Does your smartwatch know how you feel? An experience sampling study into intra-individual correlations between bodily signals and experienced emotions.
Type of assignment? Master
Internal or external? Internal
How many students possible? 3
Own data collection or existing data? Existing data
Type of research: Quantitative
EC (10 of 30EC)? 10 EC, 30EC is also possible, but then own data collection will be added.
Wearable technology is becoming available, for example the Apple Watch, that allow consumers to measure their own physiological signals (e.g. heart rate) and potentially share them with others. In many cases, fluctuations in these physiological signals are operationalized by the wearable technology to some kind of human experience: The device is measuring your heart rate, but it would indicate your stress levels on its screen or a coupled smartphone. This operationalization might seem logical, but empirical studies and theories on psychophysiology and human emotion show and theorize that these kind of substitutions are problematic (Feldman Barrett & Simmons, 2015; Evers et al., 2014; Fairclough, 2009). Technology journalists are also becoming critical on the one-to-one substitution of physiology with psychology (see for example: http://www.techradar.com/news/is-stress-tracking-the-future-of-well-being-tech).
In this study you will examine what fluctuations in self-reported experience of people best predicts the physiological signals that are captured by a wearable bio-sensor. This watch-like bio sensor (although it doesn’t tell you the time) can measure both heart rate and skin conductance (Fletcher, Poh, & Eydgahi, 2010). These two signals capture the activity of different parts of the human nervous system to a different degree. Skin conductance, for example, is supposed to mostly capture the activity of the sympathetic part of the autonomic nervous system (Boucsein, 2012). This part of the nervous system is very often associated with the arousal dimension of emotion within dimensional theories of emotion (Russell, 2009). However, a limited amount of studies have systematically tested whether such an operationalization makes sense in people’s daily lives.
Who are we looking for?
Enthusiastic students who are interested in the way the everyday human experience of emotion is related to bodily signals.
Dr. Matthijs Noordzij
Barrett, L. F., & Simmons, W. K. (2015). Interoceptive predictions in the brain. Nature Reviews Neuroscience, 16(7), 1–11.
Boucsein, W. (2012). Electrodermal Activity (2nd ed.). New York, NY, USA: Springer.
Evers, C., Hopp, H., Gross, J. J., Fischer, A. H., Manstead, A. S. R., & Mauss, I. B. (2014). Emotion response coherence: A dual-process perspective. Biological Psychology, 98(1), 43–49.
Fairclough, S. H. (2009). Fundamentals of physiological computing. Interacting with Computers, 21(1–2), 133–145. https://doi.org/10.1016/j.intcom.2008.10.011
Fletcher, R. R., Poh, M. Z., & Eydgahi, H. (2010). Wearable sensors: Opportunities and challenges for low-cost health care. 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC’10, 1763–1766.
Russell, J. A. (2009). Emotion, core affect, and psychological construction. Cognition and Emotion, 23(7), 1259–1283.