Smart Vest for Respiratory Rate Monitoring of COPD Patients Based on Non-Contact Capacitive Sensing

Detrended fluctuation analysis of day and night breathing parameters from a wearable respiratory holter

BACKGROUND AND OBJECTIVE

This study focuses on the application of Detrended Fluctuation Analysis (DFA) to understand the variability and correlation properties of respiratory parameters time series obtained by means of a wearable.

METHODS

Data from 18 healthy volunteers collected using the Airgo™ band, which provides signals proportional to thoracic circumference at a sampling frequency of 10 Hz. The primary aim was to provide preliminary normative data for DFA scaling factors.

RESULTS

DFA was applied to 6-h recordings, revealing significant differences (p < 0.001) in scaling factors (α values) for tidal volume (night: 0.97 [0.09], day: 0.88 [0.04]), minute ventilation (night: 1.02 [0.10], day: 0.91 [0.07), mean inspiratory flow (night: 0.98 [0.06], day: 0.88 [0.06]), mean expiratory flow (night: 0.89 [0.08], day: 0.81 [0.06]), and duty cycle (night: 0.64 [0.04], day: 0.59 [0.03]). Quadratic detrending highlighted additional differences not captured with linear detrending, particularly in inspiratory and expiratory time. These findings suggest distinct regulatory patterns during sleep.

CONCLUSIONS

DFA analysis of respiratory parameters obtained from wearable devices reveals distinct regulatory patterns between day and night conditions, particularly in parameters related to tidal volume and ventilation. These findings demonstrate the potential of DFA to uncover physiological differences in respiratory control mechanisms, especially during sleep, despite technical limitations such as the strong dependency of DFA scaling factors on sampling frequency, duration, and detrending order. Future research should address the limitations of sample size and expand normative datasets to include individuals with respiratory conditions, to translate this methodology into specific clinical applications.

Low compression smart clothing for respiratory rate monitoring using a bending angle sensor based on double-layer capacitance

In chronic respiratory diseases, continuous self-monitoring of vital signs such as respiratory rate aids in the early detection of exacerbations. In recent years, the development of smart clothing, such as garments equipped with sensors to measure respiratory rate, has been a focus of research. However, the usability and adoption of smart clothing are often compromised owing to the discomfort caused by compression pressure during wear. This study developed smart clothing designed to measure respiratory rate using a low compression pressure. This was achieved by integrating a bending angle sensor, based on double-layer capacitance, into the rib cage and abdomen areas. The accuracy of the respiratory rate measurement was evaluated in 20 healthy male subjects without respiratory diseases. Breathing was measured while the subjects wore the smart clothing and performed breathing exercises in sitting, supine, and lateral postures, following a metronome set between 12 and 30 bpm. To assess accuracy, the respiratory rate measured by the smart clothing was compared with that measured by a spirometer. The recorded compression pressure was 0.77 ± 0.21 kPa, with no subjects reporting discomfort. Correlation coefficients for respiratory rate in the different postures ranged within 0.97-0.99. The mean difference between the smart clothing and spirometer measurements was less than 0.1 bpm. The low mean difference indicated that the proposed low compression pressure wearable respiration sensor, employing a bending angle sensor based on double-layer capacitance, could measure respiratory rate accurately without causing discomfort and within an acceptable error range.

Wearable devices for patient monitoring in the intensive care unit

Wearable devices (WDs), originally launched for fitness, are now increasingly recognized as valuable technologies in several clinical applications, including the intensive care unit (ICU). These devices allow for continuous, non-invasive monitoring of physiological parameters such as heart rate, respiratory rate, blood pressure, glucose levels, and posture and movement. WDs offer significant advantages in making monitoring less invasive and could help bridge gaps between ICUs and standard hospital wards, ensuring more effective transitioning to lower-level monitoring after discharge from the ICU. WDs are also promising tools in applications like delirium detection, vital signs monitoring in limited resource settings, and prevention of hospital-acquired pressure injuries. Despite the potential of WDs, challenges such as measurement accuracy, explainability of data processing algorithms, and actual integration into the clinical decision-making process persist. Further research is necessary to validate the effectiveness of WDs and to integrate them into clinical practice in critical care environments.Take home messages Wearable devices are revolutionizing patient monitoring in ICUs and step down units by providing continuous, non-invasive, and cost-effective solutions. Validation of their accuracy and integration in the clinical decision-making process remain crucial for widespread clinical adoption.

