New to the forums but not to QS (The Body Blogger). Thought I would share some recent work I’ve been doing on visualising group physiology which may be of interest.
Last year I did some consultancy work on a project interested in visualising the biological rhythms of employees at different workplaces based at Liverpool. The project was interested in contrasting the physiological activity of different workplaces for an audience as part of an upcoming art exhibit.
Physiological data (heartbeat rate and motion) was collected from 10 employees, 5 from a local hairdressers and 5 from a game testing lab, for a period of 24 hours. The original exhibit was designed to show the immediate physiological activity of each workplace. Using the original data I’ve created new visualisations which I’ve included below which use aspects of my previous work on visualising physiology to convey workplace activity.
This visualisation organises employees according to their workplace and shows immediate activity as well as each groups past activity .
This visualisation shows long term and short term cardiac activity for all employees.
This visualisation shows long term and short term cardiac activity for a single employee.
As each workplace was radically different from the other, it provided both interesting QS challenges to tackle (e.g. game testers are not allowed mobile phones at work which restricts use of wearable sensors) and for interesting visualisations (e.g. observe the 2 night shift workers at the game tester labs).
While fun to produce, a big issue I found with the visualising this data set was how to convey the rhythm of each workplace which could be readily be interpreted by a non-expert. With the Body Blogger project, I had longitudinal data to provide context for the data (e.g. identifying certain activity patterns such as sleep), allowing me to create more meaningful visualisations, however, here, the nature of the data collected doesn’t provide for much.
In my next attempt at visualising this data set I’ll be looking at combining the signals we collected (heartbeat rate and motion) which will hopefully provide a more meaningful visualisation (e.g. hairdressing involves more physical activity than game testing during work hours, this should show up in the visualisation).
Hope you enjoyed the visualisations, any comments or suggestions please let me know.
For more info see http://justkiel.com/wordpress/?p=446