Monitoring respiratory rates with a wearable system using a stretchable strain sensor during moderate exercise

Prospective observational study of 2 wearable strain sensors for measuring the respiratory rate

The respiratory rate is an important factor for assessing patient status and detecting changes in the severity of illness. Real-time determination of the respiratory rate will enable early responses to changes in the patient condition. Several methods of wearable devices have enabled remote respiratory rate monitoring. However, gaps persist in large-scale validation, patient-specific calibration, standardization and their usefulness in clinical practice has not been fully elucidated. The aim of this study was to evaluate the accuracy of 2 wearable stretch sensors, C-STRECH® which is used in clinical practice and a novel stretchable capacitor in measuring the respiratory rate. The respiratory rate of 20 healthy subjects was measured by a spirometer with the stretch sensor applied to 1 of 5 locations (umbilicus, lateral abdomen, epigastrium, lateral chest, or chest) of their body at rest while they were in a sitting or supine position before or after exercise. The sensors detected the largest amplitudes at the epigastrium and umbilicus compared to other sites of measurement for the sitting and supine positions, respectively. At rest, the respiratory rate of the sensors had an error of 0.06 to 2.39 breaths/minute, whereas after exercise, an error of 1.57 to 3.72 breaths/minute was observed compared to the spirometer. The sensors were able to detect the respiratory rate of healthy volunteers in the sitting and supine positions, but there was a need for improvement in detection after exercise.

SolunumWear: A smart textile system for dynamic respiration monitoring across various postures

We introduce SolunumWear, a multi-sensory e-textile system designed for respiration in daily life settings, addressing the gap in continuous, real-world respiration event monitoring. Leveraging a textile pressure sensor belt to capture chest movements and a wireless data acquisition system, SolunumWear offers a promising solution for both medical and wellness applications. The system's efficacy was evaluated through a human study involving 10 healthy adults (six female and four male) across various breathing rates and postures, demonstrating a strong correlation (R value = 0.836) with the gold-standard system. The study highlights the system's computational and communication efficiencies, with latencies of approximately 4.84 s and 2.13 ms, respectively. These findings highlight the efficacy of SolunumWear as a wireless, wearable technology for respiration monitoring in daily settings. This research contributes to the expanding body of knowledge on smart textile-based health monitoring technologies, demonstrating its potential to provide reliable respiratory data in real-world environments.

RespirAnalyzer: an R package for analyzing data from continuous monitoring of respiratory signals

Motivation

The analysis of data obtained from continuous monitoring of respiratory signals (CMRS) holds significant importance in improving patient care, optimizing sports performance, and advancing scientific understanding in the field of respiratory health.

Results

The R package RespirAnalyzer provides an analytic tool specifically for feature extraction, fractal and complexity analysis for CMRS data. The package covers a wide and comprehensive range of data analysis methods including obtaining inter-breath intervals (IBI) series, plotting time series, obtaining summary statistics of IBI series, conducting power spectral density, multifractal detrended fluctuation analysis (MFDFA) and multiscale sample entropy analysis, fitting the MFDFA results with the extended binomial multifractal model, displaying results using various plots, etc. This package has been developed from our work in directly analyzing CMRS data and is anticipated to assist fellow researchers in computing the related features of their CMRS data, enabling them to delve into the clinical significance inherent in these features.

Availability and implementation

The package for Windows is available from both Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/RespirAnalyzer/index.html and GitHub: https://github.com/dongxinzheng/RespirAnalyzer.

Poisson-Nernst-Planck framework for modelling ionic strain and temperature sensors

Ionically conductive hydrogels are gaining traction as sensing and structural materials for use bioelectronic devices. Hydrogels that feature large mechanical compliances and tractable ionic conductivities are compelling materials that can sense physiological states and potentially modulate the stimulation of excitable tissue because of the congruence in electro-mechanical properties across the tissue-material interface. However, interfacing ionic hydrogels with conventional DC voltage-based circuits poses several technical challenges including electrode delamination, electrochemical reaction, and drifting contact impedance. Utilizing alternating voltages to probe ion-relaxation dynamics has been shown to be a viable alternative for strain and temperature sensing. In this work, we present a Poisson-Nernst-Planck theoretical framework to model ion transport under alternating fields within conductors subject to varying strains and temperatures. Using simulated impedance spectra, we develop key insights about the relationship between frequency of the applied voltage perturbation and sensitivity. Lastly, we perform preliminary experimental characterization to demonstrate the applicability of the proposed theory. We believe this work provides a useful perspective that is applicable to the design of a variety of ionic hydrogel-based sensors for biomedical and soft robotic applications.

