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Respiratory diseases are a major health concern in the UK, affecting one in five individuals and costing approximately £188 billion annually. Current monitoring methods, such as manual counting, respiration belts, and end-tidal carbon dioxide (EtCO2) measurement, have limitations in accuracy and comfort and are unsuitable for long-term continuous monitoring.

Continuous respiratory monitoring is crucial as many conditions develop progressively. Wearable medical devices offer a promising solution for real-time and continuous health tracking, but an ideal, cost-effective, and comfortable long-term respiratory monitoring system is lacking. Near-infrared spectroscopy (NIRS) uses light to interrogate the optical properties of tissue. The dynamical changes of these properties are closely related to physiological signals such as respiration, heart rate, and tissue oxygenation. This project aims to investigate the feasibility of long-term respiration monitoring using NIRS and to develop a wearable monitor using NIRS technology. 

The objectives are:

• simulating light transport in the thorax to understand the source of signals and optimise monitoring
• designing and building a low-cost wearable sensor for lung health monitoring
• testing the feasibility of continuous monitoring with the wearable sensor in a healthy adult cohort
• identifying and classifying waveform patterns and breathing parameters using artificial intelligence (AI)

The expected outcome is a set of design parameters that include source-detector separations, the optimal location of the NIRS probe, and an AI-based processing pipeline. This project will be run in collaboration with the Faculty of Medicine, which will provide advice on clinical aspects and oversee participant recruitment.