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

Advances in Respiratory Monitoring: A Comprehensive Review of Wearable and Remote Technologies

This article explores the importance of wearable and remote technologies in healthcare. The focus highlights its potential in continuous monitoring, examines the specificity of the issue, and offers a view of proactive healthcare. Our research describes a wide range of device types and scientific methodologies, starting from traditional chest belts to their modern alternatives and cutting-edge bioamplifiers that distinguish breathing from chest impedance variations. We also investigated innovative technologies such as the monitoring of thorax micromovements based on the principles of seismocardiography, ballistocardiography, remote camera recordings, deployment of integrated optical fibers, or extraction of respiration from cardiovascular variables. Our review is extended to include acoustic methods and breath and blood gas analysis, providing a comprehensive overview of different approaches to respiratory monitoring. The topic of monitoring respiration with wearable and remote electronics is currently the center of attention of researchers, which is also reflected by the growing number of publications. In our manuscript, we offer an overview of the most interesting ones.

Rationally designed cellulose hydrogel for an ultrasensitive pressure sensor

Flexible pressure sensors with high sensitivity are required in fields such as human-machine interactions, electronic skin, and health tracking. In this work, we reported cellulose ion-conductive hydrogel (ICH) rationally designed from both nano and micron perspectives for ultrasensitive pressure sensors, via a zero-waste approach, without involving soft components. By introducing low molecular weight cellulose and using the idea of a rough surface, the piezocapacitive sensitivity of the ICH was increased from 0.04 kPa-1 to 89.81 kPa-1 in increments of 2245, which also has a high degree of transparency, excellent durability, and good electrical transmission. Moreover, the ICH demonstrated great potential as sensors and arrays practicable in various industries, including medical treatment and motion recognition. The design is also applicable for piezoresistive tactile sensors, which realize enhanced sensitivity. This affordable, effective, and environmentally friendly technology definitely offers novel perspectives and the potential to enhance the functionality of flexible pressure sensors.

Heart rate and respiratory rate in predicting risk of serious bacterial infection in febrile children given antipyretics: prospective observational study

Clinical algorithms used in the assessment of febrile children in the Paediatric Emergency Departments are commonly based on threshold values for vital signs, which in children with fever are often outside the normal range. Our aim was to assess the diagnostic value of heart and respiratory rate for serious bacterial infection (SBI) in children after temperature lowering following administration of antipyretics. A prospective cohort of children presenting with fever between June 2014 and March 2015 at the Paediatric Emergency Department of a large teaching hospital in London, UK, was performed. Seven hundred forty children aged 1 month-16 years presenting with a fever and ≥ 1 warning signs of SBI given antipyretics were included. Tachycardia or tachypnoea were defined by different threshold values: (a) APLS threshold values, (b) age-specific and temperature-adjusted centiles charts and (c) relative difference in z-score. SBI was defined by a composite reference standard (cultures from a sterile site, microbiology and virology results, radiological abnormalities, expert panel). Persistent tachypnoea after body temperature lowering was an important predictor of SBI (OR 1.92, 95% CI 1.15, 3.30). This effect was only observed for pneumonia but not other SBIs. Threshold values for tachypnoea > 97th centile at repeat measurement achieved high specificity (0.95 (0.93, 0.96)) and positive likelihood ratios (LR + 3.25 (1.73, 6.11)) and may be useful for ruling in SBI, specifically pneumonia. Persistent tachycardia was not an independent predictor of SBI and had limited value as a diagnostic test.  Conclusion: Among children given antipyretics, tachypnoea at repeat measurement had some value in predicting SBI and was useful to rule in pneumonia. The diagnostic value of tachycardia was poor. Overreliance on heart rate as a diagnostic feature following body temperature lowering may not be justified to facilitate safe discharge. What is Known: • Abnormal vital signs at triage have limited value as a diagnostic test to identify children with SBI, and fever alters the specificity of commonly used threshold values for vital signs. • The observed temperature response after antipyretics is not a clinically useful indicator to differentiate the cause of febrile illness. What is New: • Persistent tachycardia following reduction in body temperature was not associated with an increased risk of SBI and of poor value as a diagnostic test, whilst persistent tachypnoea may indicate the presence of pneumonia.

Enhancing System Performance through Objective Feature Scoring of Multiple Persons' Breathing Using Non-Contact RF Approach

Breathing monitoring is an efficient way of human health sensing and predicting numerous diseases. Various contact and non-contact-based methods are discussed in the literature for breathing monitoring. Radio frequency (RF)-based breathing monitoring has recently gained enormous popularity among non-contact methods. This method eliminates privacy concerns and the need for users to carry a device. In addition, such methods can reduce stress on healthcare facilities by providing intelligent digital health technologies. These intelligent digital technologies utilize a machine learning (ML)-based system for classifying breathing abnormalities. Despite advances in ML-based systems, the increasing dimensionality of data poses a significant challenge, as unrelated features can significantly impact the developed system's performance. Optimal feature scoring may appear to be a viable solution to this problem, as it has the potential to improve system performance significantly. Initially, in this study, software-defined radio (SDR) and RF sensing techniques were used to develop a breathing monitoring system. Minute variations in wireless channel state information (CSI) due to breathing movement were used to detect breathing abnormalities in breathing patterns. Furthermore, ML algorithms intelligently classified breathing abnormalities in single and multiple-person scenarios. The results were validated by referencing a wearable sensor. Finally, optimal feature scoring was used to improve the developed system's performance in terms of accuracy, training time, and prediction speed. The results showed that optimal feature scoring can help achieve maximum accuracy of up to 93.8% and 91.7% for single-person and multi-person scenarios, respectively.

Parental Ability to Assess Pediatric Vital Signs

OBJECTIVE

To evaluate parents' ability to accurately assess their child's heart and respiratory rates (RRs) in the context of potential utility for telehealth visits.

STUDY DESIGN

In this controlled study of 203 child-parent pairs, parents measured their child's heart rate (HR) using 4 methods: palpation, auscultation, and 2 photoplethysmographic smartphone applications. Parents measured RR by inspecting the child and tapping the smartphone application. The gold standards were electrocardiogram for the HR and the child's breaths measured by a health care professional for 60 seconds for the RR. We plotted the measurements using a Bland-Altman plot with 95% limits of agreement.

RESULTS

Parents underestimated HR by palpation with a calculated bias of -18 beats per minute (bpm) (SD, 19), with limits of agreement ranging from -56 to 19 bpm. Parents overestimated and underestimated HR by auscultation with limits of agreement ranging from -53 to 46 bpm. Smartphone applications did not improve the accuracy of measurements. The accuracy of parental RR measurements was low. For young children, bias was -0.8 breaths per minute (brpm) (SD, 9.8) with limits of agreement from -20 to 19 brpm, and for older children, bias was 0.9 brpm (SD 7.4) with limits of agreement from 6 to 15 brpm. The sensitivity of parental subjective opinion to recognize accelerated RR was 37% (95% CI, 25%-51%).

CONCLUSION

Parents were not able to assess their child's RR or HR accurately. Digital remote assessment of children should not rely on parental measurements of vital signs.

