Abstract

Background: Acute exacerbations of COPD impose substantial health and economic burden. Monitoring subtle changes in respiratory rate to identify early signs of clinical deterioration in COPD patients may allow timely community interventions and reduce disease burden.
Objective: This study explores using the Pneumowave DC Mobile (PWDC), a UKCA as a Class-I device, to capture and store chest motion data continuously. This data will then be used in conjunction with experimental algorithms and analysis techniques to look for early-stage COPD exacerbation. Pre-clinical work was undertaken to validate the ability of the PWDC device to accurately detect a range of physiological-relevant respiratory rates in an in vitro manikin model.

Methodology: A PWDC biosensor was placed on the upper left side of a manikin chest, approximately 6cm down from the centre of the left collarbone. Respiratory rates (10 – 30 breaths per minute [BPM]) were generated in an in vitro manikin model comprising a SimMan ALS system operated via the associated Laerdal Patient software (Laerdal Medical, UK) within the university clinical suite. Data was captured on five separate 3-min intervals at each setting and exported as a CSV file to MATLAB (version R2023a, MathWorks Inc., USA) for visualisation and analysis. Additional experiments explored the impact of sensor chest location and manikin body position (0°, 45° or 90°) on data collection.

Results: The preclinical study confirmed the accuracy of experimental algorithms using PWDC recorded data in measuring respiratory rates between 10-30 BPM. Simulated respiratory measurements were not impacted upon by device chest location or by manikin sitting position. Conclusion: The results confirm the clinical potential of PWDC to be an effective and low-cost chest motion data capture component for system to monitor people with COPD. Future research will recruit human volunteers with COPD to provide a more robust evaluation of device utility and usability.