A systematic review of novel technology for monitoring infant and newborn heart rate

Non-invasive acquisition of vital data in anesthetized rats using laser and radar application

The aim of this study was to verify the possibility of obtaining vital sign information using a laser and radar sensor in a manner that is non-invasive and painless for test animals. A dataset was obtained from respiratory movement of anaesthetized male F344 rats, signals of laser and radar sensors were recorded simultaneously with vital data acquired with an integrated multiple-channel intraoperative monitor. In addition, respiratory movements were also video recorded, and used as reference data of respiration rate (RR; ref-RR). Reference data for heart rate (HR; ref-HR) were obtained from the R wave of electrocardiogram data for each epoch. Signals recorded from the radar sensor (I- and Q-signals) were input to a computer, and HR (radar-HR) and RR (radar-RR) were estimated using the frequency analysis method. Among the six positions where respiratory movements were measured by the laser sensor, the number of peak counts matched the visual counts of respiratory movements in the video records. The respiratory movements were significantly the greatest over the most caudal rib in the dorsal (p < 0.001). The average radar-RR and ref-RR values showed correspondence (ref-RR, 69 ± 6.2 breaths/min; radar-RR, 68 ± 5.7 breaths/min (p = 0.04-1.00); equivalence ratio, 86%). The radar-HR data showed slight variability; however, there was 80% homology compared with the ref-HR values (ref-HR, 336 ± 19.6 beats/min; radar-HR, 348 ± 34.1 (p = 0.10-0.95)). Although comparison of the data under noradrenaline administration failed to track drug-induced changes in some cases, the HR and RR data of anesthetized rats measured from the radar sensor system showed comparable accuracy to other conventional methods.

Newborn heart rate monitoring methods at birth and clinical outcomes: A systematic review

Aim

Compare heart rate assessment methods in the delivery room on newborn clinical outcomes.

Methods

A search of Medline, SCOPUS, CINAHL and Cochrane was conducted between January 1, 1946, to until August 16, 2023. (CRD 42021283438) Study Selection was based on predetermined criteria. Reviewers independently extracted data, appraised risk of bias and assessed certainty of evidence.

Results

Two randomized controlled trials involving 91 newborns and 1 nonrandomized study involving 632 newborns comparing electrocardiogram (ECG) to auscultation plus pulse oximetry were included. No studies were found that compared any other heart rate measurement methods and reported clinical outcomes. There was no difference between the ECG and control group for duration of positive pressure ventilation, time to heart rate ≥ 100 beats per minute, epinephrine use or death before discharge. In the randomized studies, there was no difference in rate of tracheal intubation [RR 1.34, 95% CI (0.69-2.59)]. No participants received chest compressions. In the nonrandomized study, fewer infants were intubated in the ECG group [RR 0.75, 95% CI (0.62-0.90)]; however, for chest compressions, benefit or harm could not be excluded. [RR 2.14, 95% (CI 0.98-4.70)].

Conclusion

There is insufficient evidence to ascertain clinical benefits or harms associated with the use of ECG versus pulse oximetry plus auscultation for heart rate assessment in newborns in the delivery room.

Does ECG monitoring affect resuscitation for neonates with pulseless electrical activity in the delivery room? A simulated, pilot, crossover randomised trial

OBJECTIVE

To evaluate whether ECG monitoring impacts resuscitative steps during simulated neonatal resuscitation in the setting of pulseless electrical activity (PEA) in the delivery room.

DESIGN

This pilot, crossover randomised controlled trial recruited providers in teams of three who participated in two simulation scenarios (PEA with and without ECG monitoring). Teams were randomised to one scenario and then crossed over. All sessions were video-recorded. The primary outcome was time to pulse check once the manikin was programmed to become pulseless. The secondary outcomes were total pulse checks, time to positive pressure ventilation, intubation, chest compressions and administration of epinephrine, and teams' quotes and behaviours during resuscitation. The primary outcome was analysed using Kaplan-Meier survival curve. The secondary outcomes were compared with Wilcoxon signed-rank test. The quotes were analysed using content analysis with pattern coding.

RESULTS

Eighty-two healthcare providers were approached and 30 consented (10 teams). The mean time to check the pulse once the manikin was pulseless was 38.5 s (SD 30.1) without ECG vs 88.1 s (SD 46.1) with ECG (p<0.01). There was a significantly decreased number of pulse checks with the ECG compared with without (p<0.01). Time to intubation, chest compressions, start of positive pressure ventilation and epinephrine administration was not different between the groups. Quotes/behaviours revealed false reassurance and over-reliance on ECG monitoring, repeated pulse check errors and troubleshooting behaviours.

CONCLUSIONS

ECG monitoring in simulated neonatal resuscitation results in delayed recognition of a pulseless state, decreased number of pulse checks and a possible false sense of security. Simulated resuscitation clinical endpoints are unaffected.

Contactless assessment of heart rate in neonates within a clinical environment using imaging photoplethysmography

Introduction

In neonatology, the accurate determination of vital parameters plays a pivotal role in monitoring critically ill newborns and premature infants, as well as aiding in disease diagnosis. In response to the limitations associated with contact-based measurement methods, substantial efforts have been directed toward developing contactless measurement techniques, particularly over the past decade.

Methods

Building upon the insights gained from our pilot study, we realized a new investigation to assess the precision of our imaging photoplethysmography-based system within a clinical environment of the neonatal intermediate care unit. We conducted measurements in 20 preterm infants or newborns requiring therapeutic interventions. As a point of reference, we employed a conventional pulse oximeter. To analytically predict measurement artifacts, we analyzed the potential influence of confounding factors, such as motion artifacts, illumination fluctuations (under- and overexposure), and loss of region of interest prior to heart rate evaluation. This reduced the amount of data we evaluated for heart rate to 56.1% of its original volume.