Lightweight End-to-End Deep Learning Solution for Estimating the Respiration Rate from Photoplethysmogram Signal

Respiratory ailments are a very serious health issue and can be life-threatening, especially for patients with COVID. Respiration rate (RR) is a very important vital health indicator for patients. Any abnormality in this metric indicates a deterioration in health. Hence, continuous monitoring of RR can act as an early indicator. Despite that, RR monitoring equipment is generally provided only to intensive care unit (ICU) patients. Recent studies have established the feasibility of using photoplethysmogram (PPG) signals to estimate RR. This paper proposes a deep-learning-based end-to-end solution for estimating RR directly from the PPG signal. The system was evaluated on two popular public datasets: VORTAL and BIDMC. A lightweight model, ConvMixer, outperformed all of the other deep neural networks. The model provided a root mean squared error (RMSE), mean absolute error (MAE), and correlation coefficient (R) of 1.75 breaths per minute (bpm), 1.27 bpm, and 0.92, respectively, for VORTAL, while these metrics were 1.20 bpm, 0.77 bpm, and 0.92, respectively, for BIDMC. The authors also showed how fine-tuning a small subset could increase the performance of the model in the case of an out-of-distribution dataset. In the fine-tuning experiments, the models produced an average R of 0.81. Hence, this lightweight model can be deployed to mobile devices for real-time monitoring of patients.

A High Accuracy & Ultra-Low Power ECG-Derived Respiration Estimation Processor for Wearable Respiration Monitoring Sensor

The respiratory rate is widely used for evaluating a person's health condition. Compared to other invasive and expensive methods, the ECG-derived respiration estimation is a more comfortable and affordable method to obtain the respiration rate. However, the existing ECG-derived respiration estimation methods suffer from low accuracy or high computational complexity. In this work, a high accuracy and ultra-low power ECG-derived respiration estimation processor has been proposed. Several techniques have been proposed to improve the accuracy and reduce the computational complexity (and thus power consumption), including QRS detection using refractory period refreshing and adaptive threshold EDR estimation. Implemented and fabricated using a 55 nm processing technology, the proposed processor achieves a low EDR estimation error of 0.73 on CEBS database and 1.2 on MIT-BIH Polysomnographic Database while demonstrating a record-low power consumption (354 nW) for the respiration monitoring, outperforming the existing designs. The proposed processor can be integrated in a wearable sensor for ultra-low power and high accuracy respiration monitoring.

Goulart A, Desuó IC, Gomes G. Application of thermography to estimate respiratory rate in the emergency room: The journal Temperature toolbox

Among the vital signs collected during hospital triage, respiratory rate is an important parameter associated with physiological, pathophysiological, and emotional changes. In recent years, the importance of its verification in emergency centers due to the severe acute respiratory syndrome 2 (SARS2) pandemic has become very clear, although it is still one of the least evaluated and collected vital signs. In this context, infrared imaging has been shown to be a reliable estimator of respiratory rate, with the advantage of not requiring physical contact with patients. The objective of this study was to evaluate the potential of analyzing a sequence of thermal images as an estimator of respiratory rate in the clinical routine of an emergency room. We used an infrared thermal camera (T540, Flir Systems) to obtain the respiratory rate data of 136 patients, based on nostrils' temperature fluctuation, during the peak of the COVID-19 pandemic in Brazil and compared it with the chest incursion count method, commonly employed in the emergency screening procedures. We found a good agreement between both methods, with Bland-Altman limits of agreement ranging from -4 to 4 min-1, no proportional bias (R2 = 0.021, p = 0.095), and a strong correlation between them (r = 0.95, p < 0.001). Our results suggest that infrared thermography has potential to be a good estimator of respiratory rate in the routine of an emergency room.

Factors associated with the frequency of respiratory rate measurement by hospital nurses: a multicentre cross-sectional study

BACKGROUND

Although the respiratory rate (RR) is a sensitive predictor of patient deterioration, it is often neglected. Moreover, only a few studies have investigated the factors that cause health professionals to disregard RR.

AIMS

This cross-sectional study aimed to elucidate the factors affecting the frequency of RR measurement by the nurses.

METHODS

An original questionnaire, comprising 18 factors extracted from previous studies, was administered to nurses from nine hospitals.

FINDINGS

Of the 644 eligible nurses, 592 (92%) completed the questionnaire. The adjusted odds ratios and 95% confidence intervals of the factors of importance, educational experiences, shortened-count method use, negative experiences, and inconvenience were 2.24 (1.13-4.45), 2.26 (1.20-4.26), 0.61 (0.42-0.91), 0.45 (0.29-0.70), and 0.41 (0.26-0.65), respectively.

CONCLUSION

Education, feedback systems, and automation are the primary issues that need attention. Prioritising these factors could provide a practical guide for optimising the frequency of RR measurement.

Respiratory rate monitoring in healthy volunteers by central photoplethysmography compared to capnography

Monitoring of respiration is a central task in clinical medicine, crucial to patient safety. Despite the uncontroversial role of altered respiratory frequency as an important sign of impending or manifest deterioration, reliable measurement methods are mostly lacking outside of intensive care units and operating theaters. Photoplethysmography targeting the central blood circulation in the sternum could offer accurate and inexpensive monitoring of respiration. Changes in blood flow related to the different parts of the respiratory cycle are used to identify the respiratory pattern. The aim of this observational study was to compare photoplethysmography at the sternum to standard capnography in healthy volunteers. Bland Altman analysis showed good agreement (bias -0.21, SD 1.6, 95% limits of agreement -3.4 to 2.9) in respiratory rate values. Photoplethysmography provided high-quality measurements of respiratory rate comparable to capnographic measurements. This suggests that photoplethysmography may become a precise, cost-effective alternative for respiratory monitoring.

Usefulness of a mobile phone application for respiratory rate measurement in adult patients

AIMS

Respiratory rate measurement is one of the core nursing skills for early detection of deterioration of a patient's condition. Nevertheless, it is sometimes bothersome to visually measure respiratory rate over 1 min. Respiratory rate measurement using a mobile phone application "RRate" has been reported to be accurate and completed in a short time. However, it has only been investigated in children. The aim of this study was to validate the "RRate" compared with the 1-min method in adult patients.

METHODS

This was a cross-sectional study in the setting of a nursing school. Videos of the movement of the thorax during respiration of adult patients were made. Nursing students watched these videos and measured respiratory rate with each method. Bland-Altman analysis was used to calculate bias and limits of agreement. The times taken for the measurements were compared using a t test.

RESULTS

A total of 59 nursing students participated. When compared to the reference measurement, the one measured using "RRate" and the one measured over 1 min showed a bias of 0.40 breaths per minute and 0.65 breaths per minute, limits of agreement of -2.86 to 3.67 breaths per minute and -2.11 to 3.41 breaths per minute, respectively. The mean measurement time for "RRate" was 22.8 s (95% CI 13.9-36.6), which was significantly shorter than the 65.8 s (95% CI 61.0-73.2) for the measurement over 1 min (p < .001).

CONCLUSIONS

Respiratory rate can be measured accurately in a shorter time using a mobile phone application in adult patients.

A nature-inspired hierarchical branching structure pressure sensor with high sensitivity and wide dynamic range for versatile medical wearables

Pressure-sensing capability is essential for flexible electronic devices, which require high sensitivity and a wide detection range to simplify the system. However, the template-based pressure sensor is powerless to detect high pressure due to the rapid deformation saturation of microstructures. Herein, we demonstrated that a nature-inspired hierarchical branching (HB) structure can effectively address this problem. Finite element analysis demonstrates that the HB structure permits a step-by-step mobilization of microstructure deformation, resulting in a dramatically improved sensitivity (up to 2 orders of magnitude) when compared with the traditional monolayer structure. Experiments show that the HB structure enables pressure sensors to have a lower elastic modulus (1/3 of that of monolayer sensors), a high sensitivity of 13.1 kPa^-1 (almost 14 times higher than the monolayer sensor), and a wide dynamic range (0-800 kPa, the minimum detection pressure is 1.6 Pa). The maximum frequency that the sensor can detect is 250 Hz. The response/recovery time is 0.675/0.55 ms respectively. Given this performance, the HB sensor enables high-resolution detection of the weak radial artery pulse wave characteristics in different states, indicating its potential to noninvasively reveal cardiovascular status and the effectiveness of related interventions, such as exercise and drug intervention. As a proof of concept, we also verified that the HB sensor can serve as a versatile platform to support diverse applications from low to high pressure.

