Biometrics

Physiological Measurement in Practice with Dr. Wu

By Alyssa HanceApril 12th, 2024in Biometrics, Homepage

Researchers from any discipline are familiar with the question that can haunt the data collection process of an experiment: is the level of measurement used valid externally and internally?  How do you know your research measurements are capturing valid data from participants?

How a researcher chooses their method of data collection can come from a multitude of factors, like the researcher’s ontological and methodological standpoints, previous literature in the field, or the study design itself. A frequent method of measuring an individual’s response is through self-report measures.

Self-report measures are quite common in the field of communication research, and can be frequently seen through the use of surveys, in-depth interviews, and focus groups. While these methods are tested and validated throughout years of research across disciplines, validity can still be a concern when using this methodology. How does a researcher know individuals are reporting their responses accurately, and aren’t saying an answer they think the researcher wants to hear, or didn’t want to make a bad impression or want to be judged by their answer? To reduce potential limitations with self-report data, leveraging physiological measures can be used in-tandem to uncover another layer of participant data.

Physiological measures can provide a different angle of data by measuring emotional and cognitive responses through a participant'sThis is an image of a student using biometric to analyze a piece of data. biological response. Types of physiological measurement can include tracking eye movements, reading facial expressions, and gauging skin conductance- a measure that focuses on the microscopic sweat-level of the skin, noting a participant’s level of emotional response to a particular piece of media. This type of measurement can give researchers participants’ emotional and cognitive responses without social desirability or recall biases. But, like any other form of measurement, using biometric and physiological data are not without their own set of limitations. A physiological response can be caused by a variety of factors besides the chosen stimulus in a study, and may not even be a conscious act of the participant. A participant’s facial expression may change for no reason, and a sudden rise in skin conductance may be due to room temperature, or another external factor.

Here at the Communication Research Center (CRC), we are equipped with physiological devices and iMotions biometric software that are used by Boston University researchers to bring reliable data on a participant’s emotional and cognitive responses. COM professor Dr. Denis Wu’s recently published 2024 article, Physiological Response to Political Advertisement: Examining the Influence of Partisan and Issue Congruence on Attention and Emotion, published in the prestigious International Journal of Communication, highlights using biometrics to uncover another side of analysis CRC’s biometric tools.

This is a photo of Dr. Denis Wu.In his article, Dr. Wu combined surveys with facial analysis and eye-tracking data to analyze participant’s emotional and cognitive reaction to US political commercials during the 2016 election cycle. By using the CRC’s eye-tracking device and iMotions biometric software, Dr. Wu was able to identify participant’s facial expressions and attention levels to political advertisements through analyzing their eye movement activity. The study found that attention to the political advertisements influenced by the level of the ad aligning to the participant's preferred political party. Dr. Wu also found that participants' facial expressions were less negative than predicted, but were never “elated”.

Interestingly, Dr. Wu also found sections of self-report data and biometric eye tracking data were not perfectly aligned, nor self-reported emotions and facial expression data. This is an important observation, and can show that sometimes self-report measures and physiological measures can highlight different results. However, Dr. Wu makes an important observation: outside factors could be the cause of the different results, and researchers should not assume these different measures are not effective in research.

No form of measurement is without limitations, and there will always be questions of validity and accuracy when conducting research of any kind. However, combining self-report data with physiological measurements presents a deeper analysis of a participant’s reaction. The CRC is proud to have supported Dr. Wu in his recent article, and our physiological and biometric tools are used by graduate students and faculty in their research efforts. For more information on the tools available at the CRC, visit our biometrics page.

Letter from the Director: July 2022

Letter from the Director: July 2022

Demystifying Biometrics

As part of our mission, the Communication Research Center offers state-of-the art technology to facilitate our fellows’ ability to advance theory and methods in addressing society’s challenges. Some of this technology involves psychophysiological measurement and analysis tools. To help explain and demystify this technology, I’ve turned to the CRC’s Lab and Research Manager, Lindsy Goldberg.

