Summary

Smartcough aims to develop a low cost and easy-to- use telemedicine solution that will enable real-time detection, assessment, and characterisation, of different types of coughing episodes, in order to better understand the underlying cause.

Smartcough focuses on exploiting current programmes and available devices, such as smartphones and smart watches, to better understand the patient experience.

The project is investigating robust and reliable signal processing methods for effective cough identification in different daily situations, with no need for device manipulation. The use of seamless and affordable add-ons is also being explored to achieve full diagnostic capabilities.

Background

A report by the European Commission of the European Communities on Telemedicine in 2008 noted the potential of telemedicine in the management of respiratory conditions, such as chronic obstructive pulmonary disease (COPD), but highlighted the pressing need for good quality research in this area.

An investigation in to how to improve the identification of symptoms, such as coughing episodes, could lead to early diagnosis or prevention, providing better healthcare for patients and reducing the burden on NHS resources.

A number of programmes are currently used in healthcare to capture and analyse cough recordings, including the Hull Automated Cough Counter, the Leicester Cough Monitor, and Lifeshirt, all of which achieve a high degree of sensitivity and specificity. With advances in smartphone and wearable technology, there is an opportunity to use these existing programmes to create an intelligent cough monitoring system that can record and measure cough sounds and related movement in real-time and store and send data to computer programmes for analysis.

Smartcough cleverly analyses the smartphone audio data to help monitor respiratory health and predict exacerbations. Respiratory health can be monitored and patients won’t be conscious of the medicalisation of their lives.

Pablo Casaseca

Senior Lecturer in Signal and Image Processing

Approach

The DHI funded a pilot study with the University of Edinburgh, University of the West of Scotland, Cirrus Logic and Chest Heart & Stroke Scotland.

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