Analysis of everyday activity through Bluetooth encounters

Christopher James (WMG)

In many situations it is useful to measure everyday human activity to
assess a number of conditions. In mental health it is sometimes useful
to assess behaviour based around normal patterns of activity - or
activity signatures. In previous work, for use in assessing behaviour in
those with bipolar disorder, a number of parameters were measured in an
unobtrusive way to attempt to gain access to this *normal* activity
signature. A literature review reveals that it may be possible to access
this activity signature through an unobtrusive measure centred on
"BlueTooth encounters" (BTE) - the person under observation carries a
mobile phone with BT enabled - software on the phone logs BTEs with
other nearby BT devices as the person goes about their daily business -
after days/weeks of encounters the data needs to be analysed to identify
and extract patterns in the BTEs. This project centres around the design
and implementation of a BTE system based around popular
mobile-phone/smart-phone, with further design of an activity signature
detection and extraction system.

A strong basis in engineering maths is recommended and an ability to
programme in Matlab and/or any other programming language is desirable.