Electrical impedance pneumography for simple nonrestrictive continuous monitoring of respiratory rate, rhythm and tidal volume for surgical patients

Impedance-Based Ventilation Detection and Signal Quality Control During Out-of-Hospital Cardiopulmonary Resuscitation

Feedback on ventilation could help improve cardiopulmonary resuscitation quality and survival from out-of-hospital cardiac arrest (OHCA). However, current technology that monitors ventilation during OHCA is very limited. Thoracic impedance (TI) is sensitive to air volume changes in the lungs, allowing ventilations to be identified, but is affected by artifacts due to chest compressions and electrode motion. This study introduces a novel algorithm to identify ventilations in TI during continuous chest compressions in OHCA. Data from 367 OHCA patients were included, and 2551 one-minute TI segments were extracted. Concurrent capnography data were used to annotate 20724 ground truth ventilations for training and evaluation. A three-step procedure was applied to each TI segment: First, bidirectional static and adaptive filters were applied to remove compression artifacts. Then, fluctuations potentially due to ventilations were located and characterized. Finally, a recurrent neural network was used to discriminate ventilations from other spurious fluctuations. A quality control stage was also developed to anticipate segments where ventilation detection could be compromised. The algorithm was trained and tested using 5-fold cross-validation, and outperformed previous solutions in the literature on the study dataset. The median (interquartile range, IQR) per-segment and per-patient F 1-scores were 89.1 (70.8-99.6) and 84.1 (69.0-93.9), respectively. The quality control stage identified most low performance segments. For the 50% of segments with highest quality scores, the median per-segment and per-patient F 1-scores were 100.0 (90.9-100.0) and 94.3 (86.5-97.8). The proposed algorithm could allow reliable, quality-conditioned feedback on ventilation in the challenging scenario of continuous manual CPR in OHCA.

RF Sensing Based Breathing Patterns Detection Leveraging USRP Devices

Non-contact detection of the breathing patterns in a remote and unobtrusive manner has significant value to healthcare applications and disease diagnosis, such as in COVID-19 infection prediction. During the epidemic prevention and control period of COVID-19, non-contact approaches have great significance because they minimize the physical burden on the patient and have the least requirement of active cooperation of the infected individual. During the pandemic, these non-contact approaches also reduce environmental constraints and remove the need for extra preparations. According to the latest medical research, the breathing pattern of a person infected with COVID-19 is unlike the breathing associated with flu and the common cold. One noteworthy symptom that occurs in COVID-19 is an abnormal breathing rate; individuals infected with COVID-19 have more rapid breathing. This requires continuous real-time detection of breathing patterns, which can be helpful in the prediction, diagnosis, and screening for people infected with COVID-19. In this research work, software-defined radio (SDR)-based radio frequency (RF) sensing techniques and machine learning (ML) algorithms are exploited to develop a platform for the detection and classification of different abnormal breathing patterns. ML algorithms are used for classification purposes, and their performance is evaluated on the basis of accuracy, prediction speed, and training time. The results show that this platform can detect and classify breathing patterns with a maximum accuracy of 99.4% through a complex tree algorithm. This research has a significant clinical impact because this platform can also be deployed for practical use in pandemic and non-pandemic situations.

An impedance pneumography signal quality index: Design, assessment and application to respiratory rate monitoring

Impedance pneumography (ImP) is widely used for respiratory rate (RR) monitoring. However, ImP-derived RRs can be imprecise. The aim of this study was to develop a signal quality index (SQI) for the ImP signal, and couple it with a RR algorithm, to improve RR monitoring. An SQI was designed which identifies candidate breaths and assesses signal quality using: the variation in detected breath durations, how well peaks and troughs are defined, and the similarity of breath morphologies. The SQI categorises 32 s signal segments as either high or low quality. Its performance was evaluated using two critical care datasets. RRs were estimated from high-quality segments using a RR algorithm, and compared with reference RRs derived from manual annotations. The SQI had a sensitivity of 77.7 %, and specificity of 82.3 %. RRs estimated from segments classified as high quality were accurate and precise, with mean absolute errors of 0.21 and 0.40 breaths per minute (bpm) on the two datasets. Clinical monitor RRs were significantly less precise. The SQI classified 34.9 % of real-world data as high quality. In conclusion, the proposed SQI accurately identifies high-quality segments, and RRs estimated from those segments are precise enough for clinical decision making. This SQI may improve RR monitoring in critical care. Further work should assess it with wearable sensor data.