Industry 4.0-Compliant Occupational Chronic Obstructive Pulmonary Disease Prevention: Literature Review and Future Directions

Chronic obstructive pulmonary disease (COPD) is among prevalent occupational diseases, causing early retirement and disabilities. This paper looks into occupational-related COPD prevention and intervention in the workplace for Industry 4.0-compliant occupation health and safety management. The economic burden and other severe problems caused by COPD are introduced. Subsequently, seminal research in relevant areas is reviewed. The prospects and challenges are introduced and discussed based on critical management approaches. An initial design of an Industry 4.0-compliant occupational COPD prevention system is presented at the end.

A Review of Patient Bed Sensors for Monitoring of Vital Signs

The analysis of biomedical signals is a very challenging task. This review paper is focused on the presentation of various methods where biomedical data, in particular vital signs, could be monitored using sensors mounted to beds. The presented methods to monitor vital signs include those combined with optical fibers, camera systems, pressure sensors, or other sensors, which may provide more efficient patient bed monitoring results. This work also covers the aspects of interference occurrence in the above-mentioned signals and sleep quality monitoring, which play a very important role in the analysis of biomedical signals and the choice of appropriate signal-processing methods. The provided information will help various researchers to understand the importance of vital sign monitoring and will be a thorough and up-to-date summary of these methods. It will also be a foundation for further enhancement of these methods.

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.

Continuous Monitoring of Heart Rate Variability and Respiration for the Remote Diagnosis of Chronic Obstructive Pulmonary Disease: Prospective Observational Study

BACKGROUND

Conventional daytime monitoring in a single day may be influenced by factors such as motion artifacts and emotions, and continuous monitoring of nighttime heart rate variability (HRV) and respiration to assist in chronic obstructive pulmonary disease (COPD) diagnosis has not been reported yet.

OBJECTIVE

The aim of this study was to explore and compare the effects of continuously monitored HRV, heart rate (HR), and respiration during night sleep on the remote diagnosis of COPD.

METHODS

We recruited patients with different severities of COPD and healthy controls between January 2021 and November 2022. Vital signs such as HRV, HR, and respiration were recorded using noncontact bed sensors from 10 PM to 8 AM of the following day, and the recordings of each patient lasted for at least 30 days. We obtained statistical means of HRV, HR, and respiration over time periods of 7, 14, and 30 days by continuous monitoring. Additionally, the effects that the statistical means of HRV, HR, and respiration had on COPD diagnosis were evaluated at different times of recordings.

RESULTS

In this study, 146 individuals were enrolled: 37 patients with COPD in the case group and 109 participants in the control group. The median number of continuous night-sleep monitoring days per person was 56.5 (IQR 32.0-113.0) days. Using the features regarding the statistical means of HRV, HR, and respiration over 1, 7, 14, and 30 days, binary logistic regression classification of COPD yielded an accuracy, Youden index, and area under the receiver operating characteristic curve of 0.958, 0.904, and 0.989, respectively. The classification performance for COPD diagnosis was directionally proportional to the monitoring duration of vital signs at night. The importance of the features for diagnosis was determined by the statistical means of respiration, HRV, and HR, which followed the order of respiration > HRV > HR. Specifically, the statistical means of the duration of respiration rate faster than 21 times/min (RRF), high frequency band power of 0.15-0.40 Hz (HF), and respiration rate (RR) were identified as the top 3 most significant features for classification, corresponding to cutoff values of 0.1 minute, 1316.3 nU, and 16.3 times/min, respectively.