Results

In artifact-free time segments, the mean difference between the pulse oximetry and the imaging photoplethysmography-based system for 1 s sampling intervals resulted in -0.2 bpm (95% CI -0.8 to 0.4, LOA ± 12.2). For the clinical standard of 8 s averaging time, the mean difference resulted in -0.09 bpm (95% CI -0.7 to 0.6, LOA ± 10.1). These results match the medical standards.

Discussion

While further research is needed to increase the range of measurable vital parameters and more diverse patient collectives need to be considered in the future, we could demonstrate very high accuracy for non-contact heart rate measurement in newborn infants in the clinical setting, provided artifacts are excluded. In particular, performing a priori signal assessment helps make clinical measurements safer by identifying unreliable readings.

Automated Prediction of Infant Cognitive Development Risk by Video: A Pilot Study

OBJECTIVE

Cognition is an essential human function, and its development in infancy is crucial. Traditionally, pediatricians used clinical observation or medical imaging to assess infants' current cognitive development (CD) status. The object of pediatricians' greater concern is however their future outcomes, because high-risk infants can be identified early in life for intervention. However, this opportunity has not yet been realized. Fortunately, some recent studies have shown that the general movement (GM) performance of infants around 3-4 months after birth might reflect their future CD status, which gives us an opportunity to achieve this goal by cameras and artificial intelligence.

METHODS

First, infants' GM videos were recorded by cameras, from which a series of features reflecting their bilateral movement symmetry (BMS) were extracted. Then, after at least eight months of natural growth, the infants' CD status was evaluated by the Bayley Infant Development Scale, and they were divided into high-risk and low-risk groups. Finally, the BMS features extracted from the early recorded GM videos were fed into the classifiers, using late infant CD risk assessment as the prediction target.

RESULTS

The area under the curve, recall and precision values reached 0.830, 0.832, and 0.823 for two-group classification, respectively.

CONCLUSION

This pilot study demonstrates that it is possible to automatically predict the CD of infants around the age of one year based on their GMs recorded early in life.

SIGNIFICANCE

This study not only helps clinicians better understand infant CD mechanisms, but also provides an economical, portable and non-invasive way to screen infants at high-risk early to facilitate their recovery.

Evaluating a Novel Infant Heart Rate Detector for Neonatal Resuscitation Efforts: Protocol for a Proof-of-Concept Study

BACKGROUND

Over 10 million newborns worldwide undergo resuscitation at birth each year. Pediatricians may use electrocardiogram (ECG), pulse oximetry (PO), and stethoscope in determining heart rate (HR), as HR guides the need for and steps of resuscitation. HR must be obtained quickly and accurately. Unfortunately, the current diagnostic modalities are either too slow, obtaining HR in more than a minute, or inaccurate. With time constraints, a reliable robust heart rate detector (HRD) modality is required. This paper discusses a protocol for conducting a methods-based comparison study to determine the HR accuracy of a novel real-time HRD based on 3D-printed dry-electrode single-lead ECG signals for cost-effective and quick HR determination. The HRD's HR results are compared to either clinical-grade ECG or PO monitors to ensure robustness and accuracy.

OBJECTIVE

The purpose of this study is to design and examine the feasibility of a proof-of-concept HRD that quickly obtains HR using biocompatible 3D-printed dry electrodes for single-lead neonatal ECG acquisition. This study uses a novel HRD and compares it to the gold-standard 3-lead clinical ECG or PO in a hospital setting.

METHODS

A cross-sectional study is planned to be conducted in the neonatal intensive care unit or postpartum unit of a large community teaching hospital in Toronto, Canada, from June 2023 to June 2024. In total, 50 newborns will be recruited for this study. The HRD and an ECG or PO monitor will be video recorded using a digital camera concurrently for 3 minutes for each newborn. Hardware-based signal processing and patent-pending embedded algorithm-based HR estimation techniques are applied directly to the raw collected single-lead ECG and displayed on the HRD in real time during video recordings. These data will be annotated and compared to the ECG or PO readings at the same points in time. Accuracy, F1-score, and other statistical metrics will be produced to determine the HRD's feasibility in providing reliable HR.

RESULTS

The study is ongoing. The projected end date for data collection is around July 2024.

CONCLUSIONS

The study will compare the novel patent-pending 3D-printed dry electrode-based HRD's real-time HR estimation techniques with the state-of-the-art clinical-grade ECG or PO monitors for HR accuracy and examines how fast the HRD provides reliable HR. The study will further provide recommendations and important improvements that can be made to implement the HRD for clinical applications, especially in neonatal resuscitation efforts. This work can be seen as a stepping stone in the development of robust dry-electrode single-lead ECG devices for HR estimations in the pediatric population.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/45512.

Review on the Advancements of Stethoscope Types in Chest Auscultation

Stethoscopes were originally designed for the auscultation of a patient's chest for the purpose of listening to lung and heart sounds. These aid medical professionals in their evaluation of the cardiovascular and respiratory systems, as well as in other applications, such as listening to bowel sounds in the gastrointestinal system or assessing for vascular bruits. Listening to internal sounds during chest auscultation aids healthcare professionals in their diagnosis of a patient's illness. We performed an extensive literature review on the currently available stethoscopes specifically for use in chest auscultation. By understanding the specificities of the different stethoscopes available, healthcare professionals can capitalize on their beneficial features, to serve both clinical and educational purposes. Additionally, the ongoing COVID-19 pandemic has also highlighted the unique application of digital stethoscopes for telemedicine. Thus, the advantages and limitations of digital stethoscopes are reviewed. Lastly, to determine the best available stethoscopes in the healthcare industry, this literature review explored various benchmarking methods that can be used to identify areas of improvement for existing stethoscopes, as well as to serve as a standard for the general comparison of stethoscope quality. The potential use of digital stethoscopes for telemedicine amidst ongoing technological advancements in wearable sensors and modern communication facilities such as 5G are also discussed. Based on the ongoing trend in advancements in wearable technology, telemedicine, and smart hospitals, understanding the benefits and limitations of the digital stethoscope is an essential consideration for potential equipment deployment, especially during the height of the current COVID-19 pandemic and, more importantly, for future healthcare crises when human and resource mobility is restricted.

