Monitoring of respiratory rate in postoperative care using a new photoplethysmographic technique

Developing an algorithm for pulse oximetry derived respiratory rate (RR(oxi)): a healthy volunteer study

Objective The presence of respiratory information within the pulse oximeter signal (PPG) is a well-documented phenomenon. However, extracting this information for the purpose of continuously monitoring respiratory rate requires: (1) the recognition of the multi-faceted manifestations of respiratory modulation components within the PPG and the complex interactions among them; (2) the implementation of appropriate advanced signal processing techniques to take full advantage of this information; and (3) the post-processing infrastructure to deliver a clinically useful reported respiratory rate to the end user. A holistic algorithmic approach to the problem is therefore required. We have developed the RR_OXI algorithm based on this principle and its performance on healthy subject trial data is described herein.

Methods Finger PPGs were collected from a cohort of 139 healthy adult volunteers monitored during free breathing over an 8-min period. These were subsequently processed using a novel in-house algorithm based on continuous wavelet transform technology within an infrastructure incorporating weighted averaging and logical decision making processes. The computed oximeter respiratory rates (RR_oxi) were then compared to an end-tidal CO₂ reference rate (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\text{RR}}_{{{\text{ETCO}}_{ 2} }} $$\end{document}).

Results\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\text{RR}}_{{{\text{ETCO}}_{ 2} }} $$\end{document} ranged from a lowest recorded value of 2.97 breaths per min (br/min) to a highest value of 28.02 br/min. The mean rate was 14.49 br/min with standard deviation of 4.36 br/min. Excellent agreement was found between RR_oxi and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\text{RR}}_{{{\text{ETCO}}_{ 2} }} $$\end{document}, with a mean difference of −0.23 br/min and standard deviation of 1.14 br/min. The two measures are tightly spread around the line of agreement with a strong correlation observable between them (R² = 0.93).

Conclusions These data indicate that RR_oxi represents a viable technology for the measurement of respiratory rate of healthy individuals.

On non-invasive measurement of gastric motility from finger photoplethysmographic signal

This article investigates the possibility of extracting gastric motility (GM) information from finger photoplethysmographic (PPG) signals non-invasively. Now-a-days measuring GM is a challenging task because of invasive and complicated clinical procedures involved. It is well-known that the PPG signal acquired from finger consists of information related to heart rate and respiratory rate. This thread is taken further and effort has been put here to find whether it is possible to extract GM information from finger PPG in an easier way and without discomfort to the patients. Finger PPG and GM (measured using Electrogastrogram, EGG) signals were acquired simultaneously at the rate of 100 Hz from eight healthy subjects for 30 min duration in fasting and postprandial states. In this study, we process the finger PPG signal and extract a slow wave that is analogous to actual EGG signal. To this end, we chose two advanced signal processing approaches: first, we perform discrete wavelet transform (DWT) to separate the different components, since PPG and EGG signals are non-stationary in nature. Second, in the frequency domain, we perform cross-spectral and coherence analysis using autoregressive (AR) spectral estimation method in order to compare the spectral details of recorded PPG and EGG signals. In DWT, a lower frequency oscillation (≈0.05 Hz) called slow wave was extracted from PPG signal which looks similar to the slow wave of GM in both shape and frequency in the range (0-0.1953) Hz. Comparison of these two slow wave signals was done by normalized cross-correlation technique. Cross-correlation values are found to be high (range 0.68-0.82, SD 0.12, R = 1.0 indicates exact agreement, p < 0.05) for all subjects and there is no significant difference in cross-correlation between fasting and postprandial states. The coherence analysis results demonstrate that a moderate coherence (range 0.5-0.7, SD 0.13, p < 0.05) exists between EGG and PPG signal in the "slow wave" frequency band, without any significant change in the level of coherence in postprandial state. These results indicate that finger PPG signal contains GM-related information. The findings are sufficiently encouraging to motivate further exploration of finger PPG as a non-invasive source of GM-related information.