CONCLUSIONS

Continuous monitoring of nocturnal vital signs has significant potential for the remote diagnosis of COPD. As the duration of night-sleep monitoring increased from 1 to 30 days, the statistical means of HRV, HR, and respiration showed a better reflection of an individual's health condition compared to monitoring the vital signs in a single day or night, and better was the classification performance for COPD diagnosis. Further, the statistical means of RRF, HF, and RR are crucial features for diagnosing COPD, demonstrating the importance of monitoring HRV and respiration during night sleep.

Mucus Structure, Viscoelastic Properties, and Composition in Chronic Respiratory Diseases

The respiratory mucus, a viscoelastic gel, effectuates a primary line of the airway defense when operated by the mucociliary clearance. In chronic respiratory diseases (CRDs), such as asthma, chronic obstructive pulmonary disease (COPD), and cystic fibrosis (CF), the mucus is overproduced and its solid content augments, changing its structure and viscoelastic properties and determining a derangement of essential defense mechanisms against opportunistic microbial (virus and bacteria) pathogens. This ensues in damaging of the airways, leading to a vicious cycle of obstruction and infection responsible for the harsh clinical evolution of these CRDs. Here, we review the essential features of normal and pathological mucus (i.e., sputum in CF, COPD, and asthma), i.e., mucin content, structure (mesh size), micro/macro-rheology, pH, and osmotic pressure, ending with the awareness that sputum biomarkers (mucins, inflammatory proteins and peptides, and metabolites) might serve to indicate acute exacerbation and response to therapies. There are some indications that old and novel treatments may change the structure, viscoelastic properties, and biomarker content of sputum; however, a wealth of work is still needed to embrace these measures as correlates of disease severity in association with (or even as substitutes of) pulmonary functional tests.

An IMU-Based Wearable System for Respiratory Rate Estimation in Static and Dynamic Conditions

PURPOSE

Breathing parameters change with activity and posture, but currently available solutions can perform measurements only during static conditions.

METHODS

This article presents an innovative wearable sensor system constituted by three inertial measurement units to simultaneously estimate respiratory rate (RR) in static and dynamic conditions and perform human activity recognition (HAR) with the same sensing principle. Two units are aimed at detecting chest wall breathing-related movements (one on the thorax, one on the abdomen); the third is on the lower back. All units compute the quaternions describing the subject's movement and send data continuously with the ANT transmission protocol to an app. The 20 healthy subjects involved in the research (9 men, 11 women) were between 23 and 54 years old, with mean age 26.8, mean height 172.5 cm and mean weight 66.9 kg. Data from these subjects during different postures or activities were collected and analyzed to extract RR.

RESULTS

Statistically significant differences between dynamic activities ("walking slow", "walking fast", "running" and "cycling") and static postures were detected (p < 0.05), confirming the obtained measurements are in line with physiology even during dynamic activities. Data from the reference unit only and from all three units were used as inputs to artificial intelligence methods for HAR. When the data from the reference unit were used, the Gated Recurrent Unit was the best performing method (97% accuracy). With three units, a 1D Convolutional Neural Network was the best performing (99% accuracy).

CONCLUSION

Overall, the proposed solution shows it is possible to perform simultaneous HAR and RR measurements in static and dynamic conditions with the same sensor system.

Wearable Health Devices for Diagnosis Support: Evolution and Future Tendencies

The use of wearable devices has increased substantially in recent years. This, together with the rise of telemedicine, has led to the use of these types of devices in the healthcare field. In this work, we carried out a detailed study on the use of these devices (regarding the general trends); we analyzed the research works and devices marketed in the last 10 years. This analysis extracted relevant information on the general trend of use, as well as more specific aspects, such as the use of sensors, communication technologies, and diseases. A comparison was made between the commercial and research aspects linked to wearables in the healthcare field, and upcoming trends were analyzed.

