Musings

Reflections on Body Lab

Way back in February, Kiel and I did an event called Body Lab in conjunction with our LJMU colleagues at OpenLabs.  The idea for this event originated in a series of conversations between ourselves and OpenLabs about our mutual interest in digital health. The brief of OpenLabs is to “support local creative technology companies to develop new products and services that capitalise upon global opportunities.”  Their interest in our work on physiological computing was to put this idea out among their community of local creatives and digital types.

I was initially apprehensive about wisdom of this event. I’m quite used to talking about our work with others from the research community, from both the commercial and academic side – what makes me slightly uncomfortable is talking about possible implementations because I feel the available sensor apparatus and other tools are not so advanced.  I was also concerned about whether doing a day-long event on this topic would pull in a sufficient number of participants – what we do has always felt very “niche” in my view.  Anyhow, some smooth-talking from Jason Taylor (our OpenLabs contact) and a little publicity in the form of this short podcast convinced that we should give it our best shot.

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Lifestreams, body blogging and sousveillance

 

Way back in June, I planned to write a post prompted by Kevin Kelly’s talk at the Quantified Self conference in May and a new word I’d heard in an interview with David Brin.  Between then and now, the summer months have whipped by, so please excuse the backtracking – those of you who have seen the site before will have heard of our bodyblogger project, where physiological data is collected on a continuous basis and shared with others via social media sites or directly on the internet.  For instance, most of the time, the colour scheme for this website responds to heart rate changes of one of our bodybloggers (green = normal, yellow = higher than normal, red = much higher than normal – see this for full details).  This colour scheme can be mapped over several days, weeks and months to create a colour chart representation of heart rate data – the one at the top of this post shows a month’s worth of data (white spaces = missing data).

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Physiological Computing, Challenges for Developers and Users.

I recently received a questionnaire from the European Parliament, or rather  its STOA panel with respect to developments in physiological computing and implications for social policy.  The European Technology Assessment Group (ETAG) is working on a study with the title “Making Perfect Life” which includes a section on biocybernetic adaptation as well as BCI as other kinds of “assistive” technology.  The accompanying email told me the questionnaire would take half-an-hour to complete (it didn’t) but they asked some interesting questions, particularly surrounding the view of the general public about this technology and issues surrounding data protection.

I’ve included a slightly-edited version of the questionnaire with my responses. Questions are in italics.
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Biometrics and evaluation of gaming experience part two: a thought experiment

Recent posts on the blog have concerned the topic of psychophysiology (or biometrics) and the evaluation of player experience.  Based on those posts and the comments that followed, I decided to do a thought experiment.

Imagine that I work for a big software house who want to sell as many games as possible and ensure that their product (which costs on average $3-5 million to develop per platform) is as good as it possibly can be – and one of the suits from upstairs calls and asks me “how should we be using biometrics as part of our user experience evaluation?  The equipment is expensive, its labour-intensive to analyse and nobody seems to understand what the data means.”  (This sentiment is not exaggerated, I once presented a set of fairly ambiguous psychophysiological data to a fellow researcher who nodded purposefully and said “So the physiology stuff is voodoo.”)

Here’s a list of 10 things I would push for by way of a response.

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Biometrics, Game Evaluation and User XP: Approach with caution

This post represents some thoughts on the use of psychophysiology to evaluate the player experience during a computer game.  As such, it’s tangential to the main business of this blog, but it’s a topic that I think is worth some discussion and debate, as it raises a whole bunch of pertinent issues for the design of physiological computer games.