A Novel, Contactless, Portable “Spot-Check” Device Accurately Measures Respiratory Rate

Respiratory rate (RR) is an important vital sign used in the initial and ongoing assessment of acutely ill patients. It is also used as a predictor of serious deterioration in a patient's clinical condition. Convenient electronic devices exist for measurement of pulse, blood pressure, oxygen saturation, and temperature. Although devices which measure RR exist, none has entered everyday clinical practice. We have developed a contactless portable respiratory rate monitor (CPRM) and evaluated the agreement in respiratory rate measurements between existing methods and our new device. The CPRM uses thermal anemometry to measure breath signals during inspiration and expiration. RR data were collected from 52 healthy adult volunteers using respiratory inductance plethysmography (RIP) bands (established contact method), visual counting of chest movements (established noncontact method), and the CPRM (new method), simultaneously. Two differently shaped funnel attachments to the CPRM were evaluated for each volunteer. Data showed a good agreement between measurements from the CPRM and the gold standard RIP, with intraclass correlation coefficient (ICC): 0.836, mean difference 0.46 and 95% limits of agreement of −5.90 to 6.83. When separate air inlet funnels of the CPRM were analyzed, stronger agreement was seen with an elliptical air inlet; ICC 0.908, mean difference 0.37 with 95% limits of agreement −4.35 to 5.08. A contactless device for accurately and quickly measuring respiratory rate will be an important triage tool in the clinical assessment of patients. More testing is needed to explore the reasons for outlying measurements and to evaluate in the clinical setting.

Small-Scale Perception in Medical Body Area Networks

Objective: Non-invasive respiration detection methods are of great value to healthcare applications and disease diagnosis with their advantages of minimizing the patient’s physical burden and lessen the requirement of active cooperation of the subject. This method avoids extra preparations, reduces environmental constraints, and strengthens the possibility of real-time respiratory detection. Furthermore, identifying abnormal breathing patterns in real-time is necessary for the diagnosis and monitoring of possible respiratory disorders. Method: A non-invasive method for detecting multiple breathing patterns using C-band sensing technique is presented, which is used for identifying different breathing patterns in addition to extract respiratory rate. We first evaluate the feasibility of this non-contact method in measuring different breathing patterns. Then, we detect several abnormal breathing patterns associated with certain respiratory disorders at real time using C-band sensing technique in indoor environment. Results: Mean square error (MSE) and correlation coefficient (CC) are used to evaluate the correlation between C-band sensing technique and contact respiratory sensor. The results show that all the MSE are less than 0.6 and all CC are more than 0.8, yielding a significant correlation between the two used for detecting each breathing pattern. Clinical Impact: C-band sensing technique is not only used to determine respiratory rates but also to identify breathing patterns, regarding as a preferred noncontact alternative approach to the traditional contact sensing methods. C-band sensing technique also provides a basis for the non-invasive detection of certain respiratory disorders.

Association of ventilation with outcomes from out-of-hospital cardiac arrest

AIM OF STUDY

To determine the association between bioimpedence-detected ventilation and out-of-hospital cardiac arrest (OHCA) outcomes.

METHODS

This is a retrospective, observational study of 560 OHCA patients from the Dallas-Fort Worth site enrolled in the Resuscitation Outcomes Consortium Trial of Continuous or Interrupted Chest Compressions During CPR from 4/2012 to 7/2015. We measured bioimpedance ventilation (lung inflation) waveforms in the pause between chest compression segments (Physio-Control LIFEPAK 12 and 15, Redmond, WA) recorded through defibrillation pads. We included cases ≥18 years with presumed cardiac cause of arrest assigned to interrupted 30:2 chest compressions with bag-valve-mask ventilation and ≥2 min of recorded cardiopulmonary resuscitation. We compared outcomes in two a priori pre-specified groups: patients with ventilation waveforms in <50% of pauses (Group 1) versus those with waveforms in ≥50% of pauses (Group 2).