Ultrasensitive Strain Sensor Utilizing a AgF-AgNW Hybrid Nanocomposite for Breath Monitoring and Pulmonary Function Analysis

Breath monitoring and pulmonary function analysis have been the prime focus of wearable smart sensors owing to the COVID-19 outbreak. Currently used lung function meters in hospitals are prone to spread the virus and can result in the transmission of the disease. Herein, we have reported the first-ever wearable patch-type strain sensor for enabling real-time lung function measurements (such as forced volume capacity (FVC) and forced expiratory volume (FEV) along with breath monitoring), which can avoid the spread of the virus. The noninvasive and highly sensitive strain sensor utilizes the synergistic effect of two-dimensional (2D) silver flakes (AgFs) and one-dimensional (1D) silver nanowires (AgNWs), where AgFs create multiple electron transmission paths and AgNWs generate percolation networks in the nanocomposite. The nanocomposite-based strain sensor possesses a high optimized conductivity of 7721 Sm^-1 (and a maximum conductivity of 83,836 Sm^-1), excellent stretchability (>1000%), and ultrasensitivity (GFs of 35 and 87 when stretched 0-20 and 20-50%, respectively), thus enabling reliable detection of small strains produced by the body during breathing and other motions. The sensor patching site was optimized to accurately discriminate between normal breathing, quick breathing, and deep breathing and analyze numerous pulmonary functions, including the respiratory rate, peak flow, FVC, and FEV. Finally, the observed measurements for different pulmonary functions were compared with a commercial peak flow meter and a spirometer, and a high correlation was observed, which highlights the practical feasibility of continuous respiratory monitoring and pulmonary function analysis.

Simultaneous Biomechanical and Biochemical Monitoring for Self-Powered Breath Analysis

The high moisture level of exhaled gases unavoidably limits the sensitivity of breath analysis via wearable bioelectronics. Inspired by pulmonary lobe expansion/contraction observed during respiration, a respiration-driven triboelectric sensor (RTS) was devised for simultaneous respiratory biomechanical monitoring and exhaled acetone concentration analysis. A tin oxide-doped polyethyleneimine membrane was devised to play a dual role as both a triboelectric layer and an acetone sensing material. The prepared RTS exhibited excellent ability in measuring respiratory flow rate (2-8 L/min) and breath frequency (0.33-0.8 Hz). Furthermore, the RTS presented good performance in biochemical acetone sensing (2-10 ppm range at high moisture levels), which was validated via finite element analysis. This work has led to the development of a novel real-time active respiratory monitoring system and strengthened triboelectric-chemisorption coupling sensing mechanism.

Respiratory Monitoring by Ultrafast Humidity Sensors with Nanomaterials: A Review

Respiratory monitoring is a fundamental method to understand the physiological and psychological relationships between respiration and the human body. In this review, we overview recent developments on ultrafast humidity sensors with functional nanomaterials for monitoring human respiration. Key advances in design and materials have resulted in humidity sensors with response and recovery times reaching 8 ms. In addition, these sensors are particularly beneficial for respiratory monitoring by being portable and noninvasive. We systematically classify the reported sensors according to four types of output signals: impedance, light, frequency, and voltage. Design strategies for preparing ultrafast humidity sensors using nanomaterials are discussed with regard to physical parameters such as the nanomaterial film thickness, porosity, and hydrophilicity. We also summarize other applications that require ultrafast humidity sensors for physiological studies. This review provides key guidelines and directions for preparing and applying such sensors in practical applications.

