Category Archives: Cool new tech
I’ve mentioned OpenSesame briefly on here before, but for those of you who weren’t keeping up, it’s a pretty awesome, free psychology experiment-developing application, built using the Python programming language, and it has a lot in common with PsychoPy (which is also awesome).
The recently-released new version of OpenSesame has just taken an important step, in that it now supports the Android mobile operating system, meaning that it can run natively on Android tablets and smartphones. As far as I’m aware, this is the first time that a psychology-experimental application has been compiled (and released to the masses) for a mobile OS.
This is cool for lots of reasons. It’s an interesting technical achievement; Android is a very different implementation to a desktop OS, being focused heavily on touch interfaces. Such interfaces are now ubiquitous, and are much more accessible, in the sense that people who may struggle with a traditional mouse/keyboard can use them relatively easily. Running psychology experiments on touch-tablets may enable the study of populations (e.g., the very young, very old, or various patient groups) that would be very difficult with a more ‘traditional’ system. Similarly, conducting ‘field’ studies might be much more effective; I can imagine handing a participant a tablet for them to complete some kind of task in the street, or in a shopping mall, for instance. Also, it may open up the possibility of using the variety of sensors in modern mobile devices (light, proximity, accelerometers, magnetometers) in interesting and creative ways. Finally, the hardware is relatively cheap, and (of course) portable.
I’m itching to try this out, but unfortunately don’t have an Android tablet. I love my iPad mini for lots of reasons, but the more restricted nature of Apple’s OS means that it’s unlikely we’ll see a similar system on iOS anytime soon.
So, very exciting times. Here’s a brief demo video of OpenSesame running on a Google Nexus 7 tablet (in the demo the tablet is actually running a version of Ubuntu Linux, but with the new version of OpenSesame it shouldn’t be necessary to replace the Android OS). Let me know in the comments if you have any experience with tablet-experiments, or if you can think of any other creative ways they could be used.
Forensic and criminal psychology are somewhat odd disciplines; they sit at the cross-roads between abnormal psychology, law, criminology, and sociology. Students seem to love forensic psychology courses, and the number of books, movies, and TV shows which feature psychologists cooperating with police (usually in some kind of offender-profiling manner) attests to the fascination that the general public have for it too. Within hours of the Newtown, CT shooting spree last December, ‘expert’ psychologists were being recruited by the news media to deliver soundbites attesting to the probable mental state of the perpetrator. Whether this kind of armchair diagnosis is appropriate or useful (hint: it’s really not), it’s a testament to the acceptance of such ideas within society at large.
Back in the late 80s and early 90s there were two opposing approaches to offender profiling, rather neatly personified by American and British practitioners. A ‘top-down’ (or deductive) approach was developed by the FBI Behavioral Sciences Unit, and involved interviewing convicted offenders, attempting to derive (somewhat subjective) general principles in order to ‘think like a criminal’. By contrast, the British approach (developed principally by David Canter and colleagues) took a much more ‘bottom-up’ (or inductive) approach focused on empirical research, and more precisely quantifiable aspects of criminal behaviour.
Interestingly, the latter approach was ideally suited to standardised analysis methods, and duly spawned a number of computer-based tools. The most prominent among them was a spatial/geographical profiling tool, developed by Canter’s Centre for Investigative Psychology, and named ‘Dragnet’. The idea behind it was relatively simple – that the most likely location of the residence of a perpetrator of a number of similar crimes could be deduced from the locations of the crimes themselves. For example, a burglar doesn’t tend to rob his next-door neighbours, nor does he tend to travel too far from familiar locations to ply his trade – he commits burglaries at a medium distance from home, and generally roughly the same distance. Also general caution might prevent him from returning to the same exact location twice, so an idealised pattern of burglary might include a central point (the perpetrators home) with a number of crime locations forming the points of a circle around it. For an investigator, of course the location of the central point isn’t known a priori, however it can easily be deduced simply by looking at the size and shape of the circle.
In practice of course, it’s never this neat, but modern techniques incorporate various other features (terrain, social geography, etc.) to build statistical models and have met with some success. Ex-police officer Kim Rossmo has been the leading figure in geographic profiling in recent years, and founded the Center for Geospatial Intelligence and Investigation at Texas State university.
Software like this seems like it should be useful, but by and large has failed to deliver on its promises in a major way. At one point it was thought that the future police service would incorporate these tools (and others) routinely in order to solve, and perhaps even predict, crimes. With the sheer amount and richness of data available on the general populace (through online search histories, social networking sites, insurance company/credit card databases, CCTV images, mobile-phone histories, licence-plate-reading traffic cameras, etc. etc.) and on urban environments (e.g. Google maps) that crime-solving software would now be highly developed, and use all these sources of information. However, it seems to have largely stalled in recent years; the Centre for Investigative Psychology’s website has clearly not been updated in several years, and it seems no-one has even bothered producing versions of their software for modern operating systems.