A capaciflector provides continuous and accurate respiratory rate monitoring for patients at rest and during exercise

Respiratory rate (RR) is a marker of critical illness, but during hospital care, RR is often inaccurately measured. The capaciflector is a novel sensor that is small, inexpensive, and flexible, thus it has the potential to provide a single-use, real-time RR monitoring device. We evaluated the accuracy of continuous RR measurements by capaciflector hardware both at rest and during exercise. Continuous RR measurements were made with capaciflectors at four chest locations. In healthy subjects (n = 20), RR was compared with strain gauge chest belt recordings during timed breathing and two different body positions at rest. In patients undertaking routine cardiopulmonary exercise testing (CPET, n = 50), RR was compared with pneumotachometer recordings. Comparative RR measurement bias and limits of agreement were calculated and presented in Bland-Altman plots. The capaciflector was shown to provide continuous RR measurements with a bias less than 1 breath per minute (BPM) across four chest locations. Accuracy and continuity of monitoring were upheld even during vigorous CPET exercise, often with narrower limits of agreement than those reported for comparable technologies. We provide a unique clinical demonstration of the capaciflector as an accurate breathing monitor, which may have the potential to become a simple and affordable medical device.Clinical trial number: NCT03832205 https://clinicaltrials.gov/ct2/show/NCT03832205 registered February 6th, 2019.

Variability of respiratory rate measurements in neonates- every minute counts

Background

Respiratory rate is difficult to measure, especially in neonates who have an irregular breathing pattern. The World Health Organisation recommends a one-minute count, but there is limited data to support this length of observation. We sought to evaluate agreement between the respiratory rate (RR) derived from capnography in neonates, over 15 s, 30 s, 120 s and 300 s, against the recommended 60 s.

Methods

Neonates at two hospitals in Nairobi were recruited and had capnograph waveforms recorded using the Masimo Rad 97. A single high quality 5 min epoch was randomly chosen from each subject. For each selected epoch, the mean RR was calculated using a breath-detection algorithm applied to the waveform. The RR in the first 60 s was compared to the mean RR measured over the first 15 s, 30 s, 120 s, full 300 s, and last 60 s. We calculated bias and limits of agreement for each comparison and used Bland-Altman plots for visual comparisons.

Results

A total of 306 capnographs were analysed from individual subjects. The subjects had a median gestation age of 39 weeks with slightly more females (52.3%) than males (47.7%). The majority of the population were term neonates (70.1%) with 39 (12.8%) having a primary respiratory pathology. There was poor agreement between all the comparisons based on the limits of agreement [confidence interval], ranging between 11.9 [− 6.79 to 6.23] breaths per minute in the one versus 2 min comparison, and 34.7 [− 17.59 to 20.53] breaths per minute in the first versus last minute comparison. Worsening agreement was observed in plots with higher RRs.

Conclusions

Neonates have high variability of RR, even over a short period of time. A slight degradation in the agreement is noted over periods shorter than 1 min. However, this is smaller than observations done 3 min apart in the same subject. Longer periods of observation also reduce agreement. For device developers, precise synchronization is needed when comparing devices to reduce the impact of RR variation. For clinicians, where possible, continuous or repeated monitoring of neonates would be preferable to one time RR measurements.

Agreement between respiratory rate measurement using a combined electrocardiographic derived method versus impedance from pneumography

BACKGROUND

Impedance pneumography (IP) is the current device-driven method used to measure respiratory rate (RR) in hospitalized patients. However, RR alarms are common and contribute to alarm fatigue. While RR derived from electrocardiographic (ECG) waveforms hold promise, they have not been compared to the IP method.

PURPOSE

Study examined the agreement between the IP and combined-ECG derived (EDR) for normal RR (≥12 or ≤20 breaths/minute [bpm]); low RR (≤5 bpm); and high RR (≥30 bpm).

METHODOLOGY

One-hundred intensive care unit patients were included by RR group: (1) normal RR (n = 50; 25 low RR and 25 high RR); (2) low RR (n = 50); and (3) high RR (n = 50). Bland-Altman analysis was used to evaluate agreement.

RESULTS

For normal RR, a significant bias difference of -1.00 + 2.11 (95% CI -1.60 to -0.40) and 95% limit of agreement (LOA) of -5.13 to 3.13 was found. For low RR, a significant bias difference of -16.54 + 6.02 (95% CI: -18.25 to -14.83) and a 95% LOA of -28.33 to - 4.75 was found. For high RR, a significant bias difference of 17.94 + 12.01 (95% CI: 14.53 to 21.35) and 95% LOA of -5.60 to 41.48 was found.

CONCLUSION

Combined-EDR method had good agreement with the IP method for normal RR. However, for the low RR, combined-EDR was consistently higher than the IP method and almost always lower for the high RR, which could reduce the number of RR alarms. However, replication in a larger sample including confirmation with visual assessment is warranted.

Pulse oximetry and supplemental oxygen use in nationwide Veterans Health Administration hospitals, 2013-2017: a Veterans Affairs Patient Database validation study

OBJECTIVE

Extraction and standardisation of pulse oximetry and supplemental oxygen data from electronic health records has the potential to improve risk-adjustment, quality assessment and prognostication. We develop an approach to standardisation and report on its use for benchmarking purposes.

MATERIALS AND METHODS

Using electronic health record data from the nationwide Veteran's Affairs healthcare system (2013-2017), we extracted, standardised and validated pulse oximetry and supplemental oxygen data for 2 765 446 hospitalisations in the Veteran's Affairs Patient Database (VAPD) cohort study. We assessed face, concurrent and predictive validities using the following approaches, respectively: (1) evaluating the stability of patients' pulse oximetry values during a 24-hour period, (2) testing for greater amounts of supplemental oxygen use in patients likely to need oxygen therapy and (3) examining the association between supplemental oxygen and subsequent mortality.

RESULTS

We found that 2 700 922 (98%) hospitalisations had at least one pulse oximetry reading, and 864 605 (31%) hospitalisations received oxygen therapy. Patients monitored by pulse oximetry had a reading on average every 6 hours (median 4; IQR 3-7). Patients on supplemental oxygen were older, white and male compared with patients not receiving oxygen therapy (p<0.001) and were more likely to have diagnoses of heart failure and chronic pulmonary diseases (p<0.001). The amount of supplemental oxygen for patients with at least three consecutive values recorded during a 24-hour period fluctuated by median 2 L/min (IQR: 2-3), and 81% of such triplets showed the same level of oxygen receipt.

CONCLUSION

Our approach to standardising pulse oximetry and supplemental oxygen data shows face, concurrent and predictive validities as the following: supplemental oxygen clusters in the range consistent with hospital wall-dispensed oxygen supplies (face validity); there are greater amounts of supplemental oxygen for certain clinical conditions (concurrent validity) and there is an association of supplemental oxygen with in-hospital and postdischarge mortality (predictive validity).

Development and Performance Evaluation of Wearable Respiratory Self-Training System Using Patch Type Magnetic Sensor

Purpose

Respiratory training system that can be used by patients themselves was developed with a micro-electro-mechanical-system (MEMS)-based patch-type magnetic sensor. We conducted a basic function test and clinical usability evaluation to determine the system’s clinical applicability.

