Novel Non-invasive Assessment of Respiratory Function (NORM)
NORM is an NHS National Institute of Health Research project, funded under the Invention for Innovation (i4i) scheme, and began in June 2009. It is a short term (one year) feasibility study.
Background
Respiratory function testing is common in specialist centres and primary care, yet for significant patient numbers across all ages no appropriate assessment tool exists. For very young children, patients with significant respiratory compromise or fatigue related disorders (e.g. muscular dystrophies) effort dependent procedures requiring coordination and cooperation can be challenging if not impossible, preventing accurate monitoring of the disease process. Bedside methods often rely on methodologies prone to significant error. There is currently no non-invasive highly accurate system, requiring minimal cooperation to monitor or assess respiratory function applicable to all ages, impeding studies of directly comparable (as opposed to directly related) data from childhood to adulthood.
Aims
We are developing a novel, non-invasive method for non-contact assessment of respiratory muscle function by monitoring changes in the three-dimensional surface details of the human torso in real time. An optical system captures and tracks all motion details of the chest and abdomen walls, recording 3D shape and dimensional variation of the body dynamically during breathing. A model is being developed to correlate measurement data with respiratory muscle function. The system is initially designed for the use on adult patients and could be adapted for use on children (after appropriate following-up research and testing). The system could be used to monitor or diagnose neurological, muscle motion and respiratory system disorders.
Current Development:
Lighting Characterization:
System Setup:
Data Acquisition Software:
Potential Impact
NHS Impact
- Cheaper; no consumables, dedicated lab space or on-site technical support.
- Allows specialist treatment assessment/monitoring in community.
- Simple to operate, enables telemedicine support by specialist centre.
- Continuous monitoring allows more detailed assessment.
- Local use reduces hospital appointments, saving time and costly investigations, e.g. polysomnography.
- Better assessment of respiratory deterioration allows more timely preventive/rescue therapy; reduced long term NHS demands.
Patient impact
- Less stress.
- Local use – no need to attend specialist centre.
- Improves diagnostic timeliness/accuracy, impacting on health/recovery; no mask, mouthpiece, or volitional component, so suitable for younger patients.
- Non-invasive, suitable for monitoring in critical care.
Contact
For further information, please contact Scott Mandry via email or telephone on +44(0)117 328 3550.
Contacts
Prof. Melvyn L. Smith
Professor of Machine Vision
Director of the Centre for Innovative Manufacturing and Machine Vision Systems
Co-director of the Machine Vision Laboratory
Tel: +44(0)117 32 86358
E-mail: melvyn.smith@uwe.ac.uk
Dr. Lyndon N. Smith
Reader in Computer Simulation and Machine Vision
Co-director of the Machine Vision Laboratory
Tel: +44(0)117 3282009
E-mail: lyndon.smith@uwe.ac.uk
Dr. P. Sagar. Midha
Senior Research Fellow
Tel: +44(0)117 3282629
E-mail: sagar2.midha@uwe.ac.uk
Correspondence address
Machine Vision Lab, DuPont
Bristol Institute of Technology
University of the West of England
Frenchay Campus
Coldharbour Lane
Bristol BS16 1QY
UK
Fax: +44(0)117 3283636

