Continuous Monitoring Of Respiratory Rate Research Articles

Wearable Masks Integrated with Conducting Polymer and Carbon-Based Nanomaterials for VOC and Breath Monitoring

There has been considerable effort to develop wearable electronics from life-supporting devices for solders to fashion accessories such as smartwatches. The research of gas sensors has also attempted to adapt wearables with the power of nanotechnology. On the wearable platform, miniature gas sensors will provide real-time information about the atmosphere to protect each personnel from possible hazardous chemical attacks. In addition, wearable gas sensors can be facilitated to monitor human’s breath as medical applications. [1] Continuous monitoring of respiratory rate in real-time can act as a crucial benchmark for non-invasively detecting cardiac or arterial vascular function. Anomalies in respiratory rate serve as a significant indicator of a patient's health deterioration. Furthermore, it has been reported that aberrations in respiratory rate, as a physiological parameter, can be utilized to monitor common COVID-19 symptoms [2]. The analysis of breath through identifying biomarkers in exhaled breath proves to be an effective method for assessing metabolic disorders or dysfunctions in the human body. Conducting polymers (CPs) have generated significant interest in constructing flexible gas sensors. The inherent issue with pure CPs lies in their tendency to deprotonate in the presence of air, leading to a notable decline in long-term stability. Furthermore, limited gas response on diverse gaseous species demands the exploration of hybridizing CPs and other nanomaterials. When nanomaterials are hybridized with CPs, a synergistic effect, which comes from the benefits of each material, can improve sensing performance.In this study, polyaniline (PANI) conducting polymer and carbon-based nanomaterials, including carbon nanotubes (CNTs), graphene, or MXene were synthesized in a composite form and deposited into disposable masks. The developed gas sensor demonstrates remarkable stability attributed to the presence of van der Waals forces and π–π interactions between carbon-based nanomaterials and polyaniline (PANI). This stability is crucial for its reliable performance over time. The sensor's sensitivity is notably improved due to enhanced charge transfer channels and a porous structure that facilitates the adsorption of target gas. Additionally, the composite sensors detect breathing patterns in real-time, which demonstrates noninvasive human breath monitoring. A noteworthy aspect is that a significant portion of breath signals originates from the presence of target gases and moisture in exhaled breath. Although volatile sulfur compounds, CO2, and volatile organic compounds in the exhaled breath have a minimal influence on the sensing signals, the sensor remains highly responsive to the key components, particularly target gas by selecting carbon-based nanomaterials [3, 4]. The proposed gas sensing mechanism of the CP-based composites is discussed.

Machine Learning-Based Respiration Rate and Blood Oxygen Saturation Estimation Using Photoplethysmogram Signals

The continuous monitoring of respiratory rate (RR) and oxygen saturation (SpO2) is crucial for patients with cardiac, pulmonary, and surgical conditions. RR and SpO2 are used to assess the effectiveness of lung medications and ventilator support. In recent studies, the use of a photoplethysmogram (PPG) has been recommended for evaluating RR and SpO2. This research presents a novel method of estimating RR and SpO2 using machine learning models that incorporate PPG signal features. A number of established methods are used to extract meaningful features from PPG. A feature selection approach was used to reduce the computational complexity and the possibility of overfitting. There were 19 models trained for both RR and SpO2 separately, from which the most appropriate regression model was selected. The Gaussian process regression model outperformed all the other models for both RR and SpO2 estimation. The mean absolute error (MAE) for RR was 0.89, while the root-mean-squared error (RMSE) was 1.41. For SpO2, the model had an RMSE of 0.98 and an MAE of 0.57. The proposed system is a state-of-the-art approach for estimating RR and SpO2 reliably from PPG. If RR and SpO2 can be consistently and effectively derived from the PPG signal, patients can monitor their RR and SpO2 at a cheaper cost and with less hassle.

Continuous Monitoring of Respiratory Rate with Wearable Sensor in Patients Admitted to Hospital with Pneumonia Compared with Intermittent Nurse-Led Monitoring in the United Kingdom: A Cost-Utility Analysis.