Methods

The system is designed with a sensor attached to the patient’s chest and a magnet on the back to monitor the patient’s respiration by measuring changes in magnetic intensity related to respiratory movements of the thoracic surface. The system comprises a MEMS-based patch-type magnetic sensor capable of wireless communication and being applied to measurement magnets and mobile applications. System performance was evaluated by the level of systemic noise, the precision of the sensor in various breathing patterns, how measurement signals change for varying distances, or the presence or absence of material between the sensor and the magnet. Various breathing patterns were created using the QUASAR respiratory motion phantom; the data obtained were analyzed using the fitting and peak value analysis methods.

Results

The sensor had a noise ratio of <0.54% of the signal; the average errors in signal amplitude and period for breathing patterns were 78.87 um and 72 ms, respectively. The signal could be measured consistently when the sensor–magnet distance was 10–25 cm. The signal difference was 1.89% for the presence or absence of a material, indicating that its influence on the measurement signal is relatively small.

Conclusion

The potential of our MEMS-based patch-type wearable respiratory self-training system was confirmed via basic function tests and clinical usability evaluations. We believe that the training system could provide thorough respiratory training for patients after a clinical trial with actual patients confirming its clinical efficacy and usability.

A review of the literature on the accuracy, strengths, and limitations of visual, thoracic impedance, and electrocardiographic methods used to measure respiratory rate in hospitalized patients

Background

Respiratory rate (RR) is one of the most important indicators of a patient's health. In critically ill patients, unrecognized changes in RR are associated with poorer outcomes. Visual assessment (VA), impedance pneumography (IP), and electrocardiographic‐derived respiration (EDR) are the three most commonly used methods to assess RR. While VA and IP are widely used in hospitals, the EDR method has not been validated for use in hospitalized patients. Additionally, little is known about their accuracy compared with one another. The purpose of this systematic review was to compare the accuracy, strengths, and limitations of VA of RR to two methods that use physiologic data, namely IP and EDR.

Methods

A systematic review of the literature was undertaken using prespecified inclusion and exclusion criteria. Each of the studies was evaluated using standardized criteria.

Results

Full manuscripts for 23 studies were reviewed, and four studies were included in this review. Three studies compared VA to IP and one study compared VA to EDR. In terms of accuracy, when Bland–Altman analyses were performed, the upper and lower levels of agreement were extremely poor for both the VA and IP and VA and EDR comparisons.

Conclusion

Given the paucity of research and the fact that no studies have compared all three methods, no definitive conclusions can be drawn about the accuracy of these three methods. The clinical importance of accurate assessment of RR warrants new research with rigorous designs to determine the accuracy, and clinically meaningful levels of agreement of these methods.

Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications

Respiratory monitoring is receiving growing interest in different fields of use, ranging from healthcare to occupational settings. Only recently, non-contact measuring systems have been developed to measure the respiratory rate (fR) over time, even in unconstrained environments. Promising methods rely on the analysis of video-frames features recorded from cameras. In this work, a low-cost and unobtrusive measuring system for respiratory pattern monitoring based on the analysis of RGB images recorded from a consumer-grade camera is proposed. The system allows (i) the automatized tracking of the chest movements caused by breathing, (ii) the extraction of the breathing signal from images with methods based on optical flow (FO) and RGB analysis, (iii) the elimination of breathing-unrelated events from the signal, (iv) the identification of possible apneas and, (v) the calculation of fR value every second. Unlike most of the work in the literature, the performances of the system have been tested in an unstructured environment considering user-camera distance and user posture as influencing factors. A total of 24 healthy volunteers were enrolled for the validation tests. Better performances were obtained when the users were in sitting position. FO method outperforms in all conditions. In the fR range 6 to 60 breaths/min (bpm), the FO allows measuring fR values with bias of −0.03 ± 1.38 bpm and −0.02 ± 1.92 bpm when compared to a reference wearable system with the user at 2 and 0.5 m from the camera, respectively.

Flexible, Highly Sensitive Paper-Based Screen Printed MWCNT/PDMS Composite Breath Sensor for Human Respiration Monitoring

Accurate measurement and monitoring of respiration is vital in patients affected by severe acute respiratory syndrome coronavirus - 2 (SARS-CoV-2). Patients with severe chronic diseases and pneumonia need continuous respiration monitoring and oxygenation support. Existing respiratory sensing techniques require direct contact with the human body along with expensive and heavy Holter monitors for continuous real-time monitoring. In this work, we propose a low-cost, non-invasive and reliable paper-based wearable screen printed sensor for human respiration monitoring as an effective alternative of existing sensing systems. The proposed sensor was fabricated using traditional screen printing of multi-walled carbon nanotubes (MWCNTs) and polydimethylsiloxane (PDMS) composite based interdigitated electrodes on paper substrate. The paper substrate was used as humidity sensing material of the sensor. The hygroscopic nature of paper during inhalation and exhalation causes a change in dielectric constant, which in turn changes the capacitance of the sensor. The composite interdigitated electrode configuration exhibited better response times with a rise time of 1.178s being recorded during exhalation and fall time of 0.88s during inhalation periods. The respiration rate of sensor was successfully examined under various breathing conditions such as normal breathing, deep breathing, workout, oral breathing, nasal breathing, fast breathing and slow breathing by employing it in a wearable mask, a mandatory wearable product during the current COVID-19 pandemic situation.Thus, the above proposed sensor may hold tremendous potential in wearable/flexible healthcare technology with good sensitivity, stability, biodegradability and flexibility at this time of need.

Accuracy of shorter respiratory rate measurement times in the pediatric population

BACKGROUND

As one of the vital signs, the respiratory rate is an important index of general health in an initial examination. The duration of respiratory rate measurements is known to influence the results in adults. We examined the difference in respiratory rate measurements between two measurement durations in a pediatric population.

METHODS

The prospective, cross-sectional study was conducted from November 2017 through March 2018 at Tokyo Metropolitan Children's Medical Center and analyzed differences in the respiratory rate in a 1 min group and 30 s group using the Bland-Altman plot.

RESULTS

Ninety-five patients were enrolled. The median age was 0.99 years, and 50 patients were male. The correlation between the results of the 30 s and 1 min measurement durations was good (r²  = 0.970, P < 0.001; Spearman's rank correlation). The mean difference between the 30 s and 1 min measurement results was 0.86 (95% confidence interval: 0.27-1.45).

CONCLUSIONS

The shorter measurement duration may result in overestimation of the respiratory rate, especially in young children or children with tachypnea. Nonetheless, the shorter measurement times correlated well with the 1 min measurement, and the difference was less than one per minute compared with the 1 min measurement. Thus, this method may be able to detect life-threatening conditions earlier than longer measurement times.

Estimation of Respiratory Rate from Thermography Using Respiratory Likelihood Index

Respiration is a key vital sign used to monitor human health status. Monitoring respiratory rate (RR) under non-contact is particularly important for providing appropriate pre-hospital care in emergencies. We propose an RR estimation system using thermal imaging cameras, which are increasingly being used in the medical field, such as recently during the COVID-19 pandemic. By measuring temperature changes during exhalation and inhalation, we aim to track the respiration of the subject in a supine or seated position in real-time without any physical contact. The proposed method automatically selects the respiration-related regions from the detected facial regions and estimates the respiration rate. Most existing methods rely on signals from nostrils and require close-up or high-resolution images, while our method only requires the facial region to be captured. Facial region is detected using YOLO v3, an object detection model based on deep learning. The detected facial region is divided into subregions. By calculating the respiratory likelihood of each segmented region using the newly proposed index, called the Respiratory Quality Index, the respiratory region is automatically selected and the RR is estimated. An evaluation of the proposed RR estimation method was conducted on seven subjects in their early twenties, with four 15 s measurements being taken. The results showed a mean absolute error of 0.66 bpm. The proposed method can be useful as an RR estimation method.

