Acoustic analysis of neonatal breath sounds using digital stethoscope technology

Reimagining apnea monitoring in the neonatal ICU

PURPOSE OF REVIEW

This review outlines the prevalence and complications of apneas and intermittent hypoxemic events in preterm infants, examines current monitoring limitations in neonatal ICUs (NICUs), and explores emerging technologies addressing these challenges.

RECENT FINDINGS

New evidence from the Prematurity-Related Ventilatory Control (Pre-Vent) study, which analyzed cardiorespiratory data from 717 extremely preterm infants, exposes the varying frequency, duration, and severity of apneas, intermittent hypoxemia, bradycardias, and periodic breathing during hospitalization, and highlights the negative impact of intermittent hypoxemia on pulmonary outcomes at discharge. Although traditional monitoring methods cannot differentiate between apnea types and quantify their burden, recent advancements in sensor technologies and data integration hold promise for improving real-time detection and evaluation of apneas in the NICU. Notably, small wearable mechano-acoustic sensors could improve apnea monitoring through continuous detection of airflow and respiratory efforts. Additionally, integrating bedside physiological data with modalities such as near-infrared spectroscopy, diaphragmatic activity, and electrical impedance tomography could help predict adverse outcomes by monitoring regional oxygen saturation and lung function in relation to apneas.

SUMMARY

Enhancing our understanding of neonatal apneas and overcoming the current limitations in apnea monitoring through advanced sensor technologies and data integration could lead to more personalized management and improved outcomes for preterm infants.

Acoustic and Perceptual Profiles of Swallowing Sounds in Preterm Neonates: A Cross-Sectional Study Cohort

Cervical auscultation, commonly used by speech-language pathologists in some countries as an adjuvant to the clinical feeding evaluation, requires data on acoustic and perceptual profiles of swallowing sounds. Whilst these exists in adults and children, none currently exist for preterm neonates. Our study aims to establish the acoustic and perceptual parameters of swallowing sounds in preterm neonates. Swallowing sounds were recorded on a digital microphone during oral feeding observations. Acoustic parameters of duration, peak frequency, peak power and peak intensity were determined. Perceptual parameters heard pre, during and post-swallows were rated as 'present', 'absent', or 'cannot be determined'. Eighty preterm neonates (43 males; mean age = 33.4 weeks [SD 2.6]) from three Australian special care nurseries demonstrated mean swallow durations of < 1 s. The peak amplitude correlated with the number of medical co-morbidities (r = 0.24; 95%CI 0.03-0.45). Most preterm neonates have coordinated swallows that are loud, quick and completed in < 1 s. The perceptual parameters of a bolus transit sound was consistently present in all preterm neonates. One in five pre-term neonates have an uncoordinated swallow where wheeze, stridor or wet breath sounds were present post-swallow. Our study provides clinicians with acoustic and perceptual parameters to guide use of cervical auscultation in special care nurseries. Future studies should consider simultaneous instrumental assessment to ensure validity when using cervical auscultation to support diagnostic decision-making on swallowing coordination.

Wireless broadband acousto-mechanical sensing system for continuous physiological monitoring

The human body generates various forms of subtle, broadband acousto-mechanical signals that contain information on cardiorespiratory and gastrointestinal health with potential application for continuous physiological monitoring. Existing device options, ranging from digital stethoscopes to inertial measurement units, offer useful capabilities but have disadvantages such as restricted measurement locations that prevent continuous, longitudinal tracking and that constrain their use to controlled environments. Here we present a wireless, broadband acousto-mechanical sensing network that circumvents these limitations and provides information on processes including slow movements within the body, digestive activity, respiratory sounds and cardiac cycles, all with clinical grade accuracy and independent of artifacts from ambient sounds. This system can also perform spatiotemporal mapping of the dynamics of gastrointestinal processes and airflow into and out of the lungs. To demonstrate the capabilities of this system we used it to monitor constrained respiratory airflow and intestinal motility in neonates in the neonatal intensive care unit (n = 15), and to assess regional lung function in patients undergoing thoracic surgery (n = 55). This broadband acousto-mechanical sensing system holds the potential to help mitigate cardiorespiratory instability and manage disease progression in patients through continuous monitoring of physiological signals, in both the clinical and nonclinical setting.