BackgroundRespiratory rate (RR) is one of the most important physiologic measures for predicting patients’ deterioration of clinical condition and final prognosis. In several studies, RR has been the most important predictor of patients’ prognoses.ObjectivesThe objective of this study was to conduct a cost-utility analysis to estimate the cost and effectiveness of automatic respiratory rate monitoring (ARRM) with a non-invasive sensor (RespiraSense™) plus intermittent nurse-led RR monitoring (ARRM strategy) compared with intermittent nurse-led RR monitoring (IM strategy) in patients admitted to hospital in the UK with pneumonia.MethodsA decision analytic model was developed based on a hypothetical cohort of patients who were admitted to hospital with pneumonia. After admission, the patients could be monitored with either ARRM or IM strategies. The outcomes of interest included total costs and total effectiveness of each strategy, including length of stay (LoS) in hospital, LoS in intensive care unit, quality-adjusted life-years (QALYs), deaths, and incremental cost per QALY gained. An incremental cost of £20,000 or less per QALY gained was considered cost effective. A lifetime time horizon (38 years) was used to capture the long-term benefits. Probabilistic and deterministic sensitivity analyses were performed.ResultsTotal costs of patient care in ARRM and IM strategies were £1986.9 million and £2079.4 million, respectively. Total incremental QALYs lived were 3548 higher in the intervention arm (ARRM), meaning that the ARRM strategy was dominant (i.e., less costly [£92.6 million less] and more effective). The results were stable in probabilistic and most of the deterministic sensitivity analyses. Results from threshold analysis indicated that a minimum of 7 and 10% improvement in percentage of early detection of respiratory compromise is required for ARRM to become cost effective and cost saving, respectively.ConclusionsOur results indicate that ARRM using RespiraSense, in addition to intermittent nurse-led monitoring of RR, in patients admitted to the hospital with pneumonia could be a cost-saving and cost-effective intervention if the minimum clinical thresholds are met.

Validation of a New Contactless and Continuous Respiratory Rate Monitoring Device Based on Ultra-Wideband Radar Technology.

Respiratory rate (RR) is typically the first vital sign to change when a patient decompensates. Despite this, RR is often monitored infrequently and inaccurately. The Circadia Contactless Breathing Monitor™ (model C100) is a novel device that uses ultra-wideband radar to monitor RR continuously and un-obtrusively. Performance of the Circadia Monitor was assessed by direct comparison to manually scored reference data. Data were collected across a range of clinical and non-clinical settings, considering a broad range of user characteristics and use cases, in a total of 50 subjects. Bland–Altman analysis showed high agreement with the gold standard reference for all study data, and agreement fell within the predefined acceptance criteria of ±5 breaths per minute (BrPM). The 95% limits of agreement were −3.0 to 1.3 BrPM for a nonprobability sample of subjects while awake, −2.3 to 1.7 BrPM for a clinical sample of subjects while asleep, and −1.2 to 0.7 BrPM for a sample of healthy subjects while asleep. Accuracy rate, using an error margin of ±2 BrPM, was found to be 90% or higher. Results demonstrate that the Circadia Monitor can effectively and efficiently be used for accurate spot measurements and continuous bedside monitoring of RR in low acuity settings, such as the nursing home or hospital ward, or for remote patient monitoring.

The effectiveness of continuous respiratory rate monitoring in predicting hypoxic and pyrexic events: a retrospective cohort study

Respiratory rate (RR) is routinely used to monitor patients with infectious, cardiac and respiratory diseases and is a component of early warning scores used to predict patient deterioration. However, it is often measured visually with considerable bias and inaccuracy. Objectives. Firstly, to compare distribution and accuracy of electronically measured RR (EMRR) and visually measured RR (VMRR). Secondly, to determine whether, and how far in advance, continuous electronic RR monitoring can predict oncoming hypoxic and pyrexic episodes in infectious respiratory disease. Approach. A retrospective cohort study analysing the difference between EMRR and VMRR was conducted using patient data from a large tertiary hospital. Cox proportional hazards models were used to determine whether continuous, EMRR measurements could predict oncoming hypoxic (SpO2 < 92%) and pyrexic (temperature >38 °C) episodes. Main results. Data were gathered from 34 COVID-19 patients, from which a total of 3445 observations of VMRR (independent of Hawthorne effect), peripheral oxygen saturation and temperature and 729 117 observations of EMRR were collected. VMRR had peaks in distribution at 18 and 20 breaths per minute. 70.9% of patients would have had a change of treatment during their admission based on the UK’s National Early Warning System if EMRR was used in place of VMRR. An elevated EMRR was predictive of hypoxic (hazard ratio: 1.8 (1.05–3.07)) and pyrexic (hazard ratio: 9.7 (3.8–25)) episodes over the following 12 h. Significance. Continuous EMRR values are systematically different to VMRR values, and results suggest it is a better indicator of true RR as it has lower kurtosis, higher variance, a lack of peaks at expected values (18 and 20) and it measures a physiological component of breathing directly (abdominal movement). Results suggest EMRR is a strong marker of oncoming hypoxia and is highly predictive of oncoming pyrexic events in the following 12 h. In many diseases, this could provide an early window to escalate care prior to deterioration, potentially preventing morbidity and mortality.

