17th January, 2009
I’ve made an attempt at displaying the results I’ve started to collect as a large visual graph, which you can see here:
View the large version here. Basically, it’s a case of spot the correlations!
6th January, 2009
More to come once I’ve sorted out how to display my initial results…
In order to compare the biofeedback data with the sounds being heard I needed an image of the entire sound heard throughout the experiment:
6th January, 2009
The continued list of tracks
This provides a significant change in tempo and tone from the previous tracks. I also think there is a difference in style from the active language rather than the passive ambience.
Nicely continues the theme, and also providing the first female vocal track. It also provides the last sad undertones before the next set of tracks. I wasn’t sure whether to swap this around with the previous track, but it stays here.
A jubilant celebration of the winter solstice, this track is designed to feel uplifting during the cold and dark winter months, and does the job effectively.
4th January, 2009
So here is a list of the tracks I have chosen for this experiment:
N.Q. = No questionnaire response needed.
Q.R. = Questionnaire response
This track will make no sound for three minutes as a form of control piece, to see what sort of feedback response is produced while not listening to the music.
It also provides time for the user to relax and buffer from any previous activity.
Three minutes is fairly arbitrary but I’m basing it on the fact that a 2 minutes silence memorial ‘feels’ rather long but at the same time I want long enough to get a reasonable reading.
This first track will provide a gentle introduction to the experiment, hopefully encouraging an initial relaxed state. From the computer game Majesty, it provides a sleepy awakening and exploration atmosphere.
2nd January, 2009
To see what sort of results I might expect from monitoring biofeedback from a user listening to music I have selected several tracks to be listened to while running a biofeedback grapher. I’ve tried to select a broad selection of very random tracks ranging from game music (this is good because they usually have a purpose creating a specific atmosphere like a movie sound track) through to more traditional pieces.
Once I’ve tried it out myself I intend testing other people to look for any form of correlation. Additionally, I would have them fill out a form of questionnaire during the session to quickly gather what mood each piece puts them in, and whether they are familiar with a particular track already.
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