Introduction: Photoplethysmography (PPG) has been widely used to assess cardiovascular function. However, few studies have comprehensively investigated the effect of measurement site on PPG waveform characteristics. This study aimed to provide a quantitative comparison on this.Methods: Thirty six healthy subjects participated in this study. For each subject, PPG signals were sequentially recorded for 1 min from six different body sites (finger, wrist under (anatomically volar), wrist upper (dorsal), arm, earlobe, and forehead) under both normal and deep breathing patterns. For each body site under a certain breathing pattern, the mean amplitude was firstly derived from recorded PPG waveform which was then normalized to derive several waveform characteristics including the pulse peak time (Tp), dicrotic notch time (Tn), and the reflection index (RI). The effects of breathing pattern and measurement site on the waveform characteristics were finally investigated by the analysis of variance (ANOVA) with post hoc multiple comparisons.Results: Under both breathing patterns, the PPG measurements from the finger achieved the highest percentage of analyzable waveforms for extracting waveform characteristics. There were significant effects of breathing pattern on Tn and RI (larger Tn and smaller RI with deep breathing on average, both p < 0.03). The effects of measurement site on mean amplitude, Tp, Tn, and RI were significant (all p < 0.001). The key results were that, under both breathing patterns, the mean amplitude from finger PPG was significantly larger and its Tp and RI were significantly smaller than those from the other five sites (all p < 0.001, except p = 0.04 for the Tp of “wrist under”), and Tn was only significantly larger than that from the earlobe (both p < 0.05).Conclusion: This study has quantitatively confirmed the effect of PPG measurement site on PPG waveform characteristics (including mean amplitude, Tp, Tn, and RI), providing scientific evidence for a better understanding of the PPG waveform variations between different body sites.

Background: It is known that the respiration-modulated photoplethysmographic (PPG) signals could be used to derive respiratory frequency (RF) and that PPG signals could be measured from different body sites. However, the accuracy of RF derived from PPG signals of different body sites has not been comprehensively investigated. Objective: This study aims to investigate the difference in the accuracy of PPG-derived RFs between measurements from different body sites, respectively, for normal and deep breathing conditions. Methods: Under normal and deep breathing patterns, the PPG signals were recorded sequentially in a randomized order from six body sites [finger, wrist under (anatomically volar), wrist upper (dorsal), earlobe, and forehead] of 36 healthy subjects. Simultaneously, the reference respiratory signal was measured by a respiratory belt on the chest. Using the frequency demodulation approach, respiratory signals were extracted from PPG signals for calculating RF by power spectral density. The bias between PPG-derived and reference RFs was then analyzed statistically using analysis of variance and non-parametric tests, Bland-Altman analysis, and linear regression to investigate the difference in RF bias between different sites. Results: The RF bias was significantly influenced by the breathing pattern and measurement site (both p < 0.001). Under normal breathing, the RF bias was insignificant in the arm, forehead, and wrist under (all p > 0.05) and significant in the other sites (all p < 0.05). Significant linear relationship between PPG-derived and reference RFs existed at all the sites ( p < 0.001) except the wrist upper ( p > 0.05). The linearity between PPG-derived and reference RFs was highest at the forehead (slope of best-fit line: 0.90, R 2 : 0.64), followed by the earlobe, finger, arm, and wrist under (slope: 0.71, R 2 : 0.40). Under deep breathing, there was no significant RF bias in all the measurement sites ( p > 0.05) except forehead ( p = 0.048). The effect of measurement site on RF bias was not significant ( p > 0.05). The finger had the smallest RF bias and the narrowest limits of agreement. Conclusion: This study has demonstrated that the accuracy of PPG-derived RF depends on the measurement site and breathing pattern. The best sites are the forehead and finger, respectively, for normal and deep breathing patterns.

Objective: Based on different physiological mechanisms, the respiratory modulations of photoplethysmography (PPG) signals differ in strength and resultant accuracy of respiratory frequency (RF) estimations. We aimed to investigate the strength of different respiratory modulations and the accuracy of resultant RF estimations in different body sites and two breathing patterns. Approach: PPG and reference respiratory signals were simultaneously measured over 60 s 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 the Scheirer–Ray–Hare test were performed with post hoc analysis. Main 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 the finger and the forehead were not significantly different (p > 0.05), but both were significantly different from the 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 at different sites and for different breathing patterns.