Smart home healthcare for chronic disease management: A scoping review

Objective

Chronic disease is the leading cause of morbidity and mortality on a global scale. Recent use of intelligent home environments for remote health monitoring has allowed patients to feel safe at home. By encouraging patient engagement and, if necessary, care delivery, smart home environments may be a useful method for managing chronic diseases at home. The purpose of this study is to synthesize the evidence on the usage of smart healthcare in the home for chronic illness management.

Methods

We conducted a scoping review using the Joanna Briggs Methodology and searched three databases from 2017 to 2022 for original research papers on smart healthcare, smart home technology, home-based technology, home monitoring, and physiological monitoring for chronic illness management. We did a descriptive study on the pertinent data we collected, as well as an analysis of whether the devices met its objectives.

Results

The final analysis included nine papers, the majority of which were randomized controlled trials. All of the studies were carried out in developed countries. The gadgets or smart healthcare in these studies are categorized based on the technology used and the outcomes measured. Respiratory, weight, and ballistocardiograph measurements, as well as changes in questionnaire ratings, hospitalization, activity monitoring, device acceptability, medication adherence, exercise capacity, and body function, were all measured.

Conclusion

Smart healthcare applications boost health by monitoring health and wellness, recording physical activity and rehabilitation, and improving overall quality of life. Not all smart home applications, however, served their intended purpose. As a result, more research into the efficacy of smart healthcare is needed to improve its application for chronic illness treatment.

Preliminary Assessment of a Flexible Multi-Sensor Wearable System Based on Fiber Bragg Gratings for Respiratory Monitoring of Hemiplegic Patients

Respiratory diseases are common in post-stroke hemiplegic patients and represent a major social problem as they worsen the quality of life and reduce the life span. As a consequence, being able to monitor respiratory parameters such as the respiratory rate (RR) and assess the presence of respiratory asynchronies could be of paramount importance to define hemiplegics' health status. Moreover, RR is a useful parameter to investigate the level of fatigue and distress that these patients undergo during rehabilitation processes. Although motion capture systems and flowmeters are the leading instruments for respiratory pattern evaluation, smart wearable systems are gaining ever more acceptance since they allow continuous monitoring by detecting chest wall breathing displacements, ensuring reduced costs and no need for dedicated spaces. Among other sensing technologies, fiber Bragg grating (FBG) sensors have emerged thanks to their high sensitivity to strain, lightness, and multiplexing capability. In this work, a wearable system composed of four flexible dumbbell-shaped sensing modules is proposed for respiratory monitoring in hemiplegic patients. The system is light and easy to wear and can be adapted to any anthropometry thanks to the modular anchoring system. Its feasibility assessment in RR evaluation was performed on seven hemiplegic volunteers in eupnea and tachypnea breathing conditions. In addition, an explorative investigation was conducted to assess the system's ability to detect asynchronies between torso compartments. The good results suggest that this device could be a useful instrument to support clinicians and operators in hemiplegic patients' management.

Mapping the global research landscape and hotspot of exercise therapy and chronic obstructive pulmonary disease: A bibliometric study based on the web of science database from 2011 to 2020

Background: The application of exercise therapy (ET) in chronic obstructive pulmonary disease (COPD) is generating increasing clinical efficacy and social-economic value. In this study, research trends, evolutionary processes and hot topics in this field are detailed, as well as predictions of future development directions.

Methods: Search for literature in the field of COPD and ET and analyze data to generate knowledge graphs using VOSiewer and CiteSpace software. The time frame for the search was from 2011 to January 2021. Then we extracted full-text key information (such as title, journal category, publication date, author, country and institution, abstract, and keyword) and obtained the co-citation analysis. Use hierarchal clustering analysis software developed by VOSviewer to map common citations, and use Citespace software to plot trend networks.