Accuracy of pre-hospital triage tools for major trauma: a systematic review with meta-analysis and net clinical benefit

BACKGROUND

We conducted a systematic review to evaluate and compare the accuracy of pre-hospital triage tools for major trauma in the context of the development of the Italian National Institute of Health guidelines on major trauma integrated management.

METHODS

PubMed, Embase, and CENTRAL were searched up to November 2019 for studies investigating pre-hospital triage tools. The ROC (receiver operating characteristics) curve and net clinical benefit for all selected triage tools were performed. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies-2. Certainty of the evidence was judged with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

RESULTS

We found 15 observational studies of 13 triage tools for adults and 11 for children. In adults, according to the ROC curve and the net clinical benefit, the most reliable tool was the Northern French Alps Trauma System (TRENAU), adopting injury severity score (ISS) > 15 as reference (sensitivity (Sn), 0.92; specificity (Sp), 0.41; 1 study; sample size, 2572; high certainty of the evidence). When mortality as reference was considered, the pre-hospital triage tool with the best net clinical benefit trajectory was the New Trauma Score (NTS) < 18 (Sn, 0.82; Sp, 0.86; 1 study; sample size, 1001; moderate certainty of the evidence). In children, high variability among all triage tools for sensitivity and specificity was found.

CONCLUSION

Sensitivity and specificity varied across all available pre-hospital trauma triage tools. TRENAU and NTS are the best accurate triage tools for adults, whereas in the pediatric area a large variability prevents any firm conclusion.

Compressible and Stretchable Magnetoelectric Sensors Based on Liquid Metals for Highly Sensitive, Self-Powered Respiratory Monitoring

Healthcare monitoring, especially for respiration, has attracted tremendous attention from academics considering the great significance of health information feedback. The respiratory rate, as a critical health indicator, has been used to screen and evaluate potential illness risks in early medical diagnoses. A self-powered sensing system for medical monitoring is critical and imperative due to needless battery replacement and simple assembly. However, the development of a self-powered respiratory sensor with highly sensitive performance is still a daunting challenge. In this work, a compressible and stretchable magnetoelectric sensor (CSMS) with an arch-shaped air gap is reported, enabling self-powered respiratory monitoring driven by exhaled/inhaled breath. The CSMS contains two key functional materials: liquid metals and magnetic powders both with low Young's modulus, allowing for sensing compressibility and stretchability simultaneously. More importantly, such a magnetoelectric sensor exhibits mechanoelectrical converting capacity under an external force, which has been verified by Maxwell numerical simulation. Owing to the air-layer introduction, the magnetoelectric sensors achieve high sensitivity (up to 17.73 kPa^-1), fast response, and long-term stability. The highly sensitive and self-powered magnetoelectric sensor can be further applied as a noninvasive, miniaturized, and portable respiratory monitoring system with the aim of warning for potential health risks. We anticipate that this technique will create an avenue for self-powered respiratory monitoring fields.

Feasibility of using a biofeedback device in mindfulness training - a pilot randomized controlled trial

Background

Stress can negatively impact an individual’s health and well-being and high levels of stress are noted to exist among college students today. While traditional treatment methods are plagued with stigma and transfer problems, newly developed wearable biofeedback devices may offer unexplored possibilities. Although these products are becoming commonplace and inexpensive, scientific evidence of the effectiveness of these products is scarce and their feasibility within research contexts are relatively unexplored. Conversely, companies are not required, and possibly reluctant, to release information on the efficacy of these products against their claims. Thus, in the present pilot, we assess the feasibility of using a real-time respiratory-based biofeedback device in preparation for a larger study. Our main aims were to assess device-adherence and collaboration with the company that develops and sells the device.

Method

Data were collected from 39 college students who self-identified as experiencing chronic stress at a Southwestern university in the USA. Students were randomized into either a mindfulness-only control group without a biofeedback device (n = 21), or an experimental group with biofeedback device (n = 18). Both groups received mindfulness meditation training. Pre-test and post-test procedures were conducted 2 weeks apart. Further, both participant compliance and company compliance were assessed and collaboration with the company was evaluated.

Results

Participant device-adherence as well as the company’s collaboration necessary for a full-scale study was determined to be low. This may also have affected our results which showed a strong main effect for time for all outcome variables, suggesting all groups showed improvement in their levels of stress after the intervention period. No group by time effects were identified, however, indicating no added benefit of the biofeedback device.

Conclusions

Our findings suggest feasibility of future studies requires full collaboration and detailed and agreed upon data sharing procedures with the biofeedback company. The particular device under investigation added no value to the intervention outcomes and it was not feasible to continue a larger-scale study. Further, as the technology sector is innovating faster than it can validate products, we urge for open science collaborations between public and private sectors to properly develop evidence-based regulations that can withstand technological innovation while maintaining product quality, safety, and effectiveness.

Trial registration

NCT02837016. Registered 19 July 2016.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40814-021-00807-1.

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.

[Postoperative remote monitoring]

During the course of surgical interventions, complications mostly occur in the postoperative period. Slight clinical indications can be observed, which precede a significant deterioration of the patient's condition. On the general ward vital parameters, such as heart and breathing frequencies are measured every 4-8 h. Even if the monitoring of critically ill patients is increased to every 2 h and the measurement of vital functions takes 10 min, the patient is only monitored for 120 min in a 24 h period and remains postoperatively on the general ward without monitoring for 22 out of 24 h. New wireless monitoring systems are available to continuously register some vital functions with the aid of wearable sensors. These systems can alert and alarm ward personnel if the patient's condition deteriorates. Although the optimal monitoring system does not yet exist and implementation of these new wireless monitoring systems might involve some risks, these new methods offer a great opportunity to optimize surveillance of postoperative patients on the general ward.

Quantitative systematic review: Sources of inaccuracy in manually measured adult respiratory rate data

AIMS

To identify the potential sources of inaccuracy in manually measured adult respiratory rate (RR) data and quantify their effects.

DESIGN

Quantitative systematic review with meta-analyses where appropriate.

DATA SOURCES

Medline, CINAHL, and Cochrane Library (from database inception to 31 July 2019).

REVIEW METHODS

Studies presenting data on individual sources of inaccuracy in the manual measurement of adult RR were analysed, assessed for quality, and grouped according to the source of inaccuracy investigated. Quantitative data were extracted and synthesized and meta-analyses performed where appropriate.

RESULTS

Included studies (N = 49) identified five sources of inaccuracy. The awareness effect creates an artefactual reduction in actual RR, and observation methods involving shorter counts cause systematic underscoring. Individual RR measurements can differ substantially in either direction between observations due to inter- or intra-observer variability. Value bias, where particular RRs are over-represented (suggesting estimation), is a widespread problem. Recording omission is also widespread, with higher average rates in inpatient versus triage/admission contexts.

CONCLUSION

This review demonstrates that manually measured RR data are subject to several potential sources of inaccuracy.

IMPACT

RR is an important indicator of clinical deterioration and commonly included in track-and-trigger systems. However, the usefulness of RR data depends on the accuracy of the observations and documentation, which are subject to five potential sources of inaccuracy identified in this review. A single measurement may be affected by several factors. Hence, clinicians should interpret recorded RR data cautiously unless systems are in place to ensure its accuracy. For nurses, this includes counting rather than estimating RRs, employing 60-s counts whenever possible, ensuring patients are unaware that their RR is being measured, and documenting the resulting value. For any given site, interventions to improve measurement should take into account the local organizational and cultural context, available resources, and the specific measurement issues that need to be addressed.