Some others seem to be pursuing similar ideas with more modern methods (e.g. this company), yet still we’re nowhere near any kind of system like the (fictional) one portrayed in the TV series ‘Person of Interest‘, which can predict crimes by analysis of CCTV footage and behaviour patterns derived therefrom. Whether or not this will ever be possible, there is certainly relevant data out there, freely accessible to law-enforcement agencies; the issue is building the right kind of data-mining algorithms to make sense of it all – clearly, not a trivial endeavour.
Something that will undoubtedly help, is the fairly recent development of pretty sophisticated facial recognition technology. Crude face-recognition technology is now embedded in most modern digital cameras, can be used as ID-verification (i.e. instead of a passcode) to unlock smartphones, and is used for ‘tagging’ pictures on websites like Facebook and Flickr. Researchers have been rapidly refining the techniques, including some very impressive methods of generating interpolated high-resolution images from low-quality sources (this paper describes an impressive ‘face hallucination’ method; PDF here). These advancements, while impressive, are essentially a somewhat dry problem in computer vision; there’s no real ‘psychology’ involved here.
One other ‘growth area’ in criminal/legal psychology over the last few years has been in fMRI lie-detection. Two companies (the stupidly-or-maybe-ingeniously-named No Lie MRI, and Cephos) have been aggressively pushing for their lie-detection procedures to be introduced as admissible evidence in US courts. So far they’ve only had minor success, but frankly, it’s only a matter of time. Most serious commentators (e.g. this bunch of imaging heavy-hitters) still strike an extremely cautious tone on such technologies, but they may be fighting a losing battle.
Despite these two very technical areas then, in general, the early promise of a systematic scientific approach to forensic psychology that could be instantiated in formal systems has not been fulfilled. I’m not sure if this is because of a lack of investment, expertise, interest, or just because the problem turned out to be substantively harder to address than people originally supposed. There is an alternative explanation of course – that governments and law enforcement agencies have indeed developed sophisticated software that ties together all the major databases of personal information, integrates it with CCTV and traffic-camera footage, and produces robust models of the behaviour of the general public, both as a whole, and at an individual level. A conspiracy theorist might suppose that if such a system existed, information about it would have to be suppressed, and that’s the likely reason for the apparent lack of development in this area in recent years. Far-fetched? Maybe.
TTFN, and remember – they’re probably (not?) watching you…
A quick post to point you towards a great website with a lot of really cool content (if you’re into that kind of thing, which if you’re reading this blog, then I assume you probably are… anyway, I digress; I apologise, it was my lab’s Christmas party last night and I’m in a somewhat rambling mood. Anyway, back to the point).
So, the website is called cogsci.nl, and is run by a post-doc at the University of Aix-Marseille called Sebastiaan Mathôt. It’s notable in that it’s the homepage of OpenSesame - a very nice-looking, Python-based graphical experiment builder that I’ve mentioned before on these very pages. There’s a lot of other cool stuff on the site though, including more software (featuring a really cool online tool for instantly creating Gabor patch stimuli), a list of links to stimulus sets, and a selection of really-cool optical illusions. Really worth spending 20 minutes of your time poking around a little and seeing what’s there.
I’ll leave you with a video of Sebastiaan demonstrating an experimental program, written in his OpenSesame system, running on a Google Nexus 7 Tablet (using Ubuntu linux as an OS). The future! It’s here!
Another very quick link-out post I’m afraid ladies and gentleman – all this damn pushing back of the boundaries of science I’ve been doing lately has left me absolutely no time at all, plus have you ever tried pushing back a boundary? It’s bloody exhausting.
Anyway, following on from my recent post about the auditory gorillas experiment, where I talked a little about audio editing, I spotted a fantastic little piece over on Engadget about the basics of digital audio, covering things like sampling rates, bit-rate, file-formats and loads of other useful/mildly-nerdy stuff. In fact their whole ‘primed’ series (where they dissect common bits of computer technology from first principles) is well worth checking out.
Have a good weekend!
A very minimal post merely to point any interested readers towards an interesting discussion going on in the comments section of a post on Engadget here. A reader asked for suggestions for a tablet and/or apps for his developmentally-delayed daughter, and a large number of people have contributed some useful ideas and links. Just try to ignore the (inevitable *sigh*) Android vs. iOS fan-boy squabbling.
Seriously cool toys – Tobii mobile eye-tracking glasses, Pivothead HD video-recording eye-wear, and the Affectiva Q-sensor
The other day I was lucky enough to be able to help out with a bit of data-collection in a well-known London department store, being run by the magnificent Tim Holmes of Acuity Intelligence. This meant that I got to examine some seriously cool bits of new hardware – and new gadgets (especially scientific ones) are basically my kryptonite, so it was generally pretty exciting.
