Better living through affective computing

I recently read a paper by Rosalind Picard entitled “emotion research for the people, by the people.”  In this article, Prof. Picard has some fun contrasting engineering and psychological perspectives on the measurement of emotion.  Perhaps I’m being defensive but she seemed to have more fun poking fun at the psychologists than the engineers, but the central impasse that she identified goes something like this: engineers develop sensor apparatus that can deliver a whole range of objective data whilst psychologists have decades of experience with theoretical concepts related to emotion, so why haven’t people really benefited from their union through the field of affective computing.  Prof. Picard correctly identifies a reluctance on the part of the psychologists to define concepts with sufficient precision to aid the work of the engineers.  What I felt was glossed over in the paper was the other side of the problem, namely the willingness of engineers to attach emotional labels to almost any piece of psychophysiological data, usually in the context of badly-designed experiments (apologies to any engineers reading this, but I wanted to add a little balance to the debate).

The central argument of the paper (with which I’m in total agreement) is the question of why a lot of emotion research doesn’t really benefit anyone outside of the academic community.  Part of this problem is an unwillingness to move from the laboratory to study emotions in the field.  This trend is an artifact of the type of psychophysiology apparatus traditionally found in academia, most of which was designed for use exclusively in a laboratory; for a different perspective on how emotion can be studied in the field using ambulatory equipment, see this recent paper by Wilhelm and Grossman (2010).  The other artifact associated with psychological research is the way in which we tend to study people – generally psychologists (and psychology journal reviewers) favour a nomothetic approach; in other words, we study a lot of people, measure them once, work with group averages and try to develop a law of cause and effect that can be generalised to a broader population.  This is contrasted to the idiothetic perspective, which still exists as a minority perspective in psychophysiological research; in this case, we focus on the individual and data collection is repeated on several occasions.  Science (we are told) is about big numbers so it’s easy to see why the nomothetic approach trumps the idiothetic perspective in psychological research.


In her paper, Prof. Picard puts forward an argument that (1) wearing sensors that objectify emotional states has the potential to be a learning experience for individuals to promote self-awareness and healthy self-regulation, and (2) that research on emotion with an idiothetic perspective is potentially more beneficial to the general population – because we need to understand the inconsistencies of our data (i.e. how physiology relates to emotional experience on an intra-individual level) as well as those consistent relationships between physiology and emotion that are recorded in a laboratory setting.

In my opinion, both arguments are sound.  I would add another strand to the same debate – it seems to me that interest in self-tracking systems, such as those lifelogging experiments described regularly on the excellent Quantified Self blog, is on the rise.  The technology to self-monitor is used principally for sports training, see this range of apparatus described recently in Wired.  Ambulatory systems to monitor physiology are generally used for fitness training but their mere existence opens the door for self-experimentation, outside the laboratory (to borrow from Prof. Picard’s title), for the people by the people.  As one example, see this blog posting by Seth Roberts on the effects on omega-3 on physical and mental ability: if you’re really interested in self-tracking and self-experimentation, I’d recommend his paper published recently in Medical Hypotheses – full text is linked from this QS post.

What boggles the mind is the endless possibilities of self-experimentation and self-tracking for the person equipped with wearable sensors whose physiological data is being continually recorded and stored.  As an added dimension, what happens when people post physiological data online in a public space as I’ve written about under the heading ‘body blogging’ and Kiel has actually put a version into practice at his bodyblogger site.  Would you like to monitor the emotional state of your partner or children when you’re not with them?  Will we see ‘crowdsourced’ experiments on emotional psychophysiology as people share physiological data linked to emotional labels?  One wonders if social network groups, for instance sufferers of psychosomatic conditions, will pool data as they experiment with different interventions?  How will we visualise cumulative tsunami of data as millions of heart rate records are blogged live during global events, such as the recent World Cup?  Does this kind of remote monitoring of one another constitute a legitimate sharing of experience?

At the very least, I hope it will push us out of the laboratory and improve the relevance of our research in the real world.

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One response to “Better living through affective computing

  1. Pingback: Physiological Computing : Road rage, unhealthy emotions and affective computing

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