Performance evaluation of a tri-axial accelerometry-based respiration monitoring for ambient assisted living

Ambient Assisted Living (AAL) technology is often proposed as a way to tackle the increasing cost of healthcare caused by population aging. However, the sensing technology for continuous respiratory monitoring at home is lacking. Known approaches of respiratory monitoring are based on measuring either respiratory effect, e.g. tracheal sound recording by a bio-acoustic sensor, or respiratory effort, e.g. abdomen movement measurement by a tri-axial accelerometer. This paper proposes a home respiration monitoring system using a tri-axial accelerometer. Three different methods to extract a single respiratory signal from the tri-axial data are proposed and analyzed. The performance of the methods is evaluated for various possible respiration conditions, defined by the sensor orientation and respiration-induced abdomen movement. The method based on Principal Component Analysis (PCA) performs better than selecting the best axis. The analytical approach called Full Angle shows worse results than the best axis when the gravity vector is close to one of the sensor's axes (<15 degrees). Hybrid-PCA, which is a combination of both methods, performs comparable to PCA. The system is evaluated using simulated data from the most common postures, such as lying and sitting, as well as real data collected from five subjects. The results show that the system can successfully reconstruct the respiration-induced movement, which is necessary to determine the respiratory rate accurately.

Photoplethysmography and nociception

Photoplethysmography (PPG), i.e. pulse oximetric wave, is a non-invasive technique that is used in anaesthesia monitoring primarily to monitor blood oxygenation. The PPG waveform resembles that of the arterial blood pressure but instead of pressure it is related to the volume changes in the measurement site and hence contains information related to the peripheral blood circulation, including skin vasomotion, which is controlled by the sympathetic nervous system. Because of this link, skin vasomotor response and PPG amplitude response have been associated with nociception under general anaesthesia. Recently, there has been interest in monitoring nociception during general anaesthesia. In many of the published studies, PPG waveform information has been included. The focus of this topical review is to provide an overview on the information embedded in the PPG waveform especially in the context of the autonomic nervous system and analgesia monitoring.

Estimation of respiratory rate from photoplethysmogram data using time-frequency spectral estimation

We present a new method that uses the pulse oximeter signal to estimate the respiratory rate. The method uses a recently developed time-frequency spectral estimation method, variable-frequency complex demodulation (VFCDM), to identify frequency modulation (FM) of the photoplethysmogram waveform. This FM has a measurable periodicity, which provides an estimate of the respiration period. We compared the performance of VFCDM to the continuous wavelet transform (CWT) and autoregressive (AR) model approaches. The CWT method also utilizes the respiratory sinus arrhythmia effect as represented by either FM or AM to estimate respiratory rates. Both CWT and AR model methods have been previously shown to provide reasonably good estimates of breathing rates that are in the normal range (12-26 breaths/min). However, to our knowledge, breathing rates higher than 26 breaths/min and the real-time performance of these algorithms are yet to be tested. Our analysis based on 15 healthy subjects reveals that the VFCDM method provides the best results in terms of accuracy (smaller median error), consistency (smaller interquartile range of the median value), and computational efficiency (less than 0.3 s on 1 min of data using a MATLAB implementation) to extract breathing rates that varied from 12-36 breaths/min.

Validation of forehead venous pressure as a measure of respiratory effort for the diagnosis of sleep apnea

OBJECTIVES

The aim of the study was to validate the measurement of Forehead Venous Pressure derived from a single site on the forehead as an alternative to esophageal manometry and respiratory effort bands in the differential diagnosis of sleep apnea.

METHODS

Fourteen subjects underwent a laboratory polysomnography concurrently with ARES Unicorder at Walter Reed Army Medical Center. Two-hundred respiratory events were selected by a scorer boarded in sleep medicine and classified into six event categories used in the differential diagnosis of sleep disordered breathing. Four sets of events were prepared, each containing airflow and one of four measures of respiratory effort (i.e., esophageal manometer, chest and abdomen bands, and forehead venous pressure). A second board-certified scorer scored each set of events twice while blinded to the type of the effort signal.