The first thing we used was a mobile eye-tracking system designed and built by Tobii. These have two cameras in – one front-facing to record video of what the participant is looking at, and another infra-red camera to record the participant’s exact eye-position. They can also capture sound in real-time too, and record the eye-tracking data at 30Hz. The system comes with a clip-on box where the data is actually recorded (in the background of the picture on the right) and which is also used for the (fairly brief and painless) initial calibration. It seems like a really great system – the glasses are very light, comfortable and unobtrusive – and could have a really broad range of applications for research, both scientific and marketing-related.
The next cool toy I got to play with was a pair of these:
These are glasses with a camera lens in the centre of the frame (between the eye-lenses) which can record full high-definition video – full 1080p at 30 fps, using an 8Mp sensor. Amazing! They have an 8GB onboard memory which is good for about an hour of recording time, and also have a couple of discreet buttons on the top of the right arm which can be used for taking still pictures in 5-picture burst or 6-picture time-lapse mode. They’re made by a company called Pivothead, and seem to be more intended for casual/recreational/sports use rather than as a research technology (hence the ‘cool’ styling). They’re a reasonably bulky pair of specs, but very light and comfortable, and I don’t think you’d attract much attention filming with them. It’s worth checking out the videos page at their website for examples of what they can do. They’re also only $349 – a lot for a pair of sunglasses, but if you can think of a good use for them, that seems like a snip. If you’re in the UK, they’re also available direct from the Acuity Intelligence website for £299, inc. VAT. I wonder how long it’ll be before they start showing up in law-enforcement/military situations?
The third device I got to geek-out over was one of these little beauties:
This is a ‘Q-Sensor’, made by a company called Affectiva and is about the size of an averagely chunky wristwatch. It has two little dry-contact electrodes on the back which make contact with the skin on the underside of the wrist, and also contains a 3-axis accelerometer and a temperature sensor. This little baby claims to be able to log skin conductance data (plus data from the other sensors) for 24 hours straight on a single charge, and will even stream the data ‘live’ via Bluetooth to a connected system for on-the-fly analysis. It seems like Affectiva are mainly pitching it as a market research tool, but I can think of a few good ‘proper’ research ideas that this would enable as well. This is seriously cool technology.
That’s all folks – TTFN.
I’ve recently been playing with a bit of software called FaceGen, and it’s basically awesome. As you might expect it’s a piece of 3D modelling software which is specialised in producing human face stimuli. You can either start off with a randomly-generated example, or upload your own (or someone else’s) picture, which the software can then extrapolate and model in 3D. The 3D model can then be modified to your heart’s content along various parameters – age, sex, race, emotional expression etc. etc. It really is an awesomely powerful piece of software, and pretty easy to use too, with the interface mostly based around a set of sliders for manipulating the various dimensions of the stimulus.
Here’s a brief video which gives an overview of some of the features:
The full version of FaceGen costs $299, but there is a free demo version that you can play with, available here.
Face stimuli have always posed a problem for researchers, and historically there have basically been two choices. The first is to use a standardised face-set such as the Ekman faces:
These stimuli have the benefit of being naturalistic, i.e. they are of real people, but several significant drawbacks. These face sets are often idiosyncratic in various ways and may not have all the facial expressions you might need, for all the picture subjects. In addition, they’re often not well-balanced in terms of race, age, sex etc. In particular the ‘classic’ Ekman face set is looking very dated and frankly, pretty ghastly, these days. Another more recent example would be the NimStim face set.
The second option is to use schematic or computer-generated faces such as these from this paper:
These have the big benefit of precise experimental controllability, but the obvious drawback that they aren’t very naturalistic at all.
The FaceGen software seems to offer the best of both worlds, in that you can create an almost infinite variety of precisely-produced images and easily control for confounding factors like age and race, while at the same time the stimuli it produces are pretty naturalistic – particularly so, if you import ‘real’ pictures and then modify them. I’m currently setting up an experiment which will use some face stimuli and I’m almost certainly going to use stimuli produced using FaceGen.
For more on faces in psychology research see my previous post on face-morphing. TTFN!
I’ve been meaning to write a new post which would be an update to my previous one on good psychology-related iPhone/iPad apps for a while now, but I just came across one app which is just too good not to share immediately. It’s a free app called RFSpotter, written by Nicolas Cottaris of the IRCS and Dept. of Psychology at The University of Pennsylvania, and it generates simple visual psychophysics stimuli for use in mapping receptive fields and the tuning properties thereof. It has a very slick interface, where stimulus size, position and rotation can all be controlled by the usual iOS finger-gestures (e.g. pinch-to-zoom to change stimulus size, two-finger rotation for orientation) with many other parameters editable through a pop-up menu. It will do gratings, patches, dot-clouds, coloured stimuli – all kinds of things! Very, very neat indeed.
The iPad really has the potential to be a serious platform for research, and it’s tools like this that will make it possible to do some really interesting work with it – here’s hoping we see many more specialist, research-oriented apps like this in the future!