From Piezoelectric Nanogenerator to Non-Invasive Medical Sensor: A Review

Piezoelectric nanogenerators (PENGs) not only are able to harvest mechanical energy from the ambient environment or body and convert mechanical signals into electricity but can also inform us about pathophysiological changes and communicate this information using electrical signals, thus acting as medical sensors to provide personalized medical solutions to patients. In this review, we aim to present the latest advances in PENG-based non-invasive sensors for clinical diagnosis and medical treatment. While we begin with the basic principles of PENGs and their applications in energy harvesting, this review focuses on the medical sensing applications of PENGs, including detection mechanisms, material selection, and adaptive design, which are oriented toward disease diagnosis. Considering the non-invasive in vitro application scenario, discussions about the individualized designs that are intended to balance a high performance, durability, comfortability, and skin-friendliness are mainly divided into two types: mechanical sensors and biosensors, according to the key role of piezoelectric effects in disease diagnosis. The shortcomings, challenges, and possible corresponding solutions of PENG-based medical sensing devices are also highlighted, promoting the development of robust, reliable, scalable, and cost-effective medical systems that are helpful for the public.

Non-invasive sensor methods used in monitoring newborn babies after birth, a clinical perspective

Background

Reducing the global new-born mortality is a paramount challenge for humanity. There are approximately 786,323 live births in the UK each year according to the office for National Statistics; around 10% of these newborn infants require assistance during this transition after birth. Each year around, globally around 2.5 million newborns die within their first month. The main causes are complications due to prematurity and during delivery. To act in a timely manner and prevent further damage, health professionals should rely on accurate monitoring of the main vital signs heart rate and respiratory rate.

Aims

To present a clinical perspective on innovative, non-invasive methods to monitor heart rate and respiratory rate in babies highlighting their advantages and limitations in comparison with well-established methods.

Methods

Using the data collected in our recently published systematic review we highlight the barriers and facilitators for the novel sensor devices in obtaining reliable heart rate measurements. Details about difficulties related to the application of sensors and interfaces, time to display, and user feedback are explored. We also provide a unique overview of using a non-invasive respiratory rate monitoring method by extracting RR from the pulse oximetry trace of newborn babies.

Results

Novel sensors to monitor heart rate offer the advantages of minimally obtrusive technologies but have limitations due to movement artefact, bad sensor coupling, intermittent measurement, and poor-quality recordings compared to gold standard well established methods. Respiratory rate can be derived accurately from pleth recordings in infants.

Conclusion

Some limitations have been identified in current methods to monitor heart rate and respiratory rate in newborn babies. Novel minimally invasive sensors have advantages that may help clinical practice. Further research studies are needed to assess whether they are sufficiently accurate, practical, and reliable to be suitable for clinical use.

Evaluation of a contactless neonatal physiological monitor in Nairobi, Kenya

BACKGROUND

Globally, 2.5 million neonates died in 2018, accounting for 46% of under-5 deaths. Multiparameter continuous physiological monitoring (MCPM) of neonates allows for early detection and treatment of life-threatening health problems. However, neonatal monitoring technology is largely unavailable in low-resource settings.

METHODS

In four evaluation rounds, we prospectively compared the accuracy of the EarlySense under-mattress device to the Masimo Rad-97 pulse CO-oximeter with capnography reference device for heart rate (HR) and respiratory rate (RR) measurements in neonates in Kenya. EarlySense algorithm optimisations were made between evaluation rounds. In each evaluation round, we compared 200 randomly selected epochs of data using Bland-Altman plots and generated Clarke error grids with zones of 20% to aid in clinical interpretation.

RESULTS

Between 9 July 2019 and 8 January 2020, we collected 280 hours of MCPM data from 76 enrolled neonates. At the final evaluation round, the EarlySense MCPM device demonstrated a bias of -0.8 beats/minute for HR and 1.6 breaths/minute for RR, and normalised spread between the 95% upper and lower limits of agreement of 6.2% for HR and 27.3% for RR. Agreement between the two MCPM devices met the a priori-defined threshold of 30%. The Clarke error grids showed that all observations for HR and 197/200 for RR were within a 20% difference.

CONCLUSION

Our research indicates that there is acceptable agreement between the EarlySense and Masimo MCPM devices in the context of large within-subject variability; however, further studies establishing cost-effectiveness and clinical effectiveness are needed before large-scale implementation of the EarlySense MCPM device in neonates.

TRIAL REGISTRATION NUMBER

NCT03920761.

Preclinical trial of noncontact anthropometric measurement using IR-UWB radar

Anthropometric profiles are important indices for assessing medical conditions, including malnutrition, obesity, and growth disorders. Noncontact methods for estimating those parameters could have considerable value in many practical situations, such as the assessment of young, uncooperative infants or children and the prevention of infectious disease transmission. The purpose of this study was to investigate the feasibility of obtaining noncontact anthropometric measurements using the impulse-radio ultrawideband (IR-UWB) radar sensor technique. A total of 45 healthy adults were enrolled, and a convolutional neural network (CNN) algorithm was implemented to analyze data extracted from IR-UWB radar. The differences (root-mean-square error, RMSE) between values from the radar and bioelectrical impedance analysis (BIA) as a reference in the measurement of height, weight, and body mass index (BMI) were 2.78, 5.31, and 2.25, respectively; predicted data from the radar highly agreed with those from the BIA. The intraclass correlation coefficients (ICCs) were 0.93, 0.94, and 0.83. In conclusion, IR-UWB radar can provide accurate estimates of anthropometric parameters in a noncontact manner; this study is the first to support the radar sensor as an applicable method in clinical situations.