RESULTS

Mean duration of 30:2 CPR was 13 ± 7 min with a total of 7762 pauses in chest compressions. Group 1 (N = 424) had a median 11 pauses and 3 ventilations per patient vs. Group 2 (N = 136) with a median 12 pauses and 8 ventilations per patient, which was associated with improved return of spontaneous circulation (ROSC) at any time (35% vs. 23%, p < 0.005), prehospital ROSC (19.8% vs. 8.7%, p < 0.0009), emergency department ROSC (33% vs. 21%, p < 0.005), and survival to hospital discharge (10.3% vs. 4.0%, p = 0.008).

CONCLUSIONS

This novel study shows that ventilation with lung inflation occurs infrequently during 30:2 CPR. Ventilation in ≥50% of pauses was associated with significantly improved rates of ROSC and survival.

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

Purpose

Altered 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.

Methods

This 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.

Results

Twenty 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.

Conclusions

None 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.

Electronic supplementary material

The online version of this article (10.1007/s12630-018-1214-z) contains supplementary material, which is available to authorized users.

Reliability of wireless monitoring using a wearable patch sensor in high-risk surgical patients at a step-down unit in the Netherlands: a clinical validation study

BACKGROUND AND OBJECTIVES

Intermittent vital signs measurements are the current standard on hospital wards, typically recorded once every 8 hours. Early signs of deterioration may therefore be missed. Recent innovations have resulted in 'wearable' sensors, which may capture patient deterioration at an earlier stage. The objective of this study was to determine whether a wireless 'patch' sensor is able to reliably measure respiratory and heart rate continuously in high-risk surgical patients. The secondary objective was to explore the potential of the wireless sensor to serve as a safety monitor.

DESIGN

In an observational methods comparisons study, patients were measured with both the wireless sensor and bedside routine standard for at least 24 hours.

SETTING

University teaching hospital, single centre.

PARTICIPANTS

Twenty-five postoperative surgical patients admitted to a step-down unit.

OUTCOME MEASURES

Primary outcome measures were limits of agreement and bias of heart rate and respiratory rate. Secondary outcome measures were sensor reliability, defined as time until first occurrence of data loss.

RESULTS

1568 hours of vital signs data were analysed. Bias and 95% limits of agreement for heart rate were -1.1 (-8.8 to 6.5) beats per minute. For respiration rate, bias was -2.3 breaths per minute with wide limits of agreement (-15.8 to 11.2 breaths per minute). Median filtering over a 15 min period improved limits of agreement of both respiration and heart rate. 63% of the measurements were performed without data loss greater than 2 min. Overall data loss was limited (6% of time).

CONCLUSIONS

The wireless sensor is capable of accurately measuring heart rate, but accuracy for respiratory rate was outside acceptable limits. Remote monitoring has the potential to contribute to early recognition of physiological decline in high-risk patients. Future studies should focus on the ability to detect patient deterioration on low care environments and at home after discharge.

Electrical Bioimpedance Spectroscopy on Acute Unilateral Stroke Patients: Initial Observations regarding Differences between Sides

PURPOSE

Electrical Bioimpedance Cerebral Monitoring is assessment in real time of health of brain tissue through study of passive dielectric properties of brain. During the last two decades theory and technology have been developed in parallel with animal experiments aiming to confirm feasibility of using bioimpedance-based technology for prompt detection of brain damage. Here, for the first time, we show that electrical bioimpedance measurements for left and right hemispheres are significantly different in acute cases of unilateral stroke within 24 hours from onset.

METHODS

Electrical BIS measurements have been taken in healthy volunteers and patients suffering from acute stroke within 24 hours of onset. BIS measurements have been obtained using SFB7 bioimpedance spectrometer manufactured by Impedimed ltd. and 4-electrode method. Measurement electrodes, current, and voltage have been placed according to 10-20 EEG system obtaining mutual BIS measurements from 4 different channels situated in pairs symmetrically from the midsagittal line. Obtained BIS data has been analyzed, assessing for symmetries and differences regarding healthy control data.

RESULTS

7 out of 10 patients for Side-2-Side comparisons and 8 out 10 for central/lateral comparison presented values outside the range defined by healthy control group. When combined only 1 of 10 patients exhibited values within the healthy range.

