Age and Gender Do Not Influence the Ability to Detect Respiration by Photoplethysmography

Nilsson, Lena; Goscinski, Tomas; Johansson, Anders; Lindberg, Lars‐Göran; Kalman, Sigridur

doi:10.1007/s10877-006-9050-z

Cited by 23 publications

(16 citation statements)

References 18 publications

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“…This was done to enroll a homogenous population, which can preclude many confounding factors of SpO 2 , and to reduce the possibility of difficult ventilation and intubation. Age and sex have not been known to influence the pulse oximeter reading; 15 therefore, our results could be applied to other population groups.…”

Section: Discussionmentioning

confidence: 99%

Comparison of desaturation and resaturation response times between transmission and reflectance pulse oximeters

Choi

Ahn

Yang

et al. 2010

Acta Anaesthesiol Scand

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Section: Discussionmentioning

confidence: 99%

Comparison of desaturation and resaturation response times between transmission and reflectance pulse oximeters

Choi

Ahn

Yang

et al. 2010

Acta Anaesthesiol Scand

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“…In terms of sex and age differences in respiratory signals from PPG, literature suggests that the pulse interval variations may be more pronounced in females than in males [16], and more pronounced in the young than in the elderly [21], but that there is no significant difference in the RIIVs with age or sex [22].…”

Section: A Respiration and Photoplethysmographymentioning

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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“…2), [15][16][17][18][19] and several methods for detecting respiratory rates from PPG are based on the RIIV component. 23,24 Different algorithms can be used to extract the respiratory rate: min-max, peak-to-peak, or pulse shape. 23,24 Different algorithms can be used to extract the respiratory rate: min-max, peak-to-peak, or pulse shape.…”

Section: Respiratory Ratementioning

confidence: 99%

Respiration Signals from Photoplethysmography

Nilsson

2013

Anesthesia &Amp; Analgesia

107

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Pulse oximetry is based on the technique of photoplethysmography (PPG) wherein light transmitted through tissues is modulated by the pulse. In addition to variations in light modulation by the cardiac cycle, the PPG signal contains a respiratory modulation and variations associated with changing tissue blood volume of other origins. Cardiovascular, respiratory, and neural fluctuations in the PPG signal are of different frequencies and can all be characterized according to their sinusoidal components. PPG was described in 1937 to measure blood volume changes. The technique is today increasingly used, in part because of developments in semiconductor technology during recent decades that have resulted in considerable advances in PPG probe design. Artificial neural networks help to detect complex nonlinear relationships and are extensively used in electronic signal analysis, including PPG. Patient and/or probe-tissue movement artifacts are sources of signal interference. Physiologic variations such as vasoconstriction, a deep gasp, or yawn also affect the signal. Monitoring respiratory rates from PPG are often based on respiratory-induced intensity variations (RIIVs) contained in the baseline of the PPG signal. Qualitative RIIV signals may be used for monitoring purposes regardless of age, gender, anesthesia, and mode of ventilation. Detection of breaths in adult volunteers had a maximal error of 8%, and in infants the rates of overdetected and missed breaths using PPG were 1.5% and 2.7%, respectively. During central apnea, the rhythmic RIIV signals caused by variations in intrathoracic pressure disappear. PPG has been evaluated for detecting airway obstruction with a sensitivity of 75% and a specificity of 85%. The RIIV and the pulse synchronous PPG waveform are sensitive for detecting hypovolemia. The respiratory synchronous variation of the PPG pulse amplitude is an accurate predictor of fluid responsiveness. Pleth variability index is a continuous measure of the respiratory modulation of the pulse oximeter waveform and has been shown to predict fluid responsiveness in mechanically ventilated patients including infants. The pleth variability index value depends on the size of the tidal volume and on positive end-expiratory pressure. In conclusion, the respiration modulation of the PPG signal can be used to monitor respiratory rate. It is probable that improvements in neural network technology will increase sensitivity and specificity for detecting both central and obstructive apnea. The size of the PPG respiration variation can predict fluid responsiveness in mechanically ventilated patients.

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Age and Gender Do Not Influence the Ability to Detect Respiration by Photoplethysmography

Abstract: These results demonstrate clinically important information implying the possibility to register qualitative PPGr signals for respiration monitoring, regardless of age and gender.

Cited by 23 publications

References 18 publications

Comparison of desaturation and resaturation response times between transmission and reflectance pulse oximeters

Comparison of desaturation and resaturation response times between transmission and reflectance pulse oximeters

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

Respiration Signals from Photoplethysmography

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