The Use of Foetal Doppler Ultrasound to Determine the Neonatal Heart Rate Immediately after Birth: A Systematic Review

Determining the neonatal heart rate immediately after birth is unsatisfactory. Auscultation is inaccurate and provides no documented results. The use of foetal Doppler ultrasound has been recognised as a possible method of determining the neonatal heart rate after birth over the last nine years. This review includes all published studies of this approach, looking at accuracy, speed of results, and practical application of the approach. Precordial Doppler ultrasound has been shown to be as accurate as ECG and more accurate than oximetry for the neonatal heart rate, and provides quicker results than either ECG or oximetry. There is the potential for a much improved determination and documentation of the neonatal heart rate using this approach.

Detection of acute ventilatory problems via magnetic induction in a newborn animal model

BACKGROUND

Magnetic induction measurement (MIM) is a noninvasive method for the contactless registration of respiration in newborn piglets by using measurement coils positioned at the bottom of an incubator. Acute pulmonary problems may be determinants of poor neurological and psychomotor outcomes in preterm infants. The current study tested the detection of pulmonary ventilation disorders via MIM in 11 newborn piglets.

METHODS

Six measurement coils determined changes in magnetic induction, depending on the ventilation of the lung, in comparison with flow resistance. Contactless registration of induced acute pulmonary ventilation disorders (apnea, atelectasis, pneumothorax, and aspiration) was detected by MIM.

RESULTS

All pathologies except aspiration were detected by MIM. Significant changes occurred after induction of apnea (three coils), malposition of the tube (one coil), and pneumothorax (three coils) (p ≤ 0.05). No significant changes occurred after induction of aspiration (p = 0.12).

CONCLUSIONS

MIM seems to have some potential to detect acute ventilation disorders in newborn piglets. The location of the measurement coil related to the animal's position plays a critical role in this process. In addition to an early detection of acute pulmonary problems, potential information pointing to a therapeutic intervention, for example, inhalations or medical respiratory analepsis, may be conceivable with MIM in the future.

IMPACT

MIM seems to be a method in which noncontact ventilation disorders of premature and mature infants can be detected. This study is an extension of the experimental setup to obtain preliminary evidence for detection of respiratory activity in neonatal piglets. For the first time, MIM is used to register acute ventilation problems of neonates. The possibility of an early detection of acute ventilation problems via MIM may provide an opportunity to receive patient-side information for therapeutical interventions like inhalations or medical respiratory analepsis.

Non-contact physiological monitoring of post-operative patients in the intensive care unit

Prolonged non-contact camera-based monitoring in critically ill patients presents unique challenges, but may facilitate safe recovery. A study was designed to evaluate the feasibility of introducing a non-contact video camera monitoring system into an acute clinical setting. We assessed the accuracy and robustness of the video camera-derived estimates of the vital signs against the electronically-recorded reference values in both day and night environments. We demonstrated non-contact monitoring of heart rate and respiratory rate for extended periods of time in 15 post-operative patients. Across day and night, heart rate was estimated for up to 53.2% (103.0 h) of the total valid camera data with a mean absolute error (MAE) of 2.5 beats/min in comparison to two reference sensors. We obtained respiratory rate estimates for 63.1% (119.8 h) of the total valid camera data with a MAE of 2.4 breaths/min against the reference value computed from the chest impedance pneumogram. Non-contact estimates detected relevant changes in the vital-sign values between routine clinical observations. Pivotal respiratory events in a post-operative patient could be identified from the analysis of video-derived respiratory information. Continuous vital-sign monitoring supported by non-contact video camera estimates could be used to track early signs of physiological deterioration during post-operative care.

Contactless heart rate measurement in newborn infants using a multimodal 3D camera system

Newborns and preterm infants require accurate and continuous monitoring of their vital parameters. Contact-based methods of monitoring have several disadvantages, thus, contactless systems have increasingly attracted the neonatal communities' attention. Camera-based photoplethysmography is an emerging method of contactless heart rate monitoring. We conducted a pilot study in 42 healthy newborn and near-term preterm infants for assessing the feasibility and accuracy of a multimodal 3D camera system on heart rates (HR) in beats per min (bpm) compared to conventional pulse oximetry. Simultaneously, we compared the accuracy of 2D and 3D vision on HR measurements. The mean difference in HR between pulse oximetry and 2D-technique added up to + 3.0 bpm [CI-3.7 - 9.7; p = 0.359, limits of agreement (LOA) ± 36.6]. In contrast, 3D-technique represented a mean difference in HR of + 8.6 bpm (CI 2.0-14.9; p = 0.010, LOA ± 44.7) compared to pulse oximetry HR. Both, intra- and interindividual variance of patient characteristics could be eliminated as a source for the results and the measuring accuracy achieved. Additionally, we proved the feasibility of this emerging method. Camera-based photoplethysmography seems to be a promising approach for HR measurement of newborns with adequate precision; however, further research is warranted.

Non-Contact Automatic Vital Signs Monitoring of Infants in a Neonatal Intensive Care Unit Based on Neural Networks

Infants with fragile skin are patients who would benefit from non-contact vital sign monitoring due to the avoidance of potentially harmful adhesive electrodes and cables. Non-contact vital signs monitoring has been studied in clinical settings in recent decades. However, studies on infants in the Neonatal Intensive Care Unit (NICU) are still limited. Therefore, we conducted a single-center study to remotely monitor the heart rate (HR) and respiratory rate (RR) of seven infants in NICU using a digital camera. The region of interest (ROI) was automatically selected using a convolutional neural network and signal decomposition was used to minimize the noise artefacts. The experimental results have been validated with the reference data obtained from an ECG monitor. They showed a strong correlation using the Pearson correlation coefficients (PCC) of 0.9864 and 0.9453 for HR and RR, respectively, and a lower error rate with RMSE 2.23 beats/min and 2.69 breaths/min between measured data and reference data. A Bland-Altman analysis of the data also presented a close correlation between measured data and reference data for both HR and RR. Therefore, this technique may be applicable in clinical environments as an economical, non-contact, and easily deployable monitoring system, and it also represents a potential application in home health monitoring.