Binary Spiky/Spherical Nanoparticle Films with Hierarchical Micro/Nanostructures for High-Performance Flexible Pressure Sensors

Flexible pressure sensors have been widely explored for their versatile applications in electronic skins, wearable healthcare monitoring devices, and robotics. However, fabrication of sensors with characteristics such as high sensitivity, linearity, and simple fabrication process remains a challenge. Therefore, we propose herein a highly flexible and sensitive pressure sensor based on a conductive binary spiky/spherical nanoparticle film that can be fabricated by a simple spray-coating method. The sea-urchin-shaped spiky nanoparticles are based on the core-shell structures of spherical silica nanoparticles decorated with conductive polyaniline spiky shells. The simple spray coating of binary spiky/spherical nanoparticles enables the formation of uniform conductive nanoparticle-based films with hierarchical nano/microstructures. The two differently shaped particles-based films (namely sea-urchin-shaped and spherical) when interlocked face-to-face to form a bilayer structure can be used as a highly sensitive piezoresistive pressure sensor. Our optimized pressure sensor exhibits high sensitivity (17.5 kPa^-1) and linear responsivity over a wide pressure range (0.008-120 kPa), owing to the effects of stress concentration and gradual deformation of the hierarchical microporous structures with sharp nanoscale tips. Moreover, the sensor exhibits high durability over 6000 repeated cycles and practical applicability in wearable devices that can be used for healthcare monitoring and subtle airflow detection (1 L/min).

Calibration and validation of the pediatric resuscitation and trauma outcome model among injured children in Rwanda

BACKGROUND

Trauma is a leading cause of mortality in low- and middle-income countries. The Pediatric Resuscitation and Trauma Outcomes (PRESTO) model uses six low-tech variables available at point of care in resource-limited environments to predict in-hospital mortality of injured children. This model was never calibrated and validated in a low-income country. We aimed to calibrate the model's coefficients and compare its performance against the Revised Trauma Score (RTS) and Kampala Trauma Score (KTS) using data from a low-income country.

STUDY DESIGN

Data from 2011 to 2015 in the prospectively-maintained Rwanda Injury Registry were reviewed after ethical approval was obtained. Patients were included for analysis if they were referred or admitted for traumatic injury, were younger than 15 years and if hospital outcomes were recorded. The variables in the PRESTO model include age, hypotension, heart rate, neurological status, oxygen saturation and airway intervention. The outcome of interest was in-hospital death. After calibration, Receiver-Operating-Characteristic curves were constructed to compare the area-under-curve (AUC) of PRESTO, RTS, and KTS with imputation of missing data. Comparisons of the relative AUC's were performed using Delong's test after bootstrapping in the full cohort and in a subset of patients <5 years-old.

RESULTS

There were 113 in-hospital deaths out of 1695 included patients (6.7%). The AUC for the PRESTO model was 0.90 (95% CI [0.82-0.91]), higher than for RTS (0.77, 95% CI [0.80-0.97], p < 0.01) but not statistically different from KTS (0.89, 95% CI [0.72-0.82], p = 0.856). In the under-five cohort, the PRESTO model AUC was 0.84 (95% CI [0.75-0.92]), significantly higher than RTS (0.73 95% CI [0.64-0.81], p < 0.01) and KTS (0.58, 95% CI [0.50-0.66], p < 0.01).

CONCLUSION

PRESTO appears to be the superior benchmarking tool for pediatric patients in a low- and middle-income country context. The PRESTO score outperforms the KTS in children <5 years of age. Further validation of the PRESTO model is needed from other low- and middle-income settings.

LEVEL OF EVIDENCE

Level III: case-control (prognostic) study.

Implementation of the National Early Warning Score in UK care homes: a qualitative evaluation

BACKGROUND

The National Early Warning Score (NEWS) is a tool for identifying and responding to acute illness. When used in care homes, staff measure residents' vital signs and record them on a tablet computer, which calculates a NEWS to share with health services. This article outlines an evaluation of NEWS implementation in care homes across one clinical commissioning group area in northern England.

AIM

To identify challenges to implementation of NEWS in care homes.

DESIGN AND SETTING

Qualitative analysis of interviews conducted with 15 staff members from six care homes, five health professionals, and one clinical commissioning group employee.

METHOD

Interviews were intended to capture people's attitudes and experiences of using the intervention. Following an inductive thematic analysis, data were considered deductively against normalisation process theory constructs to identify the challenges and successes of implementing NEWS in care homes.

RESULTS

Care home staff and other stakeholders acknowledged that NEWS could enhance the response to acute illness, improve communication with the NHS, and increase the confidence of care home staff. However, the implementation did not account for the complexity of either the intervention or the care home setting. Challenges to engagement included competing priorities, insufficient training, and shortcomings in communication.

CONCLUSION

This evaluation highlights the need to involve care home staff and the primary care services that support them when developing and implementing interventions in care homes. The appropriateness and value of NEWS in non-acute settings requires ongoing monitoring.

Contrasting characters of quick methods to measure respiratory rate in a clinical setting

INTRODUCTION

Many medical professionals unofficially use quick methods for saving time. However, the evidence of such assessments is limited. The main aim of this article is verifying the agreement of these methods.

OBJECTIVES

Overall, 106 out-patients were simultaneously evaluated with respect to the respiratory time measurement (RTM; 60 divided by the single respiratory time), 15 seconds period quadruple respiratory rate (15secRR; 15 seconds respiratory rate multiplied by 4), and 1-min respiratory rate (1minRR; gold standard respiratory rate).

METHOD

We assessed the correlation, Bland-Altman plot, kappa value, and normalized root mean square error of the quick methods for the respiratory rate, with 1minRR as the gold standard.

RESULTS

The mean ± SD of 1minRR, RTM, and 15secRR are 20.4 ± 5.6, 19.1 ± 5.7, and 21.4 ± 6.5 breathes per minute, respectively. The correlation between RTM and 1minRR was 0.85 (95% confidence interval [95% CI]: 0.79-0.90), while that between 15secRR and 1minRR was 0.81 (95% CI: 0.74-0.87). The kappa coefficients between RTM and 1minRR, between 15secRR and 1minRR, and between RTM and 15secRR were 0.57 (95% CI: 0.41-0.72), 0.59 (95% CI: 0.43-0.74), and 0.37 (95% CI: 0.20-0.53), respectively. The normalized root mean square error between RTM and 1minRR was 16.9% and that between 15secRR and 1minRR was 15.0%. The Bland Altman plot demonstrated that RTM and 15secRR showed contrasting characteristics.

CONCLUSION

Compared to the gold standard, RTM tends to underestimate, while 15secRR tends to overestimate the respiratory rate. Therefore, health care professionals should be aware of this methodological tendency to assess vital signs properly.

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.

Respiratory rate on exercise measured by nanoparticle-based humidity sensor

In this study, we show the measurement of respiratory rate on exercise using a nanoparticle-based humidity sensor. A portable respiratory rate sensor is comprised of a colloidal silica nanoparticle-based humidity sensor chip. The impedance of the silica nanoparticle film is dependent on humidity and it is used for the detection of humid exhaled air. The respiratory rate sensor can be attached on an oxygen mask and the sensor signal is remotely monitored via Bluetooth. We show that the sensor follows a respiratory rate up to 60 bpm. We compare the sensor signal with that of a conventional respiratory measurement unit, which monitors a respiratory volume. The nanoparticle-based sensor can monitor a respiratory rate of an exercising person on a treadmill. The sensor operates stably for almost one year.