Results: The United States topped the list with 27.91% of the number of articles posted, followed by the UK at 25.44%. Imperial College London was the highest number of article publications in institutions, followed by Maastricht University and the University of Toronto. The Royal Brompton Harefield NHS Foundation Trust was one of many research institutions and currently holds the highest average citations per item (ACI) value, followed by Imperial College London and the University of Leuven. Judging from the number of publications related to ET and COPD, it is mainly published in cell biology, respiratory pulmonary diseases, and rehabilitation experiments study medicine. The European Respiration Journal is the most widely published in this field, followed by the International Journal of Chronic Obstructive Pulmonary Disease and Respiratory Medicine.

Conclusion: COPD combined with ET is widely used in clinical practice and is on the rise. A distinctive feature of the field is multidisciplinary integration. Rehabilitation research for COPD involves multidisciplinary collaboration, tissue engineering, and molecular biology mechanism studies to help patients remodel healthy breathing. Multidisciplinary rehabilitation measures provide a solid foundation for advancing clinical efficacy in the field of COPD.

The impact of medical cyber–physical systems on healthcare service delivery

Purpose

The pandemic has reinforced the need for revamping the healthcare service delivery systems around the world to meet the increased challenges of modern-day illnesses. The use of medical cyber–physical system (MCPS) in the healthcare is one of the means of transforming the landscape of the traditional healthcare service delivery system. The purpose of this study is to critically examine the impact of MCPS on the quality of healthcare service delivery.

Design/methodology/approach

This paper uses an evidence-based approach, the authors have conducted a systematic literature review to study the impact of MCPS on healthcare service delivery. Fifty-four articles were thematically examined to study the impact of MCPS on eight characteristics of the healthcare service delivery proposed by the world health organisation.

Findings

The study proposes support that MCPS will positively impact (1) comprehensiveness, (2) accessibility, (3) coverage, (4) continuity, (5) quality, (6) person-centredness, (7) coordination, (8) accountability and (9) efficiency dimension of the healthcare service delivery. The study further draws nine propositions to support the impact of MCPS on the healthcare service delivery.

Practical implications

This study can be used by stakeholders as a guide point while using MCPS in healthcare service delivery systems. Besides, healthcare managers can use this study to understand the performance of their healthcare system. This study can further be used for designing effective strategies for deploying MCPS to be effective and efficient in each of the dimensions of healthcare service delivery.

Originality/value

The previous studies have focussed on technology aspects of MCPS and none of them critically analysed the impact on healthcare service delivery. This is the first literature review carried out to understand the impact of MCPS on the nine dimensions of healthcare service delivery proposed by WHO. This study provides improved thematic awareness of the resulting body of knowledge, allowing the field of MCPS and healthcare service delivery to progress in a more informed and multidisciplinary manner.

A Sensor-Based mHealth Platform for Remote Monitoring and Intervention of Frailty Patients at Home

Frailty syndrome is an independent risk factor for serious health episodes, disability, hospitalization, falls, loss of mobility, and cardiovascular disease. Its high reversibility demands personalized interventions among which exercise programs are highly efficient to contribute to its delay. Information technology-based solutions to support frailty have been recently approached, but most of them are focused on assessment and not on intervention. This paper describes a sensor-based mHealth platform integrated in a service-based architecture inside the FRAIL project towards the remote monitoring and intervention of pre-frail and frail patients at home. The aim of this platform is constituting an efficient and scalable system for reducing both the impact of aging and the advance of frailty syndrome. Among the results of this work are: (1) the development of elderly-focused sensors and platform; (2) a technical validation process of the sensor devices and the mHealth platform with young adults; and (3) an assessment of usability and acceptability of the devices with a set of pre-frail and frail patients. After the promising results obtained, future steps of this work involve performing a clinical validation in order to quantify the impact of the platform on health outcomes of frail patients.

