An Apparatus for the Simulation of Breathing Disorders: Physically Meaningful Generation of Surrogate Data

Davies, Harry J.; Hammour, Ghena; Mandic, Danilo P.

doi:10.48550/arxiv.2109.06699

Cited by 1 publication

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“…Participants were asked to breathe in through a tube of internal diameter 8mm and length 300mm, and breathe out through a tube of internal diameter 5mm and length 300mm, giving a ratio of resistance from inspiration to expiration of 25 64 ≈ 0.4. The tubes were linked with oneway valves in opposite directions so that breathing would automatically switch between the two tubes when switching from inspiration to expiration [40]. Continuous PPG was measured from the ear canal of subjects whilst they breathed through the tubes for 2 minutes.…”

Section: B Experimental Designmentioning

confidence: 99%

Wearable In-Ear PPG: Detailed Respiratory Variations Enable Classification of COPD

Davies

Bachtiger

Williams

et al. 2022

IEEE Trans. Biomed. Eng.

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An ability to extract detailed spirometry-like breathing waveforms from wearable sensors promises to greatly improve respiratory health monitoring. Photoplethysmography (PPG) has been researched in depth for estimation of respiration rate, given that it varies with respiration through overall intensity, pulse amplitude and pulse interval. We compare and contrast the extraction of these three respiratory modes from both the ear canal and finger and show a marked improvement in the respiratory power for respiration induced intensity variations and pulse amplitude variations when recording from the ear canal. We next employ a data driven multi-scale method, noise assisted multivariate empirical mode decomposition (NA-MEMD), which allows for simultaneous analysis of all three respiratory modes to extract detailed respiratory waveforms from in-ear PPG. For rigour, we considered in-ear PPG recordings from healthy subjects, both older and young, patients with chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) and healthy subjects with artificially obstructed breathing. Specific in-ear PPG waveform changes are observed for COPD, such as a decreased inspiratory duty cycle and an increased inspiratory magnitude, when compared with expiratory magnitude. These differences are used to classify COPD from healthy and IPF waveforms with a sensitivity of 87% and an overall accuracy of 92%. Our findings indicate the promise of in-ear PPG for COPD screening and unobtrusive respiratory monitoring in ambulatory scenarios and in consumer wearables.

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Section: B Experimental Designmentioning

confidence: 99%