Health Monitoring via Heart, Breath, and Korotkoff Sounds by Wearable Piezoelectret Patches

Real-time monitoring of vital sounds from cardiovascular and respiratory systems via wearable devices together with modern data analysis schemes have the potential to reveal a variety of health conditions. Here, a flexible piezoelectret sensing system is developed to examine audio physiological signals in an unobtrusive manner, including heart, Korotkoff, and breath sounds. A customized electromagnetic shielding structure is designed for precision and high-fidelity measurements and several unique physiological sound patterns related to clinical applications are collected and analyzed. At the left chest location for the heart sounds, the S1 and S2 segments related to cardiac systole and diastole conditions, respectively, are successfully extracted and analyzed with good consistency from those of a commercial medical device. At the upper arm location, recorded Korotkoff sounds are used to characterize the systolic and diastolic blood pressure without a doctor or prior calibration. An Omron blood pressure monitor is used to validate these results. The breath sound detections from the lung/ trachea region are achieved a signal-to-noise ration comparable to those of a medical recorder, BIOPAC, with pattern classification capabilities for the diagnosis of viable respiratory diseases. Finally, a 6×6 sensor array is used to record heart sounds at different locations of the chest area simultaneously, including the Aortic, Pulmonic, Erb's point, Tricuspid, and Mitral regions in the form of mixed data resulting from the physiological activities of four heart valves. These signals are then separated by the independent component analysis algorithm and individual heart sound components from specific heart valves can reveal their instantaneous behaviors for the accurate diagnosis of heart diseases. The combination of these demonstrations illustrate a new class of wearable healthcare detection system for potentially advanced diagnostic schemes.

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.

Quantification of respiratory sounds by a continuous monitoring system can be used to predict complications after extubation: a pilot study

To show that quantification of abnormal respiratory sounds by our developed device is useful for predicting respiratory failure and airway problems after extubation. A respiratory sound monitoring system was used to collect respiratory sounds in patients undergoing extubation. The recorded respiratory sounds were subsequently analyzed. We defined the composite poor outcome as requiring any of following medical interventions within 48 h as defined below. This composite outcome includes reintubation, surgical airway management, insertion of airway devices, unscheduled use of noninvasive ventilation or high-flow nasal cannula, unscheduled use of inhaled medications, suctioning of sputum by bronchoscopy and unscheduled imaging studies. The quantitative values (QV) for each abnormal respiratory sound and inspiratory sound volume were compared between composite outcome groups and non-outcome groups. Fifty-seven patients were included in this study. The composite outcome occurred in 18 patients. For neck sounds, the QVs of stridor and rhonchi were significantly higher in the outcome group vs the non-outcome group. For anterior thoracic sounds, the QVs of wheezes, rhonchi, and coarse crackles were significantly higher in the outcome group vs the non-outcome group. For bilateral lateral thoracic sounds, the QV of fine crackles was significantly higher in the outcome group vs the non-outcome group. Cervical inspiratory sounds volume (average of five breaths) immediately after extubation was significantly louder in the outcome group vs non-outcome group (63.3 dB vs 54.3 dB, respectively; p < 0.001). Quantification of abnormal respiratory sounds and respiratory volume may predict respiratory failure and airway problems after extubation.