Sensors for Context-Aware Smart Healthcare: A Security Perspective

The advances in the miniaturisation of electronic devices and the deployment of cheaper and faster data networks have propelled environments augmented with contextual and real-time information, such as smart homes and smart cities. These context-aware environments have opened the door to numerous opportunities for providing added-value, accurate and personalised services to citizens. In particular, smart healthcare, regarded as the natural evolution of electronic health and mobile health, contributes to enhance medical services and people's welfare, while shortening waiting times and decreasing healthcare expenditure. However, the large number, variety and complexity of devices and systems involved in smart health systems involve a number of challenging considerations to be considered, particularly from security and privacy perspectives. To this aim, this article provides a thorough technical review on the deployment of secure smart health services, ranging from the very collection of sensors data (either related to the medical conditions of individuals or to their immediate context), the transmission of these data through wireless communication networks, to the final storage and analysis of such information in the appropriate health information systems. As a result, we provide practitioners with a comprehensive overview of the existing vulnerabilities and solutions in the technical side of smart healthcare.

Non-Invasive Respiratory Assessment in Duchenne Muscular Dystrophy: From Clinical Research to Outcome Measures

Ventilatory failure, due to the progressive wasting of respiratory muscles, is the main cause of death in patients with Duchenne muscular dystrophy (DMD). Reliable measures of lung function and respiratory muscle action are important to monitor disease progression, to identify early signs of ventilatory insufficiency and to plan individual respiratory management. Moreover, the current development of novel gene-modifying and pharmacological therapies highlighted the urgent need of respiratory outcomes to quantify the effects of these therapies. Pulmonary function tests represent the standard of care for lung function evaluation in DMD, but provide a global evaluation of respiratory involvement, which results from the interaction between different respiratory muscles. Currently, research studies have focused on finding novel outcome measures able to describe the behavior of individual respiratory muscles. This review overviews the measures currently identified in clinical research to follow the progressive respiratory decline in patients with DMD, from a global assessment to an individual structure–function muscle characterization. We aim to discuss their strengths and limitations, in relation to their current development and suitability as outcome measures for use in a clinical setting and as in upcoming drug trials in DMD.

Role of new digital technologies and telemedicine in pulmonary rehabilitation : Smart devices in the treatment of chronic respiratory diseases

BACKGROUND

Asthma and chronic obstructive pulmonary diseases are conditions characterized by a variable progression. Some individuals experience longer asymptomatic periods while others acute worsening periods and/or exacerbations triggered by symptom multiplication factors. Medications are adjusted to the patients' respiratory function, self-assessment of health and emerging certain physical changes. A more effective treatment may be applied by real-time data registered during the patient's everyday life.

AIM AND METHODS

Introducing new modern digital technology in pulmonary rehabilitation (PR) to help tracking the patients' medication, thus we systematically reviewed the latest publications on telemedicine and pulmonary telerehabilitation.

CONCLUSION

The use of the latest digital technologies in PR is very exciting and offers great opportunities while treating patients affected by specific conditions. On the one hand, adherence to medication can be improved in patients with chronic respiratory diseases by using these new state of the art devices; on the other hand, digital devices will also be able to monitor various physiological parameters of patients during their usual everyday activities. Data can be stored on a smartphone and shared with the provider. Relying on this information, physicians will be able to tailor medications and dosage to the specific needs of individual patients. Telerehabilitation may be a sustainable solution to the growing burden of chronic respiratory disease worldwide. However, PR must keep its cornerstones, such as education and motivations, which are most successful when conducted in person. Many issues remain to be resolved in the future, e.g. cybersecurity while using smart devices since they offer unique opportunities for PR.

Integration of Internet of Things with Quantum Dots: A State-of-the-art of Medicine

Internet of Things (IoT) emerges as disruptive innovation and development in the fields of drug delivery and biomedical sciences using on-target active transportation, sensors, wearable devices, real-time diagnostics, etc. