Key result
ICA algorithm successfully extracts normal and simulated apnea respiratory activities from PPG signals.
Why the study?
A method to monitor respiratory activity using PPG without prior knowledge of respiratory rate range was needed.
Does an independent component analysis (ICA) algorithm applied to PPG signals successfully extract respiratory activity in young normal adults?
Population
10 young normal adults and simulated signals
Comparison
Independent component analysis algorithm applied to two-channel transmission mode PPG signals
Design
Preliminary report of a respiratory activity monitoring system using ICA
Authors
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Feasibility of ICA-PPG respiratory extraction shown in small healthy cohort; leaves open validation for clinical apnoea monitoring.
Does an independent component analysis (ICA) algorithm applied to PPG signals successfully extract respiratory activity in young normal adults?
An independent component analysis technique can successfully extract respiratory activity from photoplethysmographic signals, potentially allowing simultaneous monitoring of pulse rate and respiration using standard pulse oximetry hardware.
Zhou et al. (2006) studied Healthy (young normal adults) (n=10). Independent component analysis (ICA) algorithm on photoplethysmography (PPG) signals was evaluated on Extraction of normal and simulated apnoea respiratory activities. An independent component analysis algorithm successfully extracted normal and simulated apnoea respiratory activities from photoplethysmography signals in 10 young normal adults.
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