Regional respiratory sound abnormalities in pneumothorax and pleural effusion detected via respiratory sound visualization and quantification: case report

Assessment of respiratory sounds by auscultation with a conventional stethoscope is subjective. We developed a continuous monitoring and visualization system that enables objectively and quantitatively visualizing respiratory sounds. We herein present two cases in which the system showed regional differences in the respiratory sounds. We applied our novel continuous monitoring and visualization system to evaluate respiratory abnormalities in patients with acute chest disorders. Respiratory sounds were continuously recorded to assess regional changes in respiratory sound volumes. Because we used this system as a pilot study, the results were not shown in real time and were retrospectively analyzed. Case 1 An 89-year-old woman was admitted to our hospital for sudden-onset respiratory distress and hypoxia. Chest X-rays revealed left pneumothorax; thus, we drained the thorax. After confirming that the pneumothorax had improved, we attached the continuous monitoring and visualization system. Chest X-rays taken the next day showed exacerbation of the pneumothorax. Visual and quantitative findings showed a decreased respiratory volume in the left lung after 3 h. Case 2 A 94-year-old woman was admitted to our hospital for dyspnea. Chest X-rays showed a large amount of pleural effusion on the right side. The continuous monitoring and visualization system visually and quantitatively revealed a decreased respiratory volume in the lower right lung field compared with that in the lower left lung field. Our newly developed continuous monitoring and visualization system enabled quantitatively and visually detecting regional differences in respiratory sounds in patients with pneumothorax and pleural effusion.

A New Non-Negative Matrix Co-Factorisation Approach for Noisy Neonatal Chest Sound Separation

Obtaining high quality heart and lung sounds enables clinicians to accurately assess a newborns cardio-respiratory health and provide timely care. However, noisy chest sound recordings are common, hindering timely and accurate assessment. A new Non-negative Matrix Co-Factorisation based approach is proposed to separate noisy chest sound recordings into heart, lung and noise components to address this problem. This method is achieved through training with 20 high quality heart and lung sounds, in parallel with separating the sounds of the noisy recording. The method was tested on 68 10-second noisy recordings containing both heart and lung sounds and compared to the current state of the art Non-negative Matrix Factorisation methods. Results show significant improvements in heart and lung sound quality scores respectively, and improved accuracy of 3.6bpm and 1.2bpm in heart and breathing rate estimation respectively, when compared to existing methods.

Use of Telemedicine for subspecialty support in the NICU setting

The regionalization of neonatal care was implemented with an overarching goal to improve neonatal outcomes.¹ This led to centralized neonatal care in urban settings that jeopardized the sustainability of the community level 2 and level 3 Neonatal Intensive Care Units (NICU) in medically underserved areas.² Coupled with pediatric subspecialist and allied health professional workforce shortages, regionalization resulted in disparate and limited access to subspecialty care.^3-6 Innovative telemedicine technologies may offer an alternative and powerful care model for infants in geographically isolated and underserved areas. This chapter describes how telemedicine offerings of remote pediatric subspecialty and specialized programs may bridge gaps of access to specialized care and maintain the clinical services in community NICUs.

Neonatal Heart and Lung Sound Quality Assessment for Robust Heart and Breathing Rate Estimation for Telehealth Applications

With advances in digital stethoscopes, internet of things, signal processing and machine learning, chest sounds can be easily collected and transmitted to the cloud for remote monitoring and diagnosis. However, low quality of recordings complicates remote monitoring and diagnosis, particularly for neonatal care. This paper proposes a new method to objectively and automatically assess the signal quality to improve the accuracy and reliability of heart rate (HR) and breathing rate (BR) estimation from noisy neonatal chest sounds. A total of 88 10-second long chest sounds were taken from 76 preterm and full-term babies. Six annotators independently assessed the signal quality, number of detectable beats, and breathing periods from these recordings. For quality classification, 187 and 182 features were extracted from heart and lung sounds, respectively. After feature selection, class balancing, and hyperparameter optimization, a dynamic binary classification model was trained. Then HR and BR were automatically estimated from the chest sound and several approaches were compared.The results of subject-wise leave-one-out cross-validation, showed that the model distinguished high and low quality recordings in the test set with 96% specificity, 81% sensitivity and 93% accuracy for heart sounds, and 86% specificity, 69% sensitivity and 82% accuracy for lung sounds. The HR and BR estimated from high quality sounds resulted in significantly less median absolute error (4 bpm and 12 bpm difference, respectively) compared to those from low quality sounds. The methods presented in this work, facilitates automated neonatal chest sound auscultation for future telehealth applications.