Validity of a novel respiratory rate monitor comprising stretchable strain sensors during a 6-min walking test in patients with chronic pulmonary obstructive disease

BACKGROUND

Breathing frequency is rarely measured during a field walking test since the current monitoring system using a face mask is cumbersome for older adults. For effective clinical application, we aimed to validate the new respiratory monitor using wearable strain sensors during a 6-min walk test (6MWT) in young adults and patients with chronic obstructive pulmonary disease (COPD).

METHODS

The study included young adults and patients with stable COPD voluntarily recruited from three hospitals. Breathing frequency during 6MWT were measured by the strain sensor and a nasal capnometer. Total breathing frequencies were measured by the capnometer. The Bland-Altman method was used to estimate the mean limit of agreement for breathing frequency.

RESULTS

A total of 23 young adults (age = 23.1 ± 3.7, mean ± SD) and 50 patients with COPD (age = 75.2 ± 7.2, %FEV1 = 59.1 ± 19.7) were analyzed. During the entire test period, the total breathing frequencies were measured based on an average of 252 ± 46 breaths, and the total breathing frequency was higher in patients with COPD than in young adults (mean difference = -3.349, p < 0.0013). The mean difference in breathing frequency between the strain sensors and capnometer was -0.28 (95%CI: 0.75 to 0.20), and the limit of agreement ranged from -4.1 to 3.6. The CI of the limit of agreement included the limit of equivalence (4 counts/min).

CONCLUSIONS

The novel respiratory monitor with wearable sensors achieved the target accuracy in both young adults and patients with COPD in the 6MWT.

Video based non-contact monitoring of respiratory rate and chest indrawing in children with pneumonia

OBJECTIVE

Pneumonia is the single largest cause of death in children worldwide due to infectious diseases. According to WHO guidelines, fast breathing and chest indrawing are the key indicators of pneumonia in children requiring antibiotic treatments. The aim of this study was to develop a video-based novel method for simultaneous monitoring of respiratory rate and chest indrawing without upsetting babies.

APPROACH

Respiratory signals, corresponding to periodic movements of chest-abdominal walls during breathing, were extracted by analyzing RGB (red, green, blue) components in video frames captured by a smartphone camera. Respiratory rate was then obtained by applying fast fourier transform on the de-noised respiratory signal. Chest indrawing was detected by analysing relative phases of regional chest-abdominal wall mobility. The performance of the developed algorithm was evaluated on both healthy and pneumonia children.

MAIN RESULTS

The proposed method can measure respiratory rate with an overall mean absolute error of 1.8 bpm in the range 18-105 bpm. Phase difference between regional chest wall movements in the chest indrawing (pneumonia) cases was found to be 143±23.9 degrees, which was significantly higher than that in the healthy cases 52.3 ±32.6 degrees (p<0.001).

SIGNIFICANCE

Being non-intrusive and non-subjective, this computer-aided method can be useful in the monitoring for respiratory rate and chest indrawing for the diagnosis of pneumonia and its severity in children.

The Rise of Wearable Devices during the COVID-19 Pandemic: A Systematic Review

The COVID-19 pandemic has wreaked havoc globally and still persists even after a year of its initial outbreak. Several reasons can be considered: people are in close contact with each other, i.e., at a short range (1 m), and the healthcare system is not sufficiently developed or does not have enough facilities to manage and fight the pandemic, even in developed countries such as the USA and the U.K. and countries in Europe. There is a great need in healthcare for remote monitoring of COVID-19 symptoms. In the past year, a number of IoT-based devices and wearables have been introduced by researchers, providing good results in terms of high accuracy in diagnosing patients in the prodromal phase and in monitoring the symptoms of patients, i.e., respiratory rate, heart rate, temperature, etc. In this systematic review, we analyzed these wearables and their need in the healthcare system. The research was conducted using three databases: IEEE Xplore®, Web of Science®, and PubMed Central®, between December 2019 and June 2021. This article was based on the PRISMA guidelines. Initially, 1100 articles were identified while searching the scientific literature regarding this topic. After screening, ultimately, 70 articles were fully evaluated and included in this review. These articles were divided into two categories. The first one belongs to the on-body sensors (wearables), their types and positions, and the use of AI technology with ehealth wearables in different scenarios from screening to contact tracing. In the second category, we discuss the problems and solutions with respect to utilizing these wearables globally. This systematic review provides an extensive overview of wearable systems for the remote management and automated assessment of COVID-19, taking into account the reliability and acceptability of the implemented technologies.

A novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor

Objective evaluations of cough frequency are considered important for assessing the clinical state of patients with respiratory diseases. However, cough monitors with audio recordings are rarely used in clinical settings. Issues regarding privacy and background noise with audio recordings are barriers to the wide use of these monitors; to solve these problems, we developed a novel automatic cough frequency monitoring system combining a triaxial accelerator and a stretchable strain sensor. Eleven healthy adult volunteers and 10 adult patients with cough were enrolled. The participants wore two devices for 30 min for the cough measurements. An accelerator was attached to the epigastric region, and a stretchable strain sensor was worn around their neck. When the subjects coughed, these devices displayed specific waveforms. The data from all the participants were categorized into a training dataset and a test dataset. Using a variational autoencoder, a machine learning algorithm with deep learning, the components of the test dataset were automatically judged as being a “cough unit” or “non-cough unit”. The sensitivity and specificity in detecting coughs were 92% and 96%, respectively. Our cough monitoring system has the potential to be widely used in clinical settings without any concerns regarding privacy or background noise.

Wearable Sensing and Telehealth Technology with Potential Applications in the Coronavirus Pandemic

Coronavirus disease 2019 (COVID-19) has emerged as a pandemic with serious clinical manifestations including death. A pandemic at the large-scale like COVID-19 places extraordinary demands on the world's health systems, dramatically devastates vulnerable populations, and critically threatens the global communities in an unprecedented way. While tremendous efforts at the frontline are placed on detecting the virus, providing treatments and developing vaccines, it is also critically important to examine the technologies and systems for tackling disease emergence, arresting its spread and especially the strategy for diseases prevention. The objective of this article is to review enabling technologies and systems with various application scenarios for handling the COVID-19 crisis. The article will focus specifically on 1) wearable devices suitable for monitoring the populations at risk and those in quarantine, both for evaluating the health status of caregivers and management personnel, and for facilitating triage processes for admission to hospitals; 2) unobtrusive sensing systems for detecting the disease and for monitoring patients with relatively mild symptoms whose clinical situation could suddenly worsen in improvised hospitals; and 3) telehealth technologies for the remote monitoring and diagnosis of COVID-19 and related diseases. Finally, further challenges and opportunities for future directions of development are highlighted.

Clinical Evaluation of Respiratory Rate Measurements on COPD (Male) Patients Using Wearable Inkjet-Printed Sensor

Introduction: Chronic Obstructive Pulmonary Disease (COPD) is a progressive disease that causes long-term breathing problems. The reliable monitoring of respiratory rate (RR) is very important for the treatment and management of COPD. Based on inkjet printing technology, we have developed a stretchable and wearable sensor that can accurately measure RR on normal subjects. Currently, there is a lack of comprehensive evaluation of stretchable sensors in the monitoring of RR on COPD patients. We aimed to investigate the measurement accuracy of our sensor on COPD patients. Methodology: Thirty-five patients (Mean ± SD of age: 55.25 ± 13.76 years) in different stages of COPD were recruited. The measurement accuracy of our inkjet-printed (IJPT) sensor was evaluated at different body postures (i.e., standing, sitting at 90°, and lying at 45°) on COPD patients. The RR recorded by the IJPT sensor was compared with that recorded by the reference e-Health sensor using paired T-test and Wilcoxon signed-rank test. Analysis of variation (ANOVA) was performed to investigate if there was any significant effect of individual difference or posture on the measurement error. Statistical significance was defined as p-value less than 0.05. Results: There was no significant difference between the RR measurements collected by the IJPT sensor and the e-Health reference sensor overall and in three postures (p > 0.05 in paired T-tests and Wilcoxon signed-rank tests). The sitting posture had the least measurement error of −0.0542 ± 1.451 bpm. There was no significant effect of posture or individual difference on the measurement error or relative measurement error (p > 0.05 in ANOVA). Conclusion: The IJPT sensor can accurately measure the RR of COPD patients at different body postures, which provides the possibility for reliable monitoring of RR on COPD patients.