Piezoelectric Sensor-Based Continuous Monitoring of Respiratory Rate During Sleep

Respiration during sleep is one of the indicators of an individual’s health. However, many respiratory measurement devices need to be worn by the patient and can affect sleep. We introduce here a novel, easy-to-use, respiratory rate-monitoring sensor made of stretchable piezoelectric material that can be used conveniently at home as well as in a clinical setting. We enrolled 6 members of a family as volunteers ranging in age from 9 months to 69 years. The sensor was used to continuously record respiratory rate data for all individuals during sleep. The sensor could detect known breathing patterns such as stable, unstable, or deep breathing as well as apnea during sleep. We observed significant differences in the respiratory rates and respiratory stability between subjects during sleep. The piezoelectric sensor was effective in people in all age groups, paving a way for future use as a convenient and reliable mode of respiratory assessment for adults as well as neonates at home and in a clinical setting.

Incidence of Respiratory Depression After Epidural Administration of Morphine for Cesarean Delivery: Findings Using a Continuous Respiratory Rate Monitoring System

(Int J Obst Anesth. 2019;38:32–36) Epidural morphine is widely used for postcesarean analgesia. However, because of the risk of respiratory depression after neuraxial administration of morphine, the American Society of Anesthesiologists (ASA) recommends frequent respiratory rate monitoring in the 24 hours after administration. This has typically been assessed through intermittent manual counting of the respiratory rate—a practice that is prone to observer error and does not allow continuous monitoring. Using this technique has resulted in documented rates of respiratory depression after epidural or intrathecal morphine administration of 0% to 0.9%.This study aimed to estimate the incidence of respiratory depression using the Nellcor respiratory rate monitoring system, which allows continuous monitoring, in patients who received 3 mg of epidural morphine for postcesarean analgesia.

Accuracy of remote continuous respiratory rate monitoring technologies intended for low care clinical settings: a prospective observational study

PurposeAltered respiratory rate (RR) has been identified as an important predictor of serious adverse events during hospitalization. Introduction of a well-tolerated continuous RR monitor could potentially reduce serious adverse events such as opioid-induced respiratory depression. The purpose of this study was to investigate the ability of different monitor devices to detect RR in low care clinical settings.MethodsThis was a prospective method-comparison study with a cross-sectional design. Thoracic impedance pneumography (IPG), frequency modulated continuous wave radar, and an acoustic breath sounds monitor were compared with the gold standard of capnography for their ability to detect RR in breaths per minute (breaths·min−1) in awake postoperative patients in the postanesthesia care unit. The Bland and Altman method for repeated measurements and mixed effect modelling was used to obtain bias and limits of agreement (LoA). Furthermore, the ability of the three devices to assist with correct treatment decisions was evaluated in Clarke Error Grids.ResultsTwenty patients were monitored for 1,203 min, with a median [interquartile range] of 61 [60-63] min per patient. The bias (98.9% LoA) were 0.1 (−7.9 to 7.9) breaths·min−1 for the acoustic monitor, −1.6 (−10.8 to 7.6) for the radar, and −1.9 (−13.1 to 9.2) for the IPG. The extent to which the monitors guided adequate or led to inadequate treatment decisions (determined by Clarke Error Grid analysis) differed significantly between the monitors (P = 0.011). Decisions were correct 96% of the time for acoustic, 95% of the time for radar, and 94% of the time for IPG monitoring devices.ConclusionsNone of the studied devices (acoustic, IPG, and radar monitor) had LoA that were within our predefined (based on clinical judgement) limits of ± 2 breaths·min−1. The acoustic breath sound monitor predicted the correct treatment more often than the IPG and the radar device.

