PhD project in Development of a low-cost wearable system for respiration monitoring using near-infrared spectroscopy (NIRS)
PhD @University of Southampton posted 2 days agoJob Description
About the project
Respiratory diseases develop progressively. However, current monitoring methods are unsuitable for long-term continuous monitoring. Near-infrared spectroscopy (NIRS) uses light to interrogate the optical properties of tissue. This project aims to develop a wearable system for long-term respiration monitoring using NIRS powered by artificial intelligence (AI) to aid in analysis.
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.
Entry requirements
You must have a UK 2:1 honours degree or its international equivalent, in one of the following:
- electrical engineering
- electronic engineering
- biomedical engineering
- physics
- computer Science
or any related field.
Essential skills:
- Knowledge of electronics.
Desirable skills:
- strong programming skills
- biomedical signal processing experience (desirable)
- excellent written and oral communication skills
- ability to work independently.
Fees and funding
For UK students, funding is provided by an EPSRC DLA Collaborative Studentship.
How to apply
You need to:
- choose programme type (Research), 2025/26, Faculty of Engineering and Physical Sciences
- select Full time or Part time
- choose the relevant PhD in Engineering
- add name of the supervisor in section 2
Applications should include:
- a personal statement
- your CV (resumé)
- 2 academic references
- degree transcripts to date
Contact us
Faculty of Engineering and Physical Sciences
If you have a general question, email our doctoral college (feps-pgr-apply@soton.ac.uk).
Project leader
For an initial conversation, email Dr Ernesto Elias Vidal Rosas (E.E.Vidal-Rosas@soton.ac.uk).