Breath-Jockey: Development and Feasibility Assessment of a Wearable System for Respiratory Rate and Kinematic Parameter Estimation for Gallop Athletes

In recent years, wearable devices for physiological parameter monitoring in sports and physical activities have been gaining momentum. In particular, some studies have focused their attention on using available commercial monitoring systems mainly on horses during training sessions or competitions. Only a few studies have focused on the jockey's physiological and kinematic parameters. Although at a glance, it seems jockeys do not make a lot of effort during riding, it is quite the opposite. Indeed, especially during competitions, they profuse a short but high intensity effort. To this extend, we propose a wearable system integrating conductive textiles and an M-IMU to simultaneously monitor the respiratory rate (RR) and kinematic parameters of the riding activity. Firstly, we tested the developed wearable system on a healthy volunteer mimicking the typical riding movements of jockeys and compared the performances with a reference instrument. Lastly, we tested the system on two gallop jockeys during the "137∘ Derby Italiano di Galoppo". The proposed system is able to track both the RR and the kinematic parameters during the various phases of the competition both at rest and during the race.

Applying Nanomaterials to Modern Biomedical Electrochemical Detection of Metabolites, Electrolytes, and Pathogens

Personal biosensors and bioelectronics have been demonstrated for use in out-of-clinic biomedical devices. Such modern devices have the potential to transform traditional clinical analysis into a new approach, allowing patients or users to screen their own health or warning of diseases. Researchers aim to explore the opportunities of easy-to-wear and easy-to-carry sensors that would empower users to detect biomarkers, electrolytes, or pathogens at home in a rapid and easy way. This mobility would open the door for early diagnosis and personalized healthcare management to a wide audience. In this review, we focus on the recent progress made in modern electrochemical sensors, which holds promising potential to support point-of-care technologies. Key original research articles covered in this review are mainly experimental reports published from 2018 to 2020. Strategies for the detection of metabolites, ions, and viruses are updated in this article. The relevant challenges and opportunities of applying nanomaterials to support the fabrication of new electrochemical biosensors are also discussed. Finally, perspectives regarding potential benefits and current challenges of the technology are included. The growing area of personal biosensors is expected to push their application closer to a new phase of biomedical advancement.

Recent Progress in Flexible Wearable Sensors for Vital Sign Monitoring

With the development of flexible electronic materials, as well as the wide development and application of smartphones, the cloud, and wireless systems, flexible wearable sensor technology has a significant and far-reaching impact on the realization of personalized medical care and the reform of the consumer market in the future. However, due to the high requirements for accuracy, reliability, low power consumption, and less data error, the development of these potential areas is full of challenges. In order to solve these problems, this review mainly searches the literature from 2008 to May 2020, based on the PRISMA process. Based on them, this paper reviews the latest research progress of new flexible materials and different types of sensors for monitoring vital signs (including electrophysiological signals, body temperature, and respiratory frequency) in recent years. These materials and sensors can help realize accurate signal detection based on comfortable and sustainable observation, and may likely be applied to future daily clothing.

Stretchable respiration sensors: Advanced designs and multifunctional platforms for wearable physiological monitoring

Respiration signals are a vital sign of life. Monitoring human breath provides critical information for health assessment, diagnosis, and treatment for respiratory diseases such as asthma, chronic bronchitis, and emphysema. Stretchable and wearable respiration sensors have recently attracted considerable interest toward monitoring physiological signals in the era of real time and portable healthcare systems. This review provides a snapshot on the recent development of stretchable sensors and wearable technologies for respiration monitoring. The article offers the fundamental guideline on the sensing mechanisms and design concepts of stretchable sensors for detecting vital breath signals such as temperature, humidity, airflow, stress and strain. A highlight on the recent progress in the integration of variable sensing components outlines feasible pathways towards multifunctional and multimodal sensor platforms. Structural designs of nanomaterials and platforms for stretchable respiration sensors are reviewed.