MUSIC Algorithm for Respiratory Rate Estimation Using RF Signals

DOI: 10.26650/electrica.2018.03405 Continuous monitoring of respiratory rate (cycle) during sleep for diseases such as sleep apnea and sudden infant death syndrome (SIDS) can be lifesaving. Wireless radio communications signals are everywhere and can be harnessed for contactless monitoring of the respiratory rates. The amplitude of the received signal strength changes periodically depending on the exhalation and inhalation of the subject. In this paper, subspace-based multiple signal classification (MUSIC) algorithm is applied to estimate the respiratory rate for better results. The proposed method and the other power spectral density (PSD) methods for respiratory estimations are compared with the real laboratory measurements. It is demonstrated that the proposed method estimates the respiratory rate with high accuracy and outperforms the other PSD-based methods which are commonly used in the literature.

Accelerometry-Based Estimation of Respiratory Rate for Post-Intensive Care Patient Monitoring

This paper evaluates the use of accelerometers for continuous monitoring of respiratory rate (RR), which is an important vital sign in post-intensive care patients or those inside the intensive care unit (ICU). The respiratory rate can be estimated from accelerometer and photoplethysmography (PPG) signals for patients following ICU discharge. Due to sensor faults, sensor detachment, and various artifacts arising from motion, RR estimates derived from accelerometry and PPG may not be sufficiently reliable for use with existing algorithms. This paper described a case study of 10 selected patients, for which fewer RR estimates have been obtained from PPG signals in comparison to those from accelerometry. We describe an algorithm for which we show a maximum mean absolute error between estimates derived from PPG and accelerometer of 2.56 breaths/min. Our results obtained using the 10 selected patients are highly promising for estimation of RR from accelerometers, where significant agreements have been observed with the PPG-based RR estimates in many segments and across various patients. We present this research as a step towards producing reliable RR monitoring systems using low-cost mobile accelerometers for monitoring patients inside the ICU or on the ward (post-ICU).

A pulse transit time based fusion method for the noninvasive and continuous monitoring of respiratory rate.

The purpose of this study was to investigate whether pulse transit time (PTT) can be used for continuous monitoring of respiratory rate (RR). We derived PTT from the electrocardiogram and photoplethysmogram obtained from 42 recordings of CapnoBase, a publicly available benchmark data set for validating respiratory related measurements. The number of breaths in a minute (RR#) was estimated from the heart rate interval (HRI), pulse rate interval (PRI), and from PTT. In addition, to improve the estimation reliability, we investigated a fusion of the three HRI, PRI and PTT derived estimations. The root mean squared error (RSME) and a Bland-Altman plot were calculated using RR from capnography as reference. Finally, the proposed method was compared against the CapnoBase Smart Fusion RR benchmark estimation which estimates RR with three parameters extracted from the PPG signal alone. Thirty-seven recordings showed sufficient signal quality to estimate RR from PTT. The fused RR (RMSE 1.76 breaths/min) was more accurate than the estimations from PTT (RMSE 2.63 breaths/min), HRI (RMSE 1.96 breaths/min), and PRI (RMSE 2.73 breaths/min) alone. The proposed method also outperformed the CapnoBase benchmark (RMSE 3.08 breaths/min) algorithm. This study demonstrates that PTT is a valuable noninvasive parameter from which RR can be estimated.

Assessment of continuous acoustic respiratory rate monitoring as an addition to a pulse oximetry-based patient surveillance system.

Technology advances make it possible to consider continuous acoustic respiratory rate monitoring as an integral component of physiologic surveillance systems. This study explores technical and logistical aspects of augmenting pulse oximetry-based patient surveillance systems with continuous respiratory rate monitoring and offers some insight into the impact on patient deterioration detection that may result. Acoustic respiratory rate sensors were introduced to a general care pulse oximetry-based surveillance system with respiratory rate alarms deactivated. Simulation was used after 4324 patient days to determine appropriate alarm thresholds for respiratory rate, which were then activated. Data were collected for an additional 4382 patient days. Physiologic parameters, alarm data, sensor utilization and patient/staff feedback were collected throughout the study and analyzed. No notable technical or workflow issues were observed. Sensor utilization was 57%, with patient refusal leading reasons for nonuse (22.7%). With respiratory rate alarm thresholds set to 6 and 40breaths/min., the majority of nurse pager clinical notifications were triggered by low oxygen saturation values (43%), followed by low respiratory rate values (21%) and low pulse rate values (13%). Mean respiratory rate collected was 16.6±3.8breaths/min. The vast majority (82%) of low oxygen saturation states coincided with normal respiration rates of 12-20breaths/min. Continuous respiratory rate monitoring can be successfully added to a pulse oximetry-based surveillance system without significant technical, logistical or workflow issues and is moderately well-tolerated by patients. Respiratory rate sensor alarms did not significantly impact overall system alarm burden. Respiratory rate and oxygen saturation distributions suggest adding continuous respiratory rate monitoring to a pulse oximetry-based surveillance system may not significantly improve patient deterioration detection.