Infant heart-rate measurement and oxygen desaturation detection with a digital video camera using imaging photoplethysmography

OBJECTIVE

To assess the feasibility of using an ordinary digital video camera to measure heart rate and detect oxygen desaturations in healthy infants.

STUDY DESIGN

Heart rate and oxygen saturation were measured with a video camera by detecting small color changes in 28 infants' foreheads and compared with standard pulse oximetry measures. Multivariable regression examined the relationship between infant characteristics and heart-rate measurement precision.

RESULTS

The average bias of camera heart-rate measures was -4.2 beats per minute (BPM) and 95% limits of agreement were ±43.8 BPM. Desaturations detected by camera were 75% sensitive (15/20) and had a positive predictive value of 20% (15/74). Lower birth-weight was independently correlated with more precise heart-rate measures (8.05 BPM per kg, [95% CI 0.764-15.3]).

CONCLUSIONS

A digital video camera provides accurate but imprecise measures of infant heart rate and may provide a rough screening tool for oxygen desaturations.

A Review of Deep Learning-Based Contactless Heart Rate Measurement Methods

The interest in contactless or remote heart rate measurement has been steadily growing in healthcare and sports applications. Contactless methods involve the utilization of a video camera and image processing algorithms. Recently, deep learning methods have been used to improve the performance of conventional contactless methods for heart rate measurement. After providing a review of the related literature, a comparison of the deep learning methods whose codes are publicly available is conducted in this paper. The public domain UBFC dataset is used to compare the performance of these deep learning methods for heart rate measurement. The results obtained show that the deep learning method PhysNet generates the best heart rate measurement outcome among these methods, with a mean absolute error value of 2.57 beats per minute and a mean square error value of 7.56 beats per minute.

Recent Advances in Atherosclerotic Disease Screening Using Pervasive Healthcare

Atherosclerosis screening helps the medical model transform from therapeutic medicine to preventive medicine by assessing degree of atherosclerosis prior to the occurrence of fatal vascular events. Pervasive screening emphasizes atherosclerotic monitoring with easy access, quick process, and advanced computing. In this work, we introduced five cutting-edge pervasive technologies including imaging photoplethysmography (iPPG), laser Doppler, radio frequency (RF), thermal imaging (TI), optical fiber sensing and piezoelectric sensor. IPPG measures physiological parameters by using video images that record the subtle skin color changes consistent with cardiac-synchronous blood volume changes in subcutaneous arteries and capillaries. Laser Doppler obtained the information on blood flow by analyzing the spectral components of backscattered light from the illuminated tissues surface. RF is based on Doppler shift caused by the periodic movement of the chest wall induced by respiration and heartbeat. TI measures vital signs by detecting electromagnetic radiation emitted by blood flow. The working principle of optical fiber sensor is to detect the change of light properties caused by the interaction between the measured physiological parameter and the entering light. Piezoelectric sensors are based on the piezoelectric effect of dielectrics. All these pervasive technologies are noninvasive, mobile, and can detect physiological parameters related to atherosclerosis screening.

Preterm Newborn Presence Detection in Incubator and Open Bed Using Deep Transfer Learning

Video-based motion analysis recently appeared to be a promising approach in neonatal intensive care units for monitoring the state of preterm newborns since it is contact-less and noninvasive. However it is important to remove periods when the newborn is absent or an adult is present from the analysis. In this paper, we propose a method for automatic detection of preterm newborn presence in incubator and open bed. We learn a specific model for each bed type as the camera placement differs a lot and the encountered situations are different between both. We break the problem down into two binary classifications based on deep transfer learning that are fused afterwards: newborn presence detection on the one hand and adult presence detection on the other hand. Moreover, we adopt a strategy of decision intervals fusion in order to take advantage of temporal consistency. We test three deep neural network that were pre-trained on ImageNet: VGG16, MobileNetV2 and InceptionV3. Two classifiers are compared: support vector machine and a small neural network. Our experiments are conducted on a database of 120 newborns. The whole method is evaluated on a subset of 25 newborns including 66 days of video recordings. In incubator, we reach a balanced accuracy of 86%. In open bed, the performance is lower because of a much wider variety of situations whereas less data are available.

Detection of Pathologic Heart Murmurs Using a Piezoelectric Sensor

This study aimed to evaluate the capability of a piezoelectric sensor to detect a heart murmur in patients with congenital heart defects. Heart sounds and murmurs were recorded using a piezoelectric sensor and an electronic stethoscope in healthy neonates (n = 9) and in neonates with systolic murmurs caused by congenital heart defects (n = 9) who were born at a hospital. Signal data were digitally filtered by high-pass filtering, and the envelope of the processed signals was calculated. The amplitudes of systolic murmurs were evaluated using the signal-to-noise ratio and compared between healthy neonates and those with congenital heart defects. In addition, the correlation between the amplitudes of systolic murmurs recorded by the piezoelectric sensor and electronic stethoscope was determined. The amplitudes of systolic murmurs detected by the piezoelectric sensor were significantly higher in neonates with congenital heart defects than in healthy neonates (p < 0.01). Systolic murmurs recorded by the piezoelectric sensor had a strong correlation with those recorded by the electronic stethoscope (ρ = 0.899 and p < 0.01, respectively). The piezoelectric sensor can detect heart murmurs objectively. Mechanical improvement and automatic analysis algorithms are expected to improve recording in the future.

