What can Pro Lab galvanic skin response metrics tell us?

Tobii Pro Lab

Learn how to interpret the galvanic skin response measures provided by Tobii Pro Lab.

GSR can add valuable insights to your eye tracking experiment about the emotional arousal state of a participant during various situations. Pro Lab offers a set of GSR metrics that are frequently used to quantify skin conductance responses (SCRs) and arousal levels during an experiment. The type of research question and experimental design will determine which GSR metrics are more appropriate to answer your research question.

Pro Lab provides two SCR-related metrics: ER-SCR amplitude and SCR count. An SCR is a temporary increase of the GSR signal amplitude that gives information about what specific moments caused an emotional response within the participant. When an SCR happens between 1 and 5 seconds after an event, the SCR is then classified as an event-related SCR (ER-SCR) and the amplitude of the SCR gives an indication of the intensity of the emotional response towards the event. Examples of where SCR-related metrics are useful to get insights about the emotional reactions are:

  • To learn if certain stimulus condition (e.g. threatening stimuli) caused larger ER-SCR than another stimulus condition (e.g. neutral stimuli), or if a group of participants (e.g. a high anxiety group) had larger ER-SCR than another group of participants (e.g. a control group) to certain stimulus. The GSR metric ER-SCR amplitude can help answer these types of research questions by comparing the ER-SCR amplitude, magnitude and frequency between conditions.
  • To identify what specific moments of a dynamic stimulus, such as a video or shopper journey, caused emotional responses in the participants. SCR count can help identify these moments by comparing the number of SCRs in different moments during the experiment.


Pro Lab also provides a metric related to the general emotional arousal state of a participant: GSR average. When environmental conditions are kept constant, the slow fluctuations in the GSR signal (tens of seconds to minutes) reflect changes in the emotional arousal level of a participant. The researcher can use the GSR average metric to determine if a participant is getting stressed, frustrated or relaxed during the course of the test session. Examples of where the GSR average metric is useful to get insights about general emotional arousal levels are:

  • To evaluate stress level changes over different tasks that study aspects of human behavior (e.g. in a decision-making study).
  • To get an indication of the frustration level and task difficulty (e.g. in a web usability study).
  • To get an indication of the level of relaxation during the course of an experiment.


Besides the three metrics described thus far, the Data Export function of Pro Lab offers access to raw or filtered GSR data as well as information about the onset and peak time of all the SCRs in the data. The researcher can use this information to calculate additional metrics based on individual needs. Examples of additional metrics include, a list of all SCRs and their main parameters, and data standardization calculations or ratio of non-specific SCR per participant (NS-SCR).

Finally, due to the GSR signal characteristics, there are a few points that a researcher must consider to ensure the GSR results are statistically valid to answer their research question. These include:

  • Data normalization: We advise to perform some simple transformation to GSR metrics so that the results fit a normal data distribution and the researcher can apply parametric statistical analyses. The most common transformations are to compute the Log or square-root of the SCR amplitude, the Log of the GSR average and the Log of ER-SCR magnitude + 1.
  • Absolute or relative GSR metrics : The GSR signal has large individual differences. This means that the same SCR amplitude could be considered as a large response for one participant and small response for another. It is important to use relative GSR metrics values if the experimental design includes comparing GSR metrics between different groups (between-subject design). The two most common approaches to standardize are based on the calculation of maximum and minimum GSR values, and on Z-scores (mean and standard deviation of GSR metrics). The researcher can use absolute GSR metrics as long as the experimental design dictates that all participants have experienced all the conditions in the experiment (within-subject designs).

References & Recommended Reading

  • Boucsein, W. 2012. Electrodermal activity. Springer Science & Business Media.
  • Roth, W. T., Dawson, M. E., & Filion, D. L. 2012. Publication recommendations for electrodermal measurements: Publication standards for EDA. Psychophysiology, 49(8), 1017–1034. https://doi.org/10.1111/j.1469-8986.2012.01384.x

 

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