CONCLUSIONS

If these initial observations are confirmed with more patients, we can foresee emerging of noninvasive monitoring technology for brain damage with the potential to lead to paradigm shift in treatment of brain stroke and traumatic brain damage.

Polyvinylidene fluoride film based nasal sensor to monitor human respiration pattern: an initial clinical study

Design and development of a piezoelectric polyvinylidene fluoride (PVDF) thin film based nasal sensor to monitor human respiration pattern (RP) from each nostril simultaneously is presented in this paper. Thin film based PVDF nasal sensor is designed in a cantilever beam configuration. Two cantilevers are mounted on a spectacle frame in such a way that the air flow from each nostril impinges on this sensor causing bending of the cantilever beams. Voltage signal produced due to air flow induced dynamic piezoelectric effect produce a respective RP. A group of 23 healthy awake human subjects are studied. The RP in terms of respiratory rate (RR) and Respiratory air-flow changes/alterations obtained from the developed PVDF nasal sensor are compared with RP obtained from respiratory inductance plethysmograph (RIP) device. The mean RR of the developed nasal sensor (19.65 ± 4.1) and the RIP (19.57 ± 4.1) are found to be almost same (difference not significant, p > 0.05) with the correlation coefficient 0.96, p < 0.0001. It was observed that any change/alterations in the pattern of RIP is followed by same amount of change/alterations in the pattern of PVDF nasal sensor with k = 0.815 indicating strong agreement between the PVDF nasal sensor and RIP respiratory air-flow pattern. The developed sensor is simple in design, non-invasive, patient friendly and hence shows promising routine clinical usage. The preliminary result shows that this new method can have various applications in respiratory monitoring and diagnosis.

Accuracy of respiratory rate monitoring by capnometry using the Capnomask(R) in extubated patients receiving supplemental oxygen after surgery

BACKGROUND

Respiratory monitoring is standard after anaesthesia and surgery. Abnormal respiratory rate is a sensitive indicator of respiratory problems, even in patients receiving supplemental oxygen, but the best method for its continuous measurement in spontaneously breathing patients is unclear. This study compared respiratory rate assessment by capnometry using a new oxygen mask with a carbon dioxide sampling port (Capnomask(®)) and thoracic impedance pneumography with clinical measurement (used as a reference method) in extubated patients receiving supplemental oxygen.

METHODS

Adult males admitted to the post-anaesthesia care unit after general anaesthesia were studied. Immediately after extubation, a Capnomask(®) connected to a capnometer was positioned appropriately. Respiratory rate was measured by visual inspection of chest movement for 1 min, by capnometry, and thoracic impedance pneumography. One set of measurements was obtained for every patient receiving supplemental oxygen at different flow rates.

RESULTS

Twenty men, mean (inter-quartile range) age 54 (23-66) yr and BMI 25 (21-31) kg m(-2), were studied. Compared with visual inspection, the bias and limits of agreement were 0.0 (1.0 to -1.0) bpm for the Capnomask(®) and -2.2 (2.0 to -6.5) bpm for the impedance pneumography. The accuracy of respiratory rate assessment using Capnomask(®) was not influenced by the supplemental oxygen flow rate.

CONCLUSIONS

In extubated patients, continuous assessment of respiratory rate with the Capnomask(®) is more accurate than by thoracic impedance pneumography even when supplemental oxygen is delivered at a high flow rate.

Contactless respiratory and heart rate monitoring: validation of an innovative tool

PRIMARY OBJECTIVE

To assess the accuracy of the EverOn™ piezoelectric sensor based contactless heart rate and respiration rate monitoring system.

METHODS

Measurements of the EverOn™ and reference devices were performed in a sleep lab and an intensive care unit (ICU) setting. One minute measurements by both the reference device and the EverOn™ were averaged and compared. Accuracy was defined in accordance with industry criteria.

RESULTS

Respiration rate (RR) accuracy in the 41 children and 16 adults evaluated in the sleep lab was 93.1% and 90.6% respectively, and heart rate (HR) accuracy was 94.4% and 91.5% respectively. For the 42 ICU patients RR accuracy was 82.0% and 75% (versus end-tidal CO(2) and manual respectively), while accuracy of HR was 94.0%. The EverOn™ was found to be superior to the impedance technique in measuring RR.