Acoustic method respiratory rate monitoring is useful in patients under intravenous anesthesia

Respiratory depression can occur during intravenous general anesthesia without tracheal intubation. A new acoustic method for respiratory rate monitoring, RRa® (Masimo Corp., Tokyo, Japan), has been reported to show good reliability in post-anesthesia care and emergency units. The purpose of this study was to investigate the reliability of the acoustic method for measurement of respiratory rate during intravenous general anesthesia, as compared with capnography. Patients with dental anxiety undergoing dental treatment under intravenous anesthesia without tracheal intubation were enrolled in this study. Respiratory rate was recorded every 30s using the acoustic method and capnography, and detectability of respiratory rate was investigated for both methods. This study used a cohort study design. In 1953 recorded respiratory rate data points, the number of detected points by the acoustic method (1884, 96.5%) was significantly higher than that by capnography (1682, 86.1%) (P<0.0001). In the intraoperative period, there was a significant difference in the LOA (95% limits of agreement of correlation between difference and average of the two methods)/ULLOA (under the lower limit of agreement) in terms of use or non-use of a dental air turbine (P<0.0001). In comparison between capnography, the acoustic method is useful for continuous monitoring of respiratory rate in spontaneously breathing subjects undergoing dental procedures under intravenous general anesthesia. However, the acoustic method might not accurately detect in cases in with dental air turbine.

Usefulness of Acoustic Monitoring of Respiratory Rate in Patients Undergoing Endoscopic Submucosal Dissection.

Aim. The study assessed the usefulness of a recently developed method for respiratory rate (RR) monitoring in patients undergoing endoscopic submucosal dissection (ESD) under deep sedation. Methods. Study subjects comprised 182 consecutive patients with esophageal cancer or gastric cancer undergoing ESD. The usefulness of acoustic RR monitoring was assessed by retrospectively reviewing the patients' records for age, gender, height, weight, past history, serum creatinine, RR before ESD, and total dose of sedative. Results. Respiratory suppression was present in 37.9% of (69/182) patients. Continuous monitoring of RR led to detection of respiratory suppression in all these patients. RR alone was decreased in 24 patients, whereas both RR and blood oxygen saturation were decreased in 45 patients. Univariate analysis showed female gender, height, weight, and RR before treatment to be significantly associated with respiratory suppression. Multivariate analysis showed RR before treatment to be the only significant independent predictor [odds ratio (OR) 0.83, 95% confidence interval (CI) 0.73–0.95, and P = 0.006] of respiratory suppression. Conclusion. In this study, the difference in RR before treatment between patients with and without respiratory suppression was subtle. Therefore, we suggest that acoustic RR monitoring should be considered in patients undergoing ESD under sedation to prevent serious respiratory complications.

A non-contact vision-based system for respiratory rate estimation.

A non-contact vision-based system is presented for continuous respiratory rate monitoring. The system identifies feature points in a video feed and tracks them over time. Two methods are presented for comparison - a method which uses principal component analysis (PCA) and a simple averaging approach. These methods condense the feature point trajectories into a compact set of representative signals. The signal which most closely resembles an expected respiratory trace is selected based on spectral analysis. System performance is assessed by comparing the estimated respiratory rate to the rate determined via inductance plethysmogram. The system was evaluated on 5 participants in 4 simulated sleep scenarios. Accuracies of within 1 breath/minute were achieved for more than 97% of the recorded time in all scenarios. The proposed system is accurate, cost-effective, and simple, making it a suitable candidate for at-home installation.

Pulse oximetry-derived respiratory rate in general care floor patients.