Feasibility of non-contact cardiorespiratory monitoring using impulse-radio ultra-wideband radar in the neonatal intensive care unit

Background

Current cardiorespiratory monitoring equipment can cause injuries and infections in neonates with fragile skin. Impulse-radio ultra-wideband (IR-UWB) radar was recently demonstrated to be an effective contactless vital sign monitor in adults. The purpose of this study was to assess heart rates (HRs) and respiratory rates (RRs) in the neonatal intensive care unit (NICU) using IR-UWB radar and to evaluate its accuracy and reliability compared to conventional electrocardiography (ECG)/impedance pneumography (IPG).

Methods

The HR and RR were recorded in 34 neonates between 3 and 72 days of age during minimal movement (51 measurements in total) using IR-UWB radar (HR_Rd, RR_Rd) and ECG/IPG (HR_ECG, RR_IPG) simultaneously. The radar signals were processed in real time using algorithms for neonates. Radar and ECG/IPG measurements were compared using concordance correlation coefficients (CCCs) and Bland-Altman plots.

Results

From the 34 neonates, 12,530 HR samples and 3,504 RR samples were measured. Both the HR and RR measured using the two methods were highly concordant when the neonates had minimal movements (CCC = 0.95 between the RR_Rd and RR_IPG, CCC = 0.97 between the HR_Rd and HR_ECG). In the Bland-Altman plot, the mean biases were 0.17 breaths/min (95% limit of agreement [LOA] -7.0–7.3) between the RR_Rd and RR_IPG and -0.23 bpm (95% LOA -5.3–4.8) between the HR_Rd and HR_ECG. Moreover, the agreement for the HR and RR measurements between the two modalities was consistently high regardless of neonate weight.

Conclusions

A cardiorespiratory monitor using IR-UWB radar may provide accurate non-contact HR and RR estimates without wires and electrodes for neonates in the NICU.

Heart Rate Variability in the Perinatal Period: A Critical and Conceptual Review

Neonatal intensive care units (NICUs) greatly expand the use of technology. There is a need to accurately diagnose discomfort, pain, and complications, such as sepsis, mainly before they occur. While specific treatments are possible, they are often time-consuming, invasive, or painful, with detrimental effects for the development of the infant. In the last 40 years, heart rate variability (HRV) has emerged as a non-invasive measurement to monitor newborns and infants, but it still is underused. Hence, the present paper aims to review the utility of HRV in neonatology and the instruments available to assess it, showing how HRV could be an innovative tool in the years to come. When continuously monitored, HRV could help assess the baby’s overall wellbeing and neurological development to detect stress-/pain-related behaviors or pathological conditions, such as respiratory distress syndrome and hyperbilirubinemia, to address when to perform procedures to reduce the baby’s stress/pain and interventions, such as therapeutic hypothermia, and to avoid severe complications, such as sepsis and necrotizing enterocolitis, thus reducing mortality. Based on literature and previous experiences, the first step to efficiently introduce HRV in the NICUs could consist in a monitoring system that uses photoplethysmography, which is low-cost and non-invasive, and displays one or a few metrics with good clinical utility. However, to fully harness HRV clinical potential and to greatly improve neonatal care, the monitoring systems will have to rely on modern bioinformatics (machine learning and artificial intelligence algorithms), which could easily integrate infant’s HRV metrics, vital signs, and especially past history, thus elaborating models capable to efficiently monitor and predict the infant’s clinical conditions. For this reason, hospitals and institutions will have to establish tight collaborations between the obstetric, neonatal, and pediatric departments: this way, healthcare would truly improve in every stage of the perinatal period (from conception to the first years of life), since information about patients’ health would flow freely among different professionals, and high-quality research could be performed integrating the data recorded in those departments.

Defining information needs in neonatal resuscitation with work domain analysis

OBJECTIVE

To gain a deeper understanding of the information requirements of clinicians conducting neonatal resuscitation in the first 10 min after birth.

BACKGROUND

During the resuscitation of a newborn infant in the first minutes after birth, clinicians must monitor crucial physiological adjustments that are relatively unobservable, unpredictable, and highly variable. Clinicians' access to information regarding the physiological status of the infant is also crucial to determining which interventions are most appropriate. To design displays to support clinicians during newborn resuscitation, we must first carefully consider the information requirements.

METHODS

We conducted a work domain analysis (WDA) for the neonatal transition in the first 10 min after birth. We split the work domain into two 'subdomains'; the physiology of the neonatal transition, and the clinical resources supporting the neonatal transition. A WDA can reveal information requirements that are not yet supported by resources.

RESULTS

The physiological WDA acted as a conceptual tool to model the exact processes and functions that clinicians must monitor and potentially support during the neonatal transition. Importantly, the clinical resources WDA revealed several capabilities and limitations of the physical objects in the work domain-ultimately revealing which physiological functions currently have no existing sensor to provide clinicians with information regarding their status.

CONCLUSION

We propose two potential approaches to improving the clinician's information environment: (1) developing new sensors for the information we lack, and (2) employing principles of ecological interface design to present currently available information to the clinician in a more effective way.

Heart Rate Assessment during Neonatal Resuscitation

Approximately 10% of newborn infants require some form of respiratory support to successfully complete the fetal-to-neonatal transition. Heart rate (HR) determination is essential at birth to assess a newborn’s wellbeing. Not only is it the most sensitive indicator to guide interventions during neonatal resuscitation, it is also valuable for assessing the infant’s clinical status. As such, HR assessment is a key step at birth and throughout resuscitation, according to recommendations by the Neonatal Resuscitation Program algorithm. It is essential that HR is accurate, reliable, and fast to ensure interventions are delivered without delay and not prolonged. Ineffective HR assessment significantly increases the risk of hypoxic injury and infant mortality. The aims of this review are to summarize current practice, recommended techniques, novel technologies, and considerations for HR assessment during neonatal resuscitation at birth.