RESULTS

The inter-rater Kappa scores across all event types indicated all four effort signals provided moderate agreement (kappa = 0.43-0.47). When comparing the intra-rater Kappa scores, the chest belt was superior (kappa = 0.88) to the esophageal manometry, FVP and abdomen belt (kappa = 0.78-0.82). The Kappa scores for the intra-rater comparison with the esophageal serving as the gold standard, FVP abdomen and chest all showed near perfect agreement (kappa = 0.81-0.86). The esophageal manometer and FVP provided slightly better inter-rater agreement in the detection of both obstructive hypopneas and apneas as compared to the chest and abdomen belts. There was a 20-30% drop in inter-rater reliability in the detection of flow-limitation and ventilation-change events compared to obstructive events, and all effort signals showed poor inter-rater agreement for central and mixed events.

CONCLUSIONS

The results of the study suggest that the FVP can serve as an alternative to respiratory bands in the differential diagnosis of sleep disordered breathing, and in the recognition of patients appropriate for bilevel continuous positive airway pressure devices.

Noise cancellation model validation for reduced motion artifact wearable PPG sensors using MEMS accelerometers

This paper investigates the validity of utilizing Widrow's Active Noise Cancellation (ANC) in the context of motion artifact reduction for photoplethysmogram (PPG) sensors. The ANC approach has previously been applied to the PPG problem, but little consideration has been given to the validity of the ANC signal corruption assumptions and in what motion range the algorithm works. The ANC validity testing is done in the form of impact (approximate impulse) testing of the physical PPG system and comparing with the modeled response for a range of motion amplitudes. The testing reveals that the identified corruption model does not generally represent the true physical system, but locally approximates the true system. Testing shows that if a similar motion amplitude is used for model tuning as the impact test, an average peak deviation of 5.2% is obtained, but if motion amplitude that is smaller than the impact amplitude by a factor of 5, the peak deviation is 15%. Finally, after ANC filtering motion corrupted data, heart rate can be estimated with less than 1.6% error.

Low variance adaptive filter for cancelling motion artifact in wearable photoplethysmogram sensor signals

The photoplethysmogram (PPG) is an extremely useful wearable sensing medical diagnostic tool. However, the PPG signal becomes highly corrupted and unusable when the sensor wearer is in motion. This paper investigates how confidently Widrow's Adaptive Noise Cancellation can eliminate motion artifact and recover a motion corrupted PPG signal for a wearer engaged in jogging motions. It has previously been shown that Widrow's Adaptive Noise Cancellation can recover a motion corrupted PPG signal for certain data sets by using a collocated accelerometer to measure the corrupting motion. However, wearer motion is band limited, and provides little information for estimating motion-to-PPG noise transfer dynamics. This means that, without proper care, recovery results can be unreliable. In the present work, both Finite Impulse Response (FIR) and Laguerre series black box transfer dynamics models are evaluated for how confidently they can be identified. Model confidence is quantified in terms of variance of the transfer dynamics estimate at the motion frequencies. For typical jogging motion, it is found that standard deviation of the FIR model transfer dynamics is 30% of the mean value at the motion input frequency. The standard deviation of the Laguerre model transfer dynamics is only 1%. Time domain data shows how a Laguerre model outperforms a FIR model in accordance with the computed model variance.

Combined photoplethysmographic monitoring of respiration rate and pulse: a comparison between different measurement sites in spontaneously breathing subjects

BACKGROUND

The non-invasive photoplethysmographic (PPG) signal reflects blood flow and volume in a tissue. The PPG signal shows variation synchronous with heartbeat (PPGc), as used in pulse oximetry, and variations synchronous with breathing (PPGr). PPGr has been used for non-invasive monitoring of respiration with promising results. Our aim was to investigate PPG signals recorded from different skin sites in order to find suitable locations for parallel monitoring of variations synchronous with heartbeat and breathing.

METHODS

PPG sensors were applied to the forearm, finger, forehead, wrist and shoulder on 48 awake healthy volunteers. From these sites, seven PPG signals were simultaneously recorded during normal spontaneous breathing over 10 min. Capnometry served as respiration and electrocardiogram (ECG) as pulse reference signals. PPG signals were compared with respect to power spectral content and squared coherence.

