Peak-to-peak detector for the arterial pulsations in the plethysmogram II: Results of its use during anaesthesia

Sluiter, E. R.; Rowaan, Cornelis; Dorlas, J. C.; Nijboer, J. A.; Jorritsma, F. F.; Blom, J. A.; Beneken, J. E. W.

doi:10.1007/bf02442543

Cited by 8 publications

(6 citation statements)

References 8 publications

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“…However, the fight ventricle and the lungs buffer the respiratory changes in systemic venous return, and only minor changes are transmitted to the left ventricle, resulting in a more constant ejected volume from the left than from the right ventricle (SANTAMORE and AMOORE, 1994). The arterial compliance is more than ten times lower than the venous compliance (SLUITER et al, 1981) and makes fluctuations in the volume of blood less pronounced on the arterial side of the circulation. This supports our primary theory of a venous variation in blood volume as a main contributor to the RIIV signal.…”

Section: Discussionmentioning

confidence: 99%

Respiratory variations in the reflection mode photoplethysmographic signal. Relationships to peripheral venous pressure

Nilsson

Johansson

Kalman

2003

Med. Biol. Eng. Comput.

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Photoplethysmography (PPG) is a non-invasive optical way of measuring variations in blood volume and perfusion in the tissue, used in pulse oximetry for instance. Respiratory-induced intensity variations (RIIVs) in the PPG signal exist, but the physiological background is not fully understood. Respiration causes variations in the blood volume in the peripheral vascular bed. It was hypothesised that the filling of peripheral veins is one of the important factors involved. In 16 healthy subjects, the respiratory synchronous variations from a PPG reflection mode signal and the peripheral venous pressure (PVP) were recorded. Variations of tidal volume, respiratory rate and contribution from abdominal and thoracic muscles gave significant and similar amplitude changes in both RIIV and the respiratory variation of PVP (p<0.01). The highest amplitudes of both signals were found at the largest tidal volume, lowest respiratory rate and during mainly thoracic breathing, respectively. The coherence between PVP and RIIV signals was high, the median (quartile range) being 0.78 (0.42). Phase analysis showed that RIIV was usually leading PVP, but variations between subjects were large. Although respiratory-induced variations in PVP and PPG showed a close correlation in amplitude variation, a causal relationship between the signals could not be demonstrated.

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Section: Discussionmentioning

confidence: 99%

Respiratory variations in the reflection mode photoplethysmographic signal. Relationships to peripheral venous pressure

Nilsson

Johansson

Kalman

2003

Med. Biol. Eng. Comput.

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“…18,19 Under experimental conditions, tidal volume variations can be followed by RIIVs. 28 This difference might be an effect of increased pressure variation in the thorax, but also by reduced sympathetic activity from the anesthesia. 17 Automatic algorithms are influenced strongly by the amplitude of the respiratory signal and accordingly a higher respiratory rate leads to a lower signalto-interference ratio for the RIIVs extracted from the PPG signal.…”

Section: Respiratory Ratementioning

confidence: 99%

“…28 Pulse transit time is inversely proportional to blood pressure, and the decreases in blood pressure that occur with inspiration correspond to a lengthening in pulse transit time. 28 Pulse transit time is inversely proportional to blood pressure, and the decreases in blood pressure that occur with inspiration correspond to a lengthening in pulse transit time.…”

Section: Obstructive Apneamentioning

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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“…Although abdominal respiration is diminished during spontaneous breathing in sedation [29], we showed that the difference between RRc and RRp changes with distinct respiration rates. A more accurate RRp due to the increase in respiratory effort and thoracic expansion with high inspiration rates might explain this [30]. …”

Section: Discussionmentioning

confidence: 99%

Photoplethysmography respiratory rate monitoring in patients receiving procedural sedation and analgesia for upper gastrointestinal endoscopy

Touw

Verheul

Tuinman

et al. 2016

J Clin Monit Comput

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The value of capnography during procedural sedation and analgesia (PSA) for the detection of hypoxaemia during upper gastrointestinal (UGI) endoscopic procedures is limited. Photoplethysmography respiratory rate (RRp) monitoring may provide a useful alternative, but the level of agreement with capnography during PSA is unknown. We therefore investigated the level of agreement between the RRp and capnography-based RR (RRc) during PSA for UGI endoscopy. This study included patients undergoing PSA for UGI endoscopy procedures. Pulse oximetry (SpO2) and RRc were recorded in combination with Nellcor 2.0 (RRp) monitoring (Covidien, USA). Bland–Altman analysis was used to evaluate the level of agreement between RRc and RRp. Episodes of apnoea, defined as no detection of exhaled CO2 for minimal 36 s, and hypoxaemia, defined as an SpO2 < 92 %, were registered. A total of 1054 min of data from 26 patients were analysed. Bland–Altman analysis between the RRc and RRp revealed a bias of 2.25 ± 5.41 breath rate per minute (brpm), with limits of agreement from −8.35 to 12.84 brpm for an RR ≥ 4 brpm. A total of 67 apnoea events were detected. In 21 % of all apnoea events, the patient became hypoxaemic. Hypoxaemia occurred 42 times with a median length of 34 (19–141) s, and was preceded in 34 % of the cases by apnoea and in 64 % by an RRc ≥ 8 brpm. In 81 % of all apnoea events, photoplethysmography registered an RRp ≥ 4 brpm. We found a low level of agreement between capnography and the plethysmography respiratory rate during procedural sedation for UGI endoscopy. Moreover, respiratory rate derived from both the capnogram and photoplethysmogram showed a limited ability to provide warning signs for a hypoxaemic event during the sedation procedure.

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Peak-to-peak detector for the arterial pulsations in the plethysmogram II: Results of its use during anaesthesia

Cited by 8 publications

References 8 publications

Respiratory variations in the reflection mode photoplethysmographic signal. Relationships to peripheral venous pressure

Respiratory variations in the reflection mode photoplethysmographic signal. Relationships to peripheral venous pressure

Respiration Signals from Photoplethysmography

Photoplethysmography respiratory rate monitoring in patients receiving procedural sedation and analgesia for upper gastrointestinal endoscopy

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