Smartphone app for neonatal heart rate assessment: an observational study

BACKGROUND

Heart rate (HR) assessment is crucial in neonatal resuscitation, but pulse oximetry (PO) and electrocardiography (ECG) are rarely accessible in low-resource to middle-resource settings. This study evaluated a free-of-charge smartphone application, NeoTap, which records HR with a screen-tapping method bypassing mental arithmetic calculations.

METHODS

This observational study was carried out during three time periods between May 2015 and January 2019 in Uganda in three phases. In phase 1, a metronome rate (n=180) was recorded by low-end users (midwives) using NeoTap. In phase 2, HR (n=69) in breathing neonates was recorded by high-end users (paediatricians) using NeoTap versus PO. In phase 3, HR (n=235) in non-breathing neonates was recorded by low-end users using NeoTap versus ECG.

RESULTS

In high-end users the mean difference was 3 beats per minute (bpm) higher with NeoTap versus PO (95% agreement limits -14 to 19 bpm), with acquisition time of 5 seconds. In low-end users, the mean difference was 6 bpm lower with NeoTap versus metronome (95% agreement limits -26 to 14 bpm) and 3 bpm higher with NeoTap versus ECG in non-breathing neonates (95% agreement limits -48 to 53 bpm), with acquisition time of 2.7 seconds. The agreement between NeoTap and ECG was good in the HR categories of 60-99 bpm and ≥100 bpm; HR <60 bpm had few measurements (kappa index 0.71, 95% CI 0.63 to 0.79).

CONCLUSION

HR could be accurately and rapidly assessed using a smartphone application in breathing neonates in a low-resource setting. Clinical assessment by low-end users was less accurate with wider CI but still adds clinically important information in non-breathing neonates. The authors suggest low-end users may benefit from auscultation-focused training. More research is needed to evaluate its feasibility in clinical use.

Non-contact physiological monitoring of preterm infants in the Neonatal Intensive Care Unit

The implementation of video-based non-contact technologies to monitor the vital signs of preterm infants in the hospital presents several challenges, such as the detection of the presence or the absence of a patient in the video frame, robustness to changes in lighting conditions, automated identification of suitable time periods and regions of interest from which vital signs can be estimated. We carried out a clinical study to evaluate the accuracy and the proportion of time that heart rate and respiratory rate can be estimated from preterm infants using only a video camera in a clinical environment, without interfering with regular patient care. A total of 426.6 h of video and reference vital signs were recorded for 90 sessions from 30 preterm infants in the Neonatal Intensive Care Unit (NICU) of the John Radcliffe Hospital in Oxford. Each preterm infant was recorded under regular ambient light during daytime for up to four consecutive days. We developed multi-task deep learning algorithms to automatically segment skin areas and to estimate vital signs only when the infant was present in the field of view of the video camera and no clinical interventions were undertaken. We propose signal quality assessment algorithms for both heart rate and respiratory rate to discriminate between clinically acceptable and noisy signals. The mean absolute error between the reference and camera-derived heart rates was 2.3 beats/min for over 76% of the time for which the reference and camera data were valid. The mean absolute error between the reference and camera-derived respiratory rate was 3.5 breaths/min for over 82% of the time. Accurate estimates of heart rate and respiratory rate could be derived for at least 90% of the time, if gaps of up to 30 seconds with no estimates were allowed.

Circulatory emergencies in the delivery room

The transition from fetal to neonatal life is a dramatic and complex process involving extensive physiologic changes, which are most obvious at the time of birth. Individuals who care for newly born infants must monitor the progress of the transition and be prepared to intervene when necessary. In the majority of births, this transition occurs without a requirement for any significant assistance. If newborns require assistance, the majority of the time respiratory support is all that is required. In some instances, however, there are circulatory emergencies that need to be rapidly identified or there may be dire consequences including death in the delivery room. This chapter will review various pathologies that are circulatory emergencies, and discuss how to assess them. We will also review new technologies which may help providers better understand the circulatory status or hemodynamic changes in the delivery room including heart rate, cardiac output, cerebral oxygenation and echocardiography.

Non-contact respiration monitoring using impulse radio ultrawideband radar in neonates

Vital sign monitoring in neonates requires adhesive electrodes, which often damage fragile newborn skin. Because impulse radio ultrawideband (IR-UWB) radar has been reported to recognize chest movement without contact in adult humans, IR-UWB may be used to measure respiratory rates (RRs) in a non-contact fashion. We investigated the feasibility of radar sensors for respiration monitoring in neonates without any respiratory support to compare the accuracy and reliability of radar measurements with those of conventional impedance pneumography measurements. In the neonatal intensive care unit, RRs were measured using radar (RRRd) and impedance pneumography (RRIP) simultaneously. The neonatal voluntary movements were measured using the radar sensor and categorized into three levels (low [M0], intermediate [M1] and high [M2]). RRRd highly agreed with RRIP (r = 0.90; intraclass correlation coefficient [ICC] = 0.846 [0.835-0.856]). For the M0 movement, there was good agreement between RRRd and RRIP (ICC = 0.893; mean bias -0.15 [limits of agreement (LOA) -9.6 to 10.0]). However, the agreement was slightly lower for the M1 (ICC = 0.833; mean bias = 0.95 [LOA -11.4 to 13.3]) and M2 (ICC = 0.749; mean bias = 3.04 [LOA -9.30 to 15.4]) movements than for the M0 movement. In conclusion, IR-UWB radar can provide accurate and reliable estimates of RR in neonates in a non-contact fashion. The performance of radar measurements could be affected by neonate movement.

Who's counting? Assessing the effects of a simulation-based training intervention on the accuracy of neonatal heart rate auscultation

OBJECTIVE

To determine if simulation-based medical education could improve pediatric residents' ability to accurately assess neonatal heart rate via auscultation.

