along the ridge, 6000 feet above the ground. Below, dark abyss. Your hands begin to stiffen into useless claws, cold air is burning in your lungs. “Careful now, watch out” – it’s just a few more pulls until you reach the top. While you force your way up, taking one nub of rock at a time, you can hardly breathe as sweat pearls are running down your face. The harrowing fear of losing grip is making your mind spin…
As you switch off the TV in the comfy, sheltered atmosphere of your living room, you still feel the rage of your heartbeat, the dryness of your mouth and eyes. With sweaty hands, you reach for a glass of water and can’t help but chuckle to yourself, baffled by the plain fact that time and again it seems to take as little as some gripping pictures to give you the creeps, send chills down your spine and do some more things to your body that are obviously beyond your conscious control…
One of the most sensitive markers for emotional arousal is galvanic skin response (GSR), also referred to as skin conductance (SC) or electro-dermal activity (EDA). EDA modulates the amount of sweat secretion from sweat glands. The amount of sweat glands varies across the human body, being highest in hand and foot regions (200–600 sweat glands per cm2). While sweat secretion plays a major role for thermoregulation and sensory discrimination, changes in skin conductance in hand and foot regions are also triggered quite impressively by emotional stimulation (Boucsein, 2012): the higher the arousal, the higher the skin conductance. It is noteworthy to mention that both positive (“happy” or “joyful”) and negative (“threatening” or “saddening”) stimuli can result in an increase in arousal – and in an increase in skin conductance.
Skin conductance is not under conscious control. Instead, it is modulated autonomously by sympathetic activity which drives human behavior, cognitive and emotional states on a subconscious level. Skin conductance therefore offers direct insights into autonomous emotional regulation. It can be used as alternative to self-reflective test procedures, or – even better – as additional source of insight to validate verbal self-reports or interviews of a respondent.
Exemplary GSR time course during an episode of “Breaking Bad” as visualized in iMotions Biometric Research Platform. Synchronized screen capture and facial video streams provide additional information on emotional states of the respondent.
Skin conductance is captured using skin electrodes which are easy to apply (such as the Shimmer GSR+ module). Data is acquired with sampling rates between 1 – 10 Hz and is measured in units of micro-Siemens (μS). The time course of the signal is considered to be the result of two additive processes: a tonic base level driver, which fluctuates very slowly (seconds to minutes), and a faster-varying phasic component (fluctuating within seconds). Changes in phasic activity can be identified in the continuous data stream with bare eyes as these bursts have a steep incline to a distinctive peak and a slow decline to baseline level. Whenever investigating GSR signal changes in response to sensory stimuli (images, videos, sounds), researchers focus on the latency and amplitudes of the phasic bursts with respect to stimulus onset. This is also referred to as Event-Related Skin Conductance Response (ER-SCR). Interestingly, changes in GSR can also be described within a longer time interval, e.g., while watching a video or movie. In that case, Non-Stimulus-locked Skin Conductance Responses (NS-SCR) characteristics are analyzed such as number of peaks and inter-peak latencies within a longer time window in order to characterize a respondent’s emotional arousal.
Tyler et al. (2015) recently published results describing a significant reduction in arousal (as reflected by reduced modulations in skin conductance) by transdermal electrical neurosignaling. In their study, Tyler and team used iMotions Biometric Research Platform to monitor the changes in skin conductance. The synchronized acquisition of GSR with other sensors (such as optical heart rate, EEG or facial EMG) as well as video-based facial expression analysis opens completely new horizons towards multimodal experimental setups and cross-sensor analysis strategies which provide insights into the interaction of autonomous processes and higher cognitive-behavioral systems.
A screenshot from Ledalab (a freely available MATLAB toolbox for the analysis of GSR data). The toolbox decomposes the continuous data into a tonic base component (brown) and a phasic component (blue), which is sensitive to emotional stimuli (red vertical lines).
Please contact the team at iMotions if you have any questions regarding GSR or biometric research.
If you would like to read more about the theory behind skin conductance, its applications and analysis, we recommend the following resources:
- Boucsein, W. (2012). Electrodermal Activity. New York, Berlin: Springer, 2nd edition. (link)
- Benedek, M., & Kaernbach, C. (2010). Decomposition of skin conductance data by means of nonnegative deconvolution. Psychophysiology, 47, 647–658. doi:10.1111/j.1469-8986.2009.00972.x (link)
- Benedek, M., & Kaernbach, C. (2010). A continuous measure of phasic electrodermal activity. Journal of Neuroscience Methods, 190, 80–91. doi:10.1016/j.jneumeth.2010.04.028 (link)
- LEDALAB. A MATLAB toolbox for GSR analysis. (link)
If you have any questions on how iMotions can help with your GSR research please feel free to contact us.