Amoeba

// Re-Experience Big-Data //

// 3 months group project with Sanya Rai Gupta and Florian Puech, UK, London, RCA, IDE, 2014 //

A wearable device that organises web content by interest.

Amoeba is the result of an experimental project that was aimed at finding new ways of navigating through large blocks of digital data.

With increasing digital interactions, we are constantly bombarded with vast amounts of data. Organising all this data is hard.

Amoeba records changes in three bio-parameters: breathing rate, pupil size and skin conductance to analyse content by interest and presents it through a simple, interactive interface.

Process and Testing

To test our hypothesis, we first experimented with a number of sensors before shortlisting the three most effective ones. This is the final rig we used to test users and rank four articles based on each user’s interest.

Amoeba: Evaluation

Detection of indicators of psychological arousal:

- Sharp drops in value of average skin conductance are connected to change in psychological state these are directly related with deep breaths.

- Average breathing rate strongly linked to level of engagement and peaks indicate deep breaths.

- Greater pupil dilation associated with increasing processing demands of the brain. The gaps in the data only occur when the user blinks.

We could accurately predict interest for 9 out of 10 users.

Amoeba: User Interface

The bigger the circles, the higher the interest.

The interface is a Chrome plugin designed to represent all previously browsed content associated with a search keyword in the form of circles on an adjustible timeline.

The software pulls data from the Amoeba device and uses it to categorize each webpage based on interest.

Additionally, you can view the journey you took to reach a particular page by clicking on the path icon - a feature that helps in process and reflection.