STUDY DESIGN

Primary outcomes included heart rate accuracy and Neonatal Resuscitation Program (NRP) group accuracy, defined as whether a heart rate estimation fell in the appropriate NRP algorithm group. Pediatric residents completed a pre-assessment and then participated in a simulation training intervention on high-fidelity manikins. Residents completed a post-assessment 1 month later.

RESULTS

Heart rate estimates from 21 pediatric residents showed improved overall heart rate accuracy and NRP group accuracy from 53.6 to 78.7% (p < 0.0001) and 68.3 to 80% (p = 0.0002), respectively. Residents were more likely to overestimate low heart rates and underestimate high heart rates.

CONCLUSION

Heart rate simulation-based training significantly improved residents' ability to assess heart rate on high-fidelity neonatal manikins. Providers participating in NRP may benefit by receiving heart rate skills assessment-focused training during an NRP provider course.

The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review

Background

Mobile phone apps capable of monitoring arrhythmias and heart rate (HR) are increasingly used for screening, diagnosis, and monitoring of HR and rhythm disorders such as atrial fibrillation (AF). These apps involve either the use of (1) photoplethysmographic recording or (2) a handheld external electrocardiographic recording device attached to the mobile phone or wristband.

Objective

This review seeks to explore the current state of mobile phone apps in cardiac rhythmology while highlighting shortcomings for further research.

Methods

We conducted a narrative review of the use of mobile phone devices by searching PubMed and EMBASE from their inception to October 2018. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) mobile phone monitoring, (2) AF, (3) HR, and (4) HR variability (HRV).

Results

The findings of this narrative review suggest that there is a role for mobile phone apps in the diagnosis, monitoring, and screening for arrhythmias and HR. Photoplethysmography and handheld electrocardiograph recorders are the 2 main techniques adopted in monitoring HR, HRV, and AF.

Conclusions

A number of studies have demonstrated high accuracy of a number of different mobile devices for the detection of AF. However, further studies are warranted to validate their use for large scale AF screening.

Heart Rate Monitoring in Newborn Babies: A Systematic Review

BACKGROUND

Around 10% of newborn infants require assistance during transition after birth. Heart rate (HR) is the most important clinical indicator to evaluate the clinical status of a newborn.

AIM

Our study aimed to review all established and novel methods to detect HR in babies giving special consideration to non-invasive techniques.

METHODS

We performed a systematic literature search on the following databases: MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), and CINAHL. The inclusion criteria were studies on methods to detect HR in both term and preterm infants in comparison to one of the current gold standards: pulse oximetry (PO) or electrocardiography (ECG) published in the last 15 years. Two independent reviewers screened titles and abstracts for eligibility. Data extracted in an Excel table were analysed to produce a narrative review structured around the type of monitoring, identified obstacles in use, as well as methods to overcome these limitations.

RESULTS

The search revealed 649 studies after duplicates were removed. Full article analysis was performed on 26 studies of which 25 met the inclusion criteria. Well established methods such as auscultation and palpation, although rapid and easily available, have been shown to be inaccurate. ECG and PO were both more precise but the delay in obtaining a reliable HR signal from birth often exceeded 1-2 min. Novel sensors offered the advantages of minimally obtrusive technologies but have limitations mainly due to movement artefact, bad sensor coupling, intermittent measurement, and poor-quality recordings.

CONCLUSIONS

The limitations of existing methods have a potential impact on short- and long-term morbidity and mortality outcomes. The development of a technological solution to determine HR accurately and quickly in babies at birth has immense implications for further research and can guide interventions, such as placental transfusion and resuscitation.

Unobtrusive Vital Sign Monitoring in Automotive Environments-A Review

This review provides an overview of unobtrusive monitoring techniques that could be used to monitor some of the human vital signs (i.e., heart activity, breathing activity, temperature and potentially oxygen saturation) in a car seat. It will be shown that many techniques actually measure mechanical displacement, either on the body surface and/or inside the body. However, there are also techniques like capacitive electrocardiogram or bioimpedance that reflect electrical activity or passive electrical properties or thermal properties (infrared thermography). In addition, photopleythysmographic methods depend on optical properties (like scattering and absorption) of biological tissues and-mainly-blood. As all unobtrusive sensing modalities are always fragile and at risk of being contaminated by disturbances (like motion, rapidly changing environmental conditions, triboelectricity), the scope of the paper includes a survey on redundant sensor arrangements. Finally, this review also provides an overview of automotive demonstrators for vital sign monitoring.

Accurate and fast neonatal heart rate assessment with a smartphone-based application - a manikin study

AIM

This study determined the accuracy and speed of the NeoTapLifeSupport (NeoTapLS), a free smartphone application that aims to assess a neonate's heart rate.

METHODS

We asked 30 participants with a variety of backgrounds to test the NeoTapLS, which was developed by our own nonprofit organisation Tap4Life, to determine a randomly selected heart rate by auscultation or palpation. The study was carried out in 2014 at Sachs' Children and Youth Hospital, Sweden, using a Laerdal SimNewB manikin that simulates true values. The NeoTapLS calculates the heart rate based on the user's last three taps on the smartphone screen.

RESULTS

A total of 1200 measurements were carried out. A high correlation was found between measured and true values by auscultation (correlation coefficient 0.993) as well as by palpation (correlation coefficient 0.986) with 93.5% of the auscultations and 86.3% of the palpations differing from the true value by five beats or fewer. The mean time to the first estimated heart rate was 14.9 seconds for auscultation and 16.3 seconds for palpation.

CONCLUSION

Heart rates could be accurately and rapidly assessed using the NeoTapLS on a manikin. A globally accessible mobile health system could offer a low-cost alternative to expensive medical equipment.