Clinical evaluation of stretchable and wearable inkjet-printed strain gauge sensor for respiratory rate monitoring at different measurements locations

The respiration rate (RR) is a vital sign in physiological measurement and clinical diagnosis. RR can be measured using stretchable and wearable strain gauge sensors which detect the respiratory movements in the abdomen or thorax areas caused by volumetric changes. In different body locations, the accuracy of RR detection might differ due to different respiratory movement amplitudes. Few studies have quantitatively investigated the effect of the measurement location on the accuracy of new sensors in RR detection. Using a stretchable and wearable inkjet-printed strain gauge (IPSG) sensor, RR was measured from five body locations (umbilicus, upper abdomen, xiphoid process, upper thorax, and diagonal) on 30 healthy test subjects while sitting on an armless chair. At each location, reference RR was simultaneously detected by the e-Health sensor, and the measurement was repeated twice. Subjects were asked about the comfortableness of locations. Based on Levene's test, ANOVA was performed to investigate if there is a significant difference in RR between sensors, measurement locations, and two repeated measurements. Bland-Altman analysis was applied to the RR measurements at different locations. The effects of measurement site and measurement trials on RR difference between sensors were also investigated. There was no significant difference between IPSG and reference sensors, between any locations, and between the two measurements (all p > 0.05). As to the RR deviation between IPSG and reference sensors, there was no significant difference between any locations, or between two measurements (all p > 0.05). All the 30 subjects agreed that diagonal and upper thorax positions were the most uncomfortable and most comfortable locations for measurement, respectively. The IPSG sensor could accurately detect RR at five different locations with good repeatability. Upper thorax was the most comfortable location.

Investigation of an Ultra Wideband Noise Sensor for Health Monitoring

Quick on-scene assessment and early intervention is the key to reduce the mortality of stroke and trauma patients, and it is highly desirable to develop ambulance-based diagnostic and monitoring devices in order to provide additional support to the medical personnel. We developed a compact and low cost ultra wideband noise sensor for medical diagnostics and vital sign monitoring in pre-hospital settings. In this work, we demonstrated the functionality of the sensor for respiration and heartbeat monitoring. In the test, metronome was used to manipulate the breathing pattern and the heartbeat rate reference was obtained with a commercial electrocardiogram (ECG) device. With seventeen tests performed for respiration rate detection, sixteen of them were successfully detected. The results also show that it is possible to detect the heartbeat rate accurately with the developed sensor.

Measuring vital signs in children with fever at the emergency department: an observational study on adherence to the NICE recommendations in Europe

Vital signs can help clinicians identify children at risk of serious illness. The NICE guideline for fever in under-fives recommends a routine measurement of temperature, heart rate, capillary refill and respiratory rate in all febrile children visiting the emergency department (ED). This study aims to evaluate the measurement of paediatric vital signs in European EDs, with specific attention to adherence to this NICE guideline recommendation. In a prospective observational study, we included 4560 febrile children under 16 years from the ED of 28 hospitals in 11 European countries (2014-2016). Hospitals were academic (n = 17), teaching (n = 10) and non-teaching (n = 1) and ranged in annual paediatric ED visits from 2700 to 88,000. Fifty-four percent were male, their median age was 2.4 years (IQR 1.1-4.7). Temperature was measured most frequently (97%), followed by capillary refill (86%), heart rate (73%), saturation (56%) and respiratory rate (51%). In children under five (n = 3505), a complete measurement of the four NICE-recommended vital signs was performed in 48% of patients. Children under 1 year of age, those with an urgent triage level and with respiratory infections had a higher likelihood of undergoing complete measurements. After adjustment for these factors, variability between countries remained. Conclusion: Measuring vital signs in children with fever in the ED occurs with a high degree of practice variation between different European hospitals, and adherence to the NICE recommendation is moderate. Our study is essential as a benchmark for current clinical practice, in order to tailor implementation strategies to different European settings.What is Known:• Vital signs can quickly provide information on disease severity in children in the emergency department (ED), and the NICE guideline for fever in under-fives recommends to routinely measure temperature, heart rate, capillary refill and respiratory rate.• Data regarding measurement of vital signs in routine practice across European EDs is currently unavailable.What is New:• Measurement of vital signs in febrile children is highly variable across European EDs and across patient subgroups, and compliance to the NICE recommendation is <50%.• Children under 1 year of age, those with an urgent triage level and with respiratory infections had a higher likelihood of undergoing complete measurements.

Anodized Aluminum Oxide-Assisted Low-Cost Flexible Capacitive Pressure Sensors Based on Double-Sided Nanopillars by a Facile Fabrication Method

Flexible pressure sensors have garnered enormous attention in recent years as they hold great promise in wearable electronic devices. However, the realization of a high-performance flexible pressure sensor via a facile and cost-effective approach still remains a challenge. In this work, a capacitive pressure sensor based on a poly(vinylidenefluoride-co-trifluoroethylene) [P(VDF-TrFE)] dielectric film that incorporates nanopillars into both sides is demonstrated. Unlike the previous complicated and expensive methods, large-scale regular and uniform nanopillars are easily and economically achieved by the pattern transfer of anodized aluminum oxide templates. The double-sided nanopillars constituting the P(VDF-TrFE) dielectric layer enable the pressure sensor with high sensitivity (∼0.35 kPa^-1), wide working range (4 Pa to 25 kPa), short response time (∼48 ms), and excellent durability. In addition to these salient features, our sensor also exhibits superior performances under bending states, ensuring that it can be used for detecting diverse practical stimuli as experimentally validated by perceiving real-time and in-site human physiological signals and body motions that, respectively, correspond to the low- and high-pressure range. A sensor array is finally constructed and is shown to be capable of perceiving the spatial pressure distribution of either a contact or noncontact object. These demonstrations show a promising future of our sensor in healthcare monitoring, smart robot skin, and human-machine interfaces.

Pulse transit time based respiratory rate estimation with singular spectrum analysis

Respiratory rate (RR) is an important vital sign which can be difficult to measure accurately and unobtrusively in routine clinical practice. Pulse transit time (PTT), on the other hand, is unobtrusive to collect from electrocardiogram (ECG) and photoplethysmogram (PPG) signals. Using PTT is a novel method to estimate and monitor blood pressure (BP) and RR. This study aimed to estimate continuous RR using PTT with singular spectrum analysis to extract respiratory components. The performance of this method was validated on 17 subjects who carried out spontaneous breathing and controlled deep breathing conditions. Three types of estimated RR parameters (average RR by power spectral density (PSD) (RR_PSD), number of breaths (RR_#), and instantaneous RR (RR_inst)) were compared with the corresponding reference RR. The reference RR was collected using a respiratory belt. Our findings demonstrate that the PTT signal reliably tracked respiratory variation with a root mean square error of 0.84, 1.11, and 0.74 breaths/min for RR_PSD, RR_#, and RR_inst estimations, respectively. Overall, RR estimated by PTT was more accurate than heart/pulse rate interval, QRS area, and PPG amplitude, which were also extracted from ECG and PPG. The results suggest that it may be feasible to use PTT as an estimation of RR and that ECG and PPG may be relied upon for monitoring not only RR but also BP and heart rate. Graphical abstract The Pulse Transit Time (PTT) based Respiratory Rate (RR) estimation with Singular Spectrum Analysis (SSA) provides a superior performance than the method with other respiratory indicators extracted from Electrocardiogram (ECG) or Photoplethysmogram (PPG).