Amazeen: "Biometric technology" sounds very avant-garde as does "psychophysiological measurements." How would you explain this technology in layperson's terminology?

Goldberg: I’ve found that the best way to explain these is to start by deconstructing and contextualizing the word “biometric”. When researchers choose to use these technologies, they’re looking to measure something biological in human subjects. In these particular cases, the bodily attributes we’re measuring are physiological in nature, which refers to a function of living organisms. Psychophysiology refers to the study of how physiological measurements that are collected via biometric devices (like heart rate, sweat levels in the skin, or eye movements) can explain psychological phenomena (Potter & Bolls, 2012).

This technology uses sensors to detect physical changes and movements in the human body. These sensors are able to detect a variety of different physical changes and these technologies are used widely across many academic disciplines. Here at the CRC we have sensors that measure skin conductance (SCL or electrodermal activity), eye movements both on and off screens, and brain waves (electroencephalography).

Biometric research has been occurring in the communication field since the latter half of the 20th century, mostly in media effects research or as part of a specific subfield known as media psychology, but this is changing. For decades, these biometric sensors were more invasive to participants and conducting experiments using this equipment required extensive training, monitoring, and in-person resources. It is very exciting to have these newer versions that are so much less invasive and user-friendly.

We are excited to be able to offer the devices, software for experimental design, execution, and analysis to researchers who are interested in using the technology.

Amazeen: Can you give examples of how these types of tools might be used (for what purposes) for media research?

Goldberg: In a media research context, these devices are most effectively used alongside self-report measures to gain a more comprehensive understanding of how a stimulus elicits a response in a participant.

These tools are most useful in situations where participants might be more likely to adjust their behavior based on what is expected of them or lie on a self-report instrument. Some potential examples of such situations might include but are certainly not limited to:

Assessment of opinions on political candidates based on their ads, sexual attraction to potential partners on dating apps, or stress responses to horror film scenes.

These tools, especially eye-tracking, are also gaining ground in fields such as UX/UI research and design. User eye movements and click behaviors on web pages and app layouts are becoming increasingly valuable.

Amazeen: Are there any cool studies you've seen published that have leveraged this technology?

Goldberg: While CRC fellows have not yet published any studies that leverage these technologies, here are some of my favorites from other institutions:

Ansani, A., Marini, M., D’Errico, F., & Poggi, I. (2020). How soundtracks shape what we see: Analyzing the influence of music on visual scenes through self-assessment, eye tracking, and pupillometry. Frontiers in Psychology, 11, 2242.

Millet, B., Chattah, J., & Ahn, S. (2021). Soundtrack design: The impact of music on visual attention and affective responses. Applied ergonomics, 93, 103301.

Ohme, J., Maslowska, E., & Mothes, C. (2021). Mobile News Learning—Investigating Political Knowledge Gains in a Social Media Newsfeed with Mobile Eye Tracking. Political Communication, 1-19.

Amazeen: Can you tell us about the certification you have and what that allows you to do?

Goldberg: With my iMotions certification, I am able to assist researchers who are interested in using biometric devices. This involves support and training in the iMotions software, which is digital experimentation software that allows you to run an entire experiment from one computer, including self-report measures.

I have the capability and knowledge base to not just assist in the use of devices, but also to train researchers on how to use the software and hardware, including helping to identify which psychophysiological measures may be most useful. I can also support data handling, visualization, and export.

Finally, we are very fortunate to have a relationship with iMotions and their brilliant customer support team, who are all researchers themselves. If there is a question I cannot answer or a request beyond what I can support, we have external resources that can also help.

Amazeen: Relatedly, does the CRC have any plans for offering training workshops for those interested in using this equipment?

Goldberg: Yes! I am currently working with iMotions to determine a training program design that fits our students and faculty. This equipment and software does take time to learn and requires a fair amount of diligent effort to execute a high quality experiment, but we do have plans to offer training sessions. Stay tuned!

 

Source: Potter, R. F., & Bolls, P. (2012). Psychophysiological measurement and meaning: Cognitive and emotional processing of media. Routledge.