Key result
The deppG algorithm reliably extracted instantaneous heart rate and respiratory rate from single-channel photoplethysmography signals, even in the presence of noise and motion artifacts.
Why the study?
Does the deppG algorithm improve the accuracy of extracting instantaneous heart rate and respiratory rate from single-channel PPG signals compared to existing methods?
Does the deppG algorithm improve the accuracy of extracting instantaneous heart rate and respiratory rate from single-channel PPG signals compared to existing methods?
The novel deppG algorithm provides a mathematically rigorous method to accurately extract instantaneous heart and respiratory rates from PPG signals, which could enhance the reliability of wearable monitoring devices.
May support wearable vital sign monitoring; leaves open prospective clinical validation before adoption.
Despite the population of the noninvasive, economic, comfortable, and easy-to-install photoplethysmography (PPG), it is still lacking a mathematically rigorous and stable algorithm which is able to simultaneously extract from a single-channel PPG signal the instantaneous heart rate (IHR) and the instantaneous respiratory rate (IRR). In this paper, a novel algorithm called deppG is provided to tackle this challenge. deppG is composed of two theoretically solid nonlinear-type time-frequency analyses techniques, the de-shape short time Fourier transform and the synchrosqueezing transform, which allows us to extract the instantaneous physiological information from the PPG signal in a reliable way. To test its performance, in addition to validating the algorithm by a simulated signal and discussing the meaning of "instantaneous", the algorithm is applied to two publicly available batch databases, the Capnobase and the ICASSP 2015 signal processing cup. The former contains PPG signals relative to spontaneous or controlled breathing in static patients, and the latter is made up of PPG signals collected from subjects doing intense physical activities. The accuracies of the estimated IHR and IRR are compared with the ones obtained by other methods, and represent the state-of-the-art in this field of research. The results suggest the potential of deppG to extract instantaneous physiological information from a signal acquired from widely available wearable devices, even when a subject carries out intense physical activities.
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Cicone et al. (2017) studied Algorithm validation for PPG signal processing (n=42). deppG algorithm vs. Ground truth (ECG/Capnogram) and other signal processing methods was evaluated on Accuracy of estimated instantaneous heart rate (IHR) and instantaneous respiratory rate (IRR) measured by root mean square (RMS) error. The deppG algorithm reliably extracted instantaneous heart rate and respiratory rate from single-channel photoplethysmography signals, even in the presence of noise and motion artifacts.
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