RESULTS

Forearm PPG measurement showed significantly higher power within the respiratory region of the power spectrum [median (quartile range) 42 (26)%], but significantly lower power within the cardiac region [9 (10)%] compared with the other skin sites. PPG finger measurement showed the opposite; in transmission mode, the power within the respiratory region was significantly lower [4 (10)%] and within the cardiac region significantly higher [45 (25)%] than the other sites. PPGc coherence values were generally high [>0.96 (0.08)], and PPGr coherence values lower [0.83 (0.35)-0.94 (0.17)].

CONCLUSION

Combined PPG respiration and pulse monitoring is possible, but there are significant differences between the respiratory and cardiac components of the PPG signal at different sites.

Photoplethysmography and its application in clinical physiological measurement

Photoplethysmography (PPG) is a simple and low-cost optical technique that can be used to detect blood volume changes in the microvascular bed of tissue. It is often used non-invasively to make measurements at the skin surface. The PPG waveform comprises a pulsatile ('AC') physiological waveform attributed to cardiac synchronous changes in the blood volume with each heart beat, and is superimposed on a slowly varying ('DC') baseline with various lower frequency components attributed to respiration, sympathetic nervous system activity and thermoregulation. Although the origins of the components of the PPG signal are not fully understood, it is generally accepted that they can provide valuable information about the cardiovascular system. There has been a resurgence of interest in the technique in recent years, driven by the demand for low cost, simple and portable technology for the primary care and community based clinical settings, the wide availability of low cost and small semiconductor components, and the advancement of computer-based pulse wave analysis techniques. The PPG technology has been used in a wide range of commercially available medical devices for measuring oxygen saturation, blood pressure and cardiac output, assessing autonomic function and also detecting peripheral vascular disease. The introductory sections of the topical review describe the basic principle of operation and interaction of light with tissue, early and recent history of PPG, instrumentation, measurement protocol, and pulse wave analysis. The review then focuses on the applications of PPG in clinical physiological measurements, including clinical physiological monitoring, vascular assessment and autonomic function.

Age and gender do not influence the ability to detect respiration by photoplethysmography

OBJECTIVE

The non-invasive technique photoplethysmography (PPG) can detect changes in blood volume and perfusion in a tissue. Respiration causes variations in the peripheral circulation, making it possible to monitor breaths using an optical sensor attached to the skin. The respiratory-synchronous part of the PPG signal (PPGr) has been used to monitor respiration during anaesthesia, and in postoperative and neonatal care. Studies addressing possible differences in PPGr signal characteristics depending on gender or age are lacking.

METHODS

We studied three groups of 16 healthy subjects each during normal breathing; young males, old males and young females, and calculated the concordance between PPGr, derived from a reflection mode PPG sensor on the forearm, and a reference CO(2 )signal. The concordance was quantified by using a squared coherence analysis. Time delay between the two signals was calculated. In this process, we compared three different methods for calculating time delay.

RESULTS

Coherence values >or=0.92 were seen for all three groups without any significant differences depending on age or gender (p = 0.67). Comparison between the three different methods for calculating time delay showed a correlation r = 0.93.

CONCLUSIONS

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

What Is the Best Site for Measuring the Effect of Ventilation on the Pulse Oximeter Waveform?

The cardiac pulse is the predominant feature of the pulse oximeter (plethysmographic) waveform. Less obvious is the effect of ventilation on the waveform. There have been efforts to measure the effect of ventilation on the waveform to determine respiratory rate, tidal volume, and blood volume. We measured the relative strength of the effect of ventilation on the reflective plethysmographic waveform at three different sites: the finger, ear, and forehead. The plethysmographic waveforms from 18 patients undergoing positive pressure ventilation during surgery and 10 patients spontaneously breathing during renal dialysis were collected. The respiratory signal was isolated from the waveform using spectral analysis. It was found that the respiratory signal in the pulse oximeter waveform was more than 10 times stronger in the region of the head when compared with the finger. This was true with both controlled positive pressure ventilation and spontaneous breathing. A significant correlation was demonstrated between the estimated blood loss from surgical procedures and the impact of ventilation on ear plethysmographic data (r(s) = 0.624, P = 0.006).

The Use of Joint Time Frequency Analysis to Quantify the Effect of Ventilation on the Pulse Oximeter Waveform

OBJECTIVE

In the process of determining oxygen saturation, the pulse oximeter functions as a photoelectric plethysmograph. By analyzing how the frequency spectrum of the pulse oximeter waveform changes over time, new clinically relevant features can be extracted.