Respiratory rate is recognized as a clinically important parameter for monitoring respiratory status on the general care floor (GCF). Currently, intermittent manual assessment of respiratory rate is the standard of care on the GCF. This technique has several clinically-relevant shortcomings, including the following: (1) it is not a continuous measurement, (2) it is prone to observer error, and (3) it is inefficient for the clinical staff. We report here on an algorithm designed to meet clinical needs by providing respiratory rate through a standard pulse oximeter. Finger photoplethysmograms were collected from a cohort of 63 GCF patients monitored during free breathing over a 25-min period. These were processed using a novel in-house algorithm based on continuous wavelet-transform technology within an infrastructure incorporating confidence-based averaging and logical decision-making processes. The computed oximeter respiratory rates (RRoxi) were compared to an end-tidal CO2 reference rate (RRETCO2). RRETCO2 ranged from a lowest recorded value of 4.7 breaths per minute (brpm) to a highest value of 32.0 brpm. The mean respiratory rate was 16.3 brpm with standard deviation of 4.7 brpm. Excellent agreement was found between RRoxi and RRETCO2, with a mean difference of −0.48 brpm and standard deviation of 1.77 brpm. These data demonstrate that our novel respiratory rate algorithm is a potentially viable method of monitoring respiratory rate in GCF patients. This technology provides the means to facilitate continuous monitoring of respiratory rate, coupled with arterial oxygen saturation and pulse rate, using a single non-invasive sensor in low acuity settings.

Electromagnetic Biosensing of Respiratory Rate

Continuous monitoring of respiratory rate is crucial in forecasting health crises and other major physiological instabilities. Current respiratory monitoring methods limit the mobility of the patient or require constant battery replacement. Wireless, wearable technology can collect continuous physiological data without immobilizing or inconveniencing patients, and human energy harvesting can be used to power these wearable sensors. In this paper, we explore this zero-net energy biosensor concept through simultaneous sensing and harvesting of respiratory effort. An off-the-shelf dc brushed motor is modified into a chest belt, and tested on a mechanical chest simulator as well as on 20 human subjects, using a spirometer as a reference. The electromagnetic biosensor is used to successfully harvest 7-70 μW from human subjects. On the mechanical chest, respiratory rate is detected with a mean absolute error of 0.00027 breaths/min with a standard deviation of 0.00019 breaths/min. For human subjects, respiratory rate is detected with a mean difference of 0.36 breaths/min with a standard deviation of 2.83 breaths/min (sitting), 0.23 breaths/min with a standard deviation of 2.64 breaths/min (standing), and 0.48 breaths/min with a standard deviation of 3.06 breaths/min (walking).

Pulmonary and cardiac sequelae of subarachnoid haemorrhage: time for active management?

Cardiac injury and pulmonary oedema occurring after acute neurological injury have been recognised for more than a century. Catecholamines, released in massive quantities due to hypothalamic stress from subarachnoid haemorrhage (SAH), result in specific myocardial lesions and hydrostatic pressure injury to the pulmonary capillaries causing neurogenic pulmonary oedema (NPO). The acute, reversible cardiac injury ranges from hypokinesis with a normal cardiac index, to low output cardiac failure. Some patients exhibit both catastrophic cardiac failure and NPO, while others exhibit signs of either one or other, or have subclinical evidence of the same. Hypoxia and hypotension are two of the most important insults which influence outcome after acute brain injury. However, despite this, little attention has hitherto been devoted to prevention and reversal of these potentially catastrophic medical complications which occur in patients with SAH. It is not clear which patients with SAH will develop important cardiac and respiratory complications. An active approach to investigation and organ support could provide a window of opportunity to intervene before significant hypoxia and hypotension develop, potentially reducing adverse consequences for the long-term neurological status of the patient. Indeed, there is an argument for all SAH patients to have echocardiography and continuous monitoring of respiratory rate, pulse oximetry, blood pressure and electrocardiogram. In the event of cardio-respiratory compromise developing i.e. cardiogenic shock and/or NPO, full investigation, attentive monitoring and appropriate intervention are required immediately to optimise cardiorespiratory function and allow subsequent definitive management of the SAH.

Electrical Impedance Pneumography for Simple Nonrestrictive Continuous Monitoring of Respiratory Rate, Rhythm and Tidal Volume for Surgical Patients

Controversial reports concerning theory and use of impedance pneumography necessitated clinical evaluation of the technique. Recorded data from nine control subjects, 12 patients during surgical anesthesia, and seven patients during recovery from surgery form the basis of the study. Useful correlation (mean r=0.89) was obtained between impedance waveform amplitude and tidal volume during surgical anesthesia. Control correlation was about the same (mean r=0.87). Artifacts were easily recognized and not a problem. Intentional complete airway obstruction was easily detected by this noninvasive method. The monitoring equipment was easy to use, electrically safe, and the ability to obtain the ECG from the same electrodes make it especially useful during surgical anesthesia and in the recovery room.