CONCLUSIONS

The system described was found to be accurate in accordance with regulatory and industry criteria.

Capnography Accurately Detects Apnea During Monitored Anesthesia Care

Apnea and airway obstruction are common during monitored anesthesia care (MAC). Because their early detection is essential, we sought to measure the efficacy of capnography as an indicator of apnea during MAC at a variety of oxygen flow rates compared with thoracic impedance. Anesthesia care providers using standard American Society of Anesthesiologists monitors were blinded to capnography and thoracic impedance monitoring. Ten (26%) of the 39 patients studied developed 20 s of apnea; none was detected by the anesthesia provider, but all were detected by capnography and impedance monitoring. There was no difference in detection rates between the two methods. Higher oxygen flow rates decreased the amplitude of the capnograph but did not interfere with apnea detection. This pilot study revealed that apnea of at least 20 s in duration may occur in every fourth patient undergoing MAC. Although these episodes were undetected by the anesthesia provider, they were reliably detected by both capnography and respiratory plethysmography. Monitoring of nasal end-tidal CO(2) is an important way to improve safety in patients undergoing MAC.

The validity of the static-charge-sensitive bed in the detection of fentanyl-induced respiratory depression

BACKGROUND

Only a few methods for the measurement of breathing are non-invasive and do not interfere with measured parameters. The static-charge-sensitive bed (SCSB) could be such a monitor. The aim of this study was to evaluate the validity of the SCSB compared with the respiratory inductive plethysmograph (RIP) using a fentanyl-induced respiratory depression model.

METHODS

Eight healthy male volunteers were infused with intravenous (i.v.) fentanyl (15 microg/kg/h) until a decrease in SpO2 below 90% for 1 min emerged. Breathing was continuously and simultaneously measured with SCSB and RIP. Oxygenation, hemodynamics, arterial blood gas analysis, and subjective opioid-related effects were monitored. Fentanyl concentration was measured from an arterial blood sample. The respiratory rate data of the SCSB (automated analysis and manual calculation) were compared with the corresponding RIP data, using analysis of variance for repeated measures. The validity of the SCSB compared with RIP was evaluated using an intra-class correlation coefficient.

RESULTS

Mean fentanyl dose was 629 microg. A statistically significant association was found between the RIP and SCSB data in the manual SCSB analysis (P < 0.0001), but not in the automated SCSB analysis (P = 0.91). After adjusting for the effect of time and the SCSB method, an intra-class correlation coefficient between the manually calculated SCSB values and the RIP values was 0.66.

CONCLUSION

Clinically significant changes in respiratory rate were detected with the SCSB, but the results had to be analyzed manually. The SCSB best suits situations, where comprehensive data are needed. It is not suitable for on-line respiratory monitoring, as the automated analysis did not calculate the respiratory rate correctly.

The PEP transducer: a new way of measuring respiratory rate in the non-intubated patient

OBJECTIVES

To explore the use of a pyroelectric polymer (PEP) film as a transducer for a simple respiratory rate monitor and to evaluate the transducer in a laboratory situation.

METHODS

Laboratory evaluation of a new pyroelectric transducer for measurement of respiratory rate.

RESULTS

The amplified output from the pyroelectric film produced an excellent respiratory trace when used on a normal spontaneously breathing subject. The transducer is cheap, robust, and reliable.

CONCLUSIONS

PEP films have the potential to be used as cheap and effective transducers in respiratory rate monitors for non-intubated patients. In the laboratory, they have many desirable characteristics which should now be evaluated in a clinical setting.

Intrapartum maternal and fetal monitoring: the obstetric intensive care unit

The Obstetric Intensive Care Unit (OBICU) at Bellevue Hospital in New York City has adapted intensive care and coronary care models to the care of patients in labor. During the past 3 years, 519 of the most serious of 2 250 high-risk obstetric patients treated at the hospital were monitored in the OBICU. There were two maternal and six perinatal deaths. The perinatal mortality rate of the very high risk population of the OBICU was 11.6/1 000, compared to 14.7/1 000 for all deliveries performed at the hospital. Our findings indicate that the OBICU system provides the ideal mechanism for the rapid and continuous control of symptoms in very high risk gravidas which is essential for stabilizing the patient, both for prompt delivery and for optimal maternal and fetal survival.