METHODS

Thirty patients undergoing general anesthesia for abdominal surgery had their pulse oximeter, airway pressure and CO(2) waveforms collected (50 Hz). The pulse oximeter waveform was analyzed with a short-time Fourier transform using a moving 4096 point Hann window of 82 seconds duration. The frequency signal created by positive pressure ventilation was extracted using a peak detection algorithm in the frequency range of ventilation (0.08-0.4 Hz = 5-24 breaths/minute). The respiratory rate derived in this manner was compared to the respiratory rate as determined by CO(2) detection.

RESULTS

In total, 52 hours of telemetry data were analyzed. The respiratory rate measured from the pulse oximeter waveform was found to have a 0.89 linear correlation when compared to CO(2) detection and airway pressure change. the bias was 0.03 breath/min, SD was 0.557 breath/min and the upper and lower limits of agreement were 1.145 and -1.083 breath/min respectively. The presence of motion artifact proved to be the primary cause of failure of this technique.

CONCLUSION

Joint time frequency analysis of the pulse oximeter waveform can be used to determine the respiratory rate of ventilated patients and to quantify the impact of ventilation on the waveform. In addition, when applied to the pulse oximeter waveform new clinically relevant features were observed.

Using the morphology of photoplethysmogram peaks to detect changes in posture

The morphology of the pulsatile component of the photoplethysmogram (PPG) has been shown to vary with physiology, but changes in the morphology caused by the baroreflex response to orthostatic stress have not been investigated. Using two FDA approved Nonin pulse oximeters placed on the finger and ear, we monitored 11 subjects, for three trials each, as they stood from a supine position. Each cardiac cycle was automatically extracted from the PPG waveform and characterized using statistics corresponding to normalized peak width, instantaneous heart rate, and amplitude of the pulsatile component of the ear PPG. A nonparametric Wilcoxon rank sum test was then used to detect in real-time changes in these features with p < 0.01. In all 33 trials, the standing event was detected as an abrupt change in at least two of these features, with only one false alarm. In 26 trials, an abrupt change was detected in all three features, with no false alarms. An increase in the normalize peak width was detected before an increase in heart rate, and in 21 trials a peak in the feature was detected before or as standing commenced. During standing, the pulse rate always increases, and then amplitude of the ear PPG constricts by a factor of two or more. We hypothesis that the baroreflex first reduces the percentage of time blood flow is stagnant during the cardiac cycle, then increases the hear rate, and finally vasoconstricts the peripheral tissue in order to reestablishing a nominal blood pressure. These three features therefore can be used as a detector of the baroreflex response to changes in posture or other forms of blood volume sequestration.

Respiration can be monitored by photoplethysmography with high sensitivity and specificity regardless of anaesthesia and ventilatory mode

BACKGROUND

Photoplethysmography (PPG) is a non-invasive optical technique used, for instance, in pulse oximetry. Beside the pulse synchronous component, PPG has a respiratory synchronous variation (PPGr). Efforts have been made to utilize this component for indirect monitoring of respiratory rate and volume. Assessment of the clinical usefulness as well as of the physiological background of PPGr is required. We evaluated if anaesthesia and positive-pressure ventilation would affect PPGr.

METHODS

We recorded reflection mode PPGr, at the forearm, and the respiratory synchronous changes in central venous pressure (CVP), peripheral venous pressure (PVP) and arterial blood pressure (ABP) in 12 patients. Recordings for each patient were made on three occasions: awake with spontaneous breathing; anaesthetized with spontaneous breathing; and anaesthetized with positive-pressure ventilation. We analyzed the sensitivity, specificity, coherence and time relationship between the signals.

RESULTS

PPGr sensitivity for breath detection was [mean (SD)] >86(21)% and specificity >96(12)%. Respiratory detection in the macrocirculation (CVP, PVP and ABP) showed a sensitivity >83(29)% and specificity >93(12)%. The coherence between signals was high (0.75-0.99). The three measurement situations did not significantly influence sensitivity, specificity or time shifts between the PPGr, PVP, ABP, and the reference CVP signal despite changes in physiological data between measurements.

