Abstract
OBJECTIVE: Based on different physiological mechanisms, respiratory modulations of photoplethysmography (PPG) signal differ in strength and resultant accuracy of respiratory frequency (RF) estimation. We aimed to investigate the strength of different respiratory modulations and the accuracy of resultant RF estimation in different body sites and two breathing patterns.
APPROACH: PPG and reference respiratory signals were simultaneously measured in 60 seconds from 36 healthy subjects in six sites (arm, earlobe, finger, forehead, wrist-under (volar side), wrist-upper (dorsal side)). Respiratory signals were extracted from PPG recordings using four demodulation approaches: amplitude modulation (AM), baseline wandering (BW), frequency modulation (FM), and filtering. RFs were calculated from the PPG-derived and reference respiratory signals. To investigate the strength of respiratory modulations, the energy proportion in the range that covers 75% of the total energy in the reference respiratory signal, with RF in the middle, was calculated and compared between different modulations. Analysis of variance and Scheirer-Ray-Hare test were performed with post hoc analysis.
RESULTS: In normal breathing, FM was the only modulation whose RF was not significantly different from the reference RF (p>0.05). Compared with other modulations, FM was significantly higher in energy proportion (p<0.05) and lower in RF estimation error (p<0.05). As to energy proportion, measurements from finger and forehead were not significantly different (p>0.05), but both significantly different from other four sites (p<0.05). In deep breathing, the RFs derived by BW, filtering, and FM were not significantly different from the reference RF (p>0.05). The RF estimation error of FM was significantly less than that of AM or BW (p<0.05). The energy proportion of FM was significantly higher than that of other modulations (p>0.05).
SIGNIFICANCE: Of all the respiratory modulations, FM has the highest strength and is appropriate for accurate RF estimation from PPG signals recorded in different sites and different breathing patterns.
| Original language | English |
|---|---|
| Journal | Physiological Measurement |
| Early online date | 30 Jul 2020 |
| DOIs | |
| Publication status | Published - 30 Jul 2020 |
Bibliographical note
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