This project aims to extend and adapt signal processing and discrimination techniques for separating normal from disordered subjects by analysis of speech signals. This project will improve the reliability and applicability of existing techniques by managing and reporting uncertainty in realistic clinical settings with background noise. This work will contribute to the growth in automated, remote and objective assessment of symptoms for assisted living in an ageing population.

Further technical details of the project are available here.

Project staff and support

Athanasios Tsanas (Postgraduate Associate, University of Oxford)
Max Little (Academic supervisor, University of Oxford)
Pat McSharry (Academic co-supervisor, University of Oxford)
Michael Deisher (Industrial supervisor, Intel)
Tim Boxer (Technology Translator, Industrial Mathematics KTN)

This project is being carried out at the University of Oxford, in conjunction with Intel. It is supported by an EPSRC industrial CASE award, made available through the Knowledge Transfer Network for Industrial Mathematics. Start date: September 2008; duration: 3.5 years.