CONCLUSION

A respiratory synchronous variation in PPG and all invasive pressure signals was detected. The reflection mode PPGr signal seemed to be a constant phenomenon related to respiration regardless of whether or not the subject was awake, anaesthetized or ventilated, which increases its clinical usefulness in respiratory monitoring.

The vexatious vital: neither clinical measurements by nurses nor an electronic monitor provides accurate measurements of respiratory rate in triage

STUDY OBJECTIVE

Of all the vital signs, only respiratory rate is still measured clinically in most US triage systems. Previous studies have demonstrated the inaccuracy, poor interobserver agreement, and low variability of routine measurements of respiratory rate. We assess the variability and accuracy of triage nurses' measurements of respiratory rate against a criterion standard. Also, we assess electronic measurement of respiratory rate against the same criterion standard.

METHODS

Consecutive patients presenting to an urban teaching emergency department (ED) were enrolled in this prospective study. Electronic measurement of respiratory rate was recorded throughout the triage encounter when nurses were recording measurements of respiratory rate. Electronic respiratory rate was measured using transthoracic impedance plethysmography. Immediately after each triage evaluation, criterion standard measurements of respiratory rate were made by research assistants using the World Health Organization recommendation of auscultation or observation for 60 seconds.

RESULTS

We enrolled 159 patients. Variability was low for triage nurses' measurements of respiratory rate (SD 3.3) and electronic measurement of respiratory rate (SD 4.1) compared with criterion standard measurements of respiratory rate (SD 4.8; P <.05). Triage nurses' measurements of respiratory rate and electronic measurement of respiratory rate showed low sensitivity in detecting bradypnea and tachypnea. In a Bland-Altman analysis, triage nurses' measurements of respiratory rate and electronic measurement of respiratory rate showed poor agreement with criterion standard measurements of respiratory rate. Subgroup analysis of patients presenting with cardiac and respiratory symptoms yielded similar results.

CONCLUSION

Neither triage nurses nor an electronic monitor provides accurate measurements of respiratory rate in the ED. Emergency physicians should search for new electronic modalities for measuring respiratory rate to bring respiratory rate into line with other vital signs. Emergency physicians should also consider new clinical strategies for measuring respiratory rate.

An Algorithm for the Detection of Individual Breaths from the Pulse Oximeter Waveform

OBJECTIVES

To determine if wavelet analysis techniques can be used to reliably identify individual breaths from the photoplethysmogram (PPG).

METHODS

Photoplethysmograms were obtained from 22 healthy adult volunteers timing their respiration rate in synchronisation with a metronome. A secondary timing signal was obtained by asking the volunteers to actuate a small push button switch, held in their right hand, in synchronisation with their respiration. Each PPG was analyzed using primary wavelet decomposition and two new, related, secondary decompositions to determine the accuracy of individual breath detection.

RESULTS

The optimal breath capture was obtained by manually polling the three techniques, allowing detection of 466 out of the 472 breaths studied; a detection rate of 98.7% with no false positive breaths detected.

CONCLUSION

Our technique allows the accurate capture of individual breaths from the photoplethysmogram, and leads the way for developing a simple non-invasive combined respiration and saturation monitor.

Macrocirculation is not the sole determinant of respiratory induced variations in the reflection mode photoplethysmographic signal

Photoplethysmography (PPG) is a non-invasive optical technique sensitive to variations in blood volume and perfusion in the tissue. Reflection mode PPG may have clinical advantages over transmission mode PPG. To improve clinical usefulness and further development of the reflection mode PPG, studies on factors that modify the signal are warranted. We studied the coherence between the respiratory induced intensity variations (RIIV) of the PPG signal and respiratory synchronous pressure variations in central venous pressure (CVP), peripheral venous pressure (PVP) and arterial blood pressure (ABP) during positive pressure ventilation on 12 patients under anaesthesia and on 12 patients with spontaneous breathing. During positive pressure ventilation the coherence between all signals was high. Inspiration was followed first by an increase in CVP, then by increases in ABP and PVP and lastly by RIIV indicating less back-scattered light. In spontaneously breathing patients the coherence was high, but the phases between the signals were changed. During inspiration, ABP decreased slightly before CVP, followed by a decrease in RIIV and PVP. The phase relation between RIIV and respiratory induced variation in macrocirculation changed with ventilatory mode, but not in a uniform way, indicating the influence of mechanisms other than macrocirculation involved in generating the RIIV signal.