Estimation of respiratory rate using infrared video in an inpatient population: an observational study

Respiratory rate (RR) is one of the most sensitive markers of a deteriorating patient. Despite this, there is significant inter-observer discrepancy when measured by clinical staff, and modalities used in clinical practice such as ECG bioimpedance are prone to error. This study utilized infrared thermography (IRT) to measure RR in a critically ill population in the Intensive Care Unit. This study was carried out in a Single Hospital Centre. Respiratory rate in 27 extubated ICU patients was counted by two observers and compared to ECG Bioimpedance and IRT-derived RR at distances of 0.4-0.6 m and > 1 m respectively. IRT-derived RR using two separate computer vision algorithms outperformed ECG derived RR at distances of 0.4-0.6 m. Using an Autocorrelation estimator, mean bias was - 0.667 breaths/min. Using a Fast Fourier Transform estimator, mean bias was - 1.000 breaths/min. At distances greater than 1 m no statistically significant signal could be obtained. Over all frequencies, there was a significant relationship between the RR estimated using IRT and via manual counting, with Pearson correlation coefficients between 0.796 and 0.943 (p < 0.001). Correlation between counting and ECG-derived RR demonstrated significance only at > 19 bpm (r = 0.562, p = 0.029). Overall agreement between IRT-derived RR at distances of 0.4-0.6 m and gold standard counting was satisfactory, and outperformed ECG derived bioimpedance. Contactless IRT derived RR may be feasible as a routine monitoring modality in wards and subacute inpatient settings.

Insights into postoperative respiration by using continuous wireless monitoring of respiratory rate on the postoperative ward: a cohort study

Change of respiratory rate (RespR) is the most powerful predictor of clinical deterioration. Brady- (RespR ≤ 8) and tachypnea (RespR ≥ 31) are associated with serious adverse events. Simultaneously, RespR is the least accurately measured vital parameter. We investigated the feasibility of continuously measuring RespR on the ward using wireless monitoring equipment, without impeding mobilization. Continuous monitoring of vital parameters using a wireless SensiumVitals® patch was installed and RespR was measured every 2 mins. We defined feasibility of adequate RespR monitoring if the system reports valid RespR measurements in at least 50% of time-points in more than 80% of patients during day- and night-time, respectively. Data from 119 patients were analysed. The patch detected in 171,151 of 227,587 measurements valid data for RespR (75.2%). During postoperative day and night four, the system still registered 68% and 78% valid measurements, respectively. 88% of the patients had more than 67% of valid RespR measurements. The RespR’s most frequently measured were 13–15; median RespR was 15 (mean 16, 25th- and 75th percentile 13 and 19). No serious complications or side effects were observed. We successfully measured electronically RespR on a surgical ward in postoperative patients continuously for up to 4 days post-operatively using a wireless monitoring system. While previous studies mentioned a digit preference of 18–22 for RespR, the most frequently measured RespR were 13–16. However, in the present study we did not validate the measurements against a reference method. Rather, we attempted to demonstrate the feasibility of achieving continuous wireless measurement in patients on surgical postoperative wards. As the technology used is based on impedance pneumography, obstructive apnoea might have been missed, namely in those patients receiving opioids post-operatively.

Multispectral camera fusion increases robustness of ROI detection for biosignal estimation with nearables in real-world scenarios

Thermal cameras enable non-contact estimation of the respiratory rate (RR). Accurate estimation of RR is highly dependent on the reliable detection of the region of interest (ROI), especially when using cameras with low pixel resolution. We present a novel approach for the automatic detection of the human nose ROI, based on facial landmark detection from an RGB camera that is fused with the thermal image after tracking. We evaluated the detection rate and spatial accuracy of the novel algorithm on recordings obtained from 16 subjects under challenging detection scenarios. Results show a high detection rate (median: 100%, 5^th-95^th percentile: 92%- 100%) and very good spatial accuracy with an average root mean square error of 2 pixels in the detected ROI center when compared to manual labeling. Therefore, the implementation of a multispectral camera fusion algorithm is a valid strategy to improve the reliability of non-contact RR estimation with nearable devices featuring thermal cameras.

Improving Respiratory Rate Accuracy in the Hospital: A Quality Improvement Initiative

Respiratory rate (RR) is a predictor of adverse outcomes. However, RRs are inaccurately measured in the hospital. We conducted a quality improvement (QI) initiative using plan-do-study-act methodology on one inpatient unit of a safety-net hospital to improve RR accuracy. We added time-keeping devices to vital sign carts and retrained patient-care assistants on a newly modified workflow that included concomitant RR measurement during automated blood pressure measurement. The median RR was 18 (interquartile range [IQR] 18-20) preintervention versus 14 (IQR 15-20) postintervention. RR accuracy, defined as ±2 breaths of gold-standard measurements, increased from 36% preintervention to 58% postintervention (P < .01). The median time for vital signs decreased from 2:36 minutes (IQR, 2:04-3:20) to 1:55 minutes (IQR, 1:40-2:22; P < .01). The intervention was associated with a 7.8% reduced incidence of tachypnea-specific systemic inflammatory response syndrome (SIRS = 2 points with RR > 20; 95% CI, -13.5% to -2.2%). Our interdisciplinary, low-cost, low-tech QI initiative improved the accuracy and efficiency of RR measurement.

Smoothing Effect in Vital Sign Recordings: Fact or Fiction? A Retrospective Cohort Analysis of Manual and Continuous Vital Sign Measurements to Assess Data Smoothing in Postoperative Care

BACKGROUND:

Data smoothing of vital signs has been reported in the anesthesia literature, suggesting that clinical staff are biased toward measurements of normal physiology. However, these findings may be partially explained by clinicians interpolating spurious values from noisy signals and by the undersampling of physiological changes by infrequent manual observations. We explored the phenomenon of data smoothing using a method robust to these effects in a large postoperative dataset including respiratory rate, heart rate, and oxygen saturation (Spo₂). We also assessed whether the presence of the vital sign taker creates an arousal effect.

METHODS:

Study data came from a UK upper gastrointestinal postoperative ward (May 2009 to December 2013). We compared manually recorded vital sign data with contemporaneous continuous data recorded from monitoring equipment. We proposed that data smoothing increases differences between vital sign sources as vital sign abnormality increases. The primary assessment method was a mixed-effects model relating continuous-manual differences to vital sign values, adjusting for repeated measurements. We tested the regression slope significance and predicted the continuous-manual difference at clinically important vital sign values. We calculated limits of agreement (LoA) between vital sign sources using the Bland–Altman method, adjusting for repeated measures. Similarly, we assessed whether the vital sign taker affected vital signs, comparing continuous data before and during manual recording.

RESULTS:

From 407 study patients, 271 had contemporaneous continuous and manual recordings, allowing 3740 respiratory rate, 3844 heart rate, and 3896 Spo₂ paired measurements for analysis. For the model relating continuous-manual differences to continuous-manual average vital sign values, the regression slope (95% confidence interval) was 0.04 (−0.01 to 0.10; P = .11) for respiratory rate, 0.04 (−0.01 to 0.09; P = .11) for heart rate, and 0.10 (0.07–0.14; P < .001) for Spo₂. For Spo₂ measurements of 91%, the model predicted a continuous-manual difference (95% confidence interval) of −0.88% (−1.17% to −0.60%). The bias (LoA) between measurement sources was −0.74 (−7.80 to 6.32) breaths/min for respiratory rate, −1.13 (−17.4 to 15.1) beats/min for heart rate, and −0.25% (−3.35% to 2.84%) for Spo₂. The bias (LoA) between continuous data before and during manual observation was −0.57 (−5.63 to 4.48) breaths/min for respiratory rate, −0.71 (−10.2 to 8.73) beats/min for heart rate, and −0.07% (−2.67% to 2.54%) for Spo₂.

CONCLUSIONS:

We found no evidence of data smoothing for heart rate and respiratory rate measurements. Although an effect exists for Spo₂ measurements, it was not clinically significant. The wide LoAs between continuous and manually recorded vital signs would commonly result in different early warning scores, impacting clinical care. There was no evidence of an arousal effect caused by the vital sign taker.