The Potential of smartphones voice recordings to monitor depression severity

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• Nick Cummins, Kings College London
• Tuesday 07 February 2023, 16:00-17:00
• FW26, Computer Laboratory, William Gates Building and Online.

If you have a question about this talk, please contact Cecilia Mascolo.

Zoom link: https://cl-cam-ac-uk.zoom.us/j/92219689343?pwd=Q1p1eUt4V3NORWVGM3hGUEZNV1JqQT09

Speech is a unique and rich health signal: no other signal contains its singular combination of cognitive, neuromuscular and physiological information. However, its highly personal and complex nature also means that there are several significant challenges to overcome to build a reliable, useful and ethical tool suitable for widespread use in health research and clinical practice. With hundreds of participants and over 18 months of speech collection, the Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD) study incorporates one of the largest longitudinal speech studies of its kind. It offers a unique opportunity in speech-health research, the investigation of throughout the entire data pipeline, from recording through to analysis, where gaps in our understanding remain. In this presentation, I will describe how our voice is a tacit communicator of our health, present initial speech analysis finding from RADAR -MDD and discussion future challenges in relation to the translation of speech analysis into clinic practise.

Bio: Dr Nicholas (Nick) Cummins is a Lecturer in AI for speech analysis for health at the Department of Biostatistics and Health Informatics at King’s College London. He is also the Chief Science Officer for Thymia, a start-up developing technologies to make mental health assessments faster, more accurate and objective. Nick is fascinated by the application of machine learning techniques to improve our understanding of different health conditions. He is particularly interested in applying these techniques to mental health disorders.

This talk is part of the Mobile and Wearable Health Seminar Series series.

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