Critical review of non-invasive respiratory monitoring in medical care

Respiratory failure can be difficult to predict. It can develop into a life-threatening condition in just a few minutes, or it can build up more slowly. Thus continuous monitoring of respiratory activity should be mandatory in clinical, high-risk situations, and appropriate monitoring equipment could be life-saving. The review considers non-invasive methods and devices claimed to provide information about respiratory rate or depth, or gas exchange. Methods are categorised into those responding to movement, volume and tissue composition detection; air flow; and blood gas concentration. The merits and limitations of the methods and devices are analysed, considering information content and their ability to minimise the rate of false alarms and false non-alarms. It is concluded that the field of non-invasive respiratory monitoring is still in an exploratory phase, with numerous reports on specific device solutions but less work on evaluation and adaptation to clinical requirements. Convincing evidence of the clinical usefulness of respiratory monitors is still lacking. Devices responding only to respiratory rate, and lacking information about actual gas exchange, will have limited clinical value. Furthermore, enhancement in specificity and sensitivity to avoid false alarms and non-alarms will be necessary to meet clinical requirements. Miniature CO2 sensors are identified as one route towards substantial improvement.

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

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.

Neural network for photoplethysmographic respiratory rate monitoring

The reflection mode photoplethysmographic (PPG) signal was studied with the aim of determining respiratory rate. The PPG signal includes respiratory synchronous components, seen as frequency modulation of the heart rate (respiratory sinus arrhythmia), amplitude modulation of the cardiac pulse and respiratory-induced intensity variations (RIIVs) in the PPG baseline. PPG signals were recorded from the foreheads of 15 healthy subjects. From these signals, the systolic wave-form, diastolic waveform, respiratory sinus arrhythmia, pulse amplitude and RIIVs were extracted. Using basic algorithms, the rates of false positive and false negative detection of breaths were calculated separately for each of the five components. Furthermore, a neural network was assessed in a combined pattern recognition approach. The error rates (sum of false positive and false negative breath detections) for the basic algorithms ranged from 9.7% (pulse amplitude) to 14.5% (systolic waveform). The corresponding values for the neural network analysis were 9.5-9.6%. These results suggest the use of a combined PPG system for simultaneous monitoring of respiratory rate and arterial oxygen saturation (pulse oximetry).

Influence of tidal volume and thoraco-abdominal separation on the respiratory induced variation of the photoplethysmogram

OBJECTIVE

The present study was aimed at determining the relative influences of tidal volume and thoraco-abdominal separation (relative thoracic and abdominal contribution to the tidal volume) on the respiratory induced intensity variation (RIIV) of the photoplethysmographic signal. The effects were studied in two body positions.

METHODS

Respiratory inductive plethysmography was used for quantifying thoraco-abdominal separation and for assessing tidal volumes. 10 subjects were trained to perform widely varying degrees of thoraco-abdominal separation at different tidal volumes. The relationship between the RIIV signal peak-to-peak value (measured at the forearm), and the tidal volume and thoraco-abdominal separation was investigated in two body positions with the use of multiple linear regression.

RESULTS

Larger tidal volume and more thoracic contribution to respiration were found to increase the RIIV peak-to-peak value (p < 0.0005). In the supine position, the tidal volume influence was stronger than that of thoraco-abdominal separation, and in the sitting position, the opposite was seen.

CONCLUSIONS

The effects on the RIIV signal following changes in thoraco-abdominal separation and tidal volume are of the same order of magnitude. In the supine position, the influence of thoracic versus abdominal contribution to the tidal volume is not as significant as in the sitting position. Photoplethysmography is a promising technique for combined monitoring of several respiratory parameters, including tidal volume. In situations where the relative thoracic and abdominal contributions are likely to vary, the tidal volume information becomes less reliable.