Automatic Discovery of Movement Activities from Eye-Movement and Head-Movement Data (NEWMANJ_U25SCI)

Primary Supervisor – Dr Jacob Newman

This project will focus on developing computer software and algorithms for movement activity discovery using a large, pre-existing dataset of unlabelled eye- and head-movement data obtained from healthy volunteers. You will explore ways of clustering, analysing, classifying, and representing the activities undertaken by individuals during their daily lives. This may involve the application and development of time-series clustering techniques, neural network classifiers and hidden Markov models. Such records of activities could provide clinicians with the high-level context of how disease impacts daily life, uncover what provokes changes in symptom severity, and could enable the impact of treatments to be monitored. 

Entry Requirements

The standard minimum entry requirement is 2:1 in Computing Science

Mode of study

Full Time

Start date

1 October 2025