Psychophysiological methods are combined with computer games in two types of context: applied psychology research and game evaluation in a commercial context.  With respect to the former, a researcher may use a computer game as a platform to study a psychological concept, such as effects of game play on aggression or how playing against a friend or a stranger influences the experience of the player (see this recent issue of Entertainment Computing for examples).  In both cases, we’re dealing with the application of an experimental psychology methodology to an issue where the game is used as a task or virtual world within which to study behaviour.  The computer game merely represents an environment or context in which to study human behaviour.   This approach is characterised by several features: (1) comparisons are made between carefully controlled conditions, (2) statistical power is important (if you want to see your work published) so large numbers of participants are run through the design, (3) selection of participants is carefully controlled (equal number of males and females, comparative age ranges if groups are compared) and (4) counterbalanced designs, i.e. if participants play 2 different games, half of them play game 1 then game 2 whilst the other half play game 2 and then game 1; this is important because the order in which games are presented often influences the response of the participants.
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Road rage, unhealthy emotions and affective computing

From the point of view of an outsider, the utility and value of computer technology that provides emotional feedback to the human operator is questionable.  The basic argument normally goes like this: even if the technology works, do I really need a machine to tell me that I’m happy or angry or calm or anxious or excited?  First of all, the feedback provided by this machine would be redundant, I already have a mind/body that keeps me fully appraised of my emotional status – thank you.  Secondly, if I’m angry or frustrated, do you really think I would helped in any way by a machine that drew my attention to these negative emotions, actually that would be particularly annoying.  Finally, sometimes I’m not quite sure how I’m feeling or how I feel about something; feedback from a machine that says you’re happy or angry would just muddy the waters and add further confusion.

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Emotiv EPOC and the triple dilemma of early adoption

The UK version of Wired magazine ran an article in last month’s edition (no online version available) about Emotiv and the development of the EPOC headset.  Much of the article focused on the human side of the story, the writer mixed biographical details of company founders with how the ideas driving the development of the headset came together.  I’ve written about Emotiv before here on a specific technical issue.  I still haven’t had any direct experience of the system, but I’d like to write about the EPOC again because it’s emerging as the headset of choice for early adopters.

In this article, I’d like to discuss a number of dilemmas that are faced by both the company and their customers.  These issues aren’t specific to Emotiv, they hold for other companies in the process of selling/developing hardware for physiological computing systems.

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Physiological Computing: increased self-awareness or the fast track to a divided ego?

In last week’s excellent Bad Science article from The Guardian, Ben Goldacre puts his finger on a topic that I think is particularly relevant for physiological computing systems.  He quotes press reports about MRI research into “hypoactive sexual desire response” – no, I hadn’t heard of it either, it’s a condition where the person has low libido.  In this study women with the condition and ‘normals’ viewed erotic imagery in the scanner.  A full article on the study from the Mail can be found here but what caught the attention of Bad Science is this interesting quote from one of the researchers involved: “Being able to identify physiological changes, to me provides significant evidence that it’s a true disorder as opposed to a societal construct.”

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Valve experimenting with physiological input for games

This recent interview with Gabe Newell of Valve caught our interest because it’s so rare that a game developer talks publicly about the potential of physiological computing to enhance the experience of gamers.  The idea of using live physiological data feeds in order to adapt computer games and enhance game play was first floated by Kiel  in these papers way back in 2003 and 2005.  Like Kiel, in my writings on this topic (Fairclough,   2007; 2008 – see publications here), I focused exclusively on two problems: (1) how to represent the state of the player, and (2) what could the software do with this representation of the player state.  In other words, how can live physiological monitoring of the player state inform real-time software adaptation?  For example, to make the game harder or to increase the music or to offer help (a set of strategies that Kiel summarised in three categories, challenge me/assist me/emote me)- but to make these adjustments in real time in order to enhance game play.

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Mobile Monitors and Apps for Physiological Computing

I always harbored two assumptions about the development of physiological computing systems that have only become apparent (to me at least) as technological innovation seems to contradict them.  First of all, I thought nascent forms of physiological computing systems would be developed for desktop system where the user stays in a stationary and more-or-less sedentary position, thus minimising the probability of movement artifacts.  Also, I assumed that physiological computing devices would only ever be achieved as coordinated holistic systems.  In other words, specific sensors linked to a dedicated controller that provides input to adaptive software, all designed as a seamless chain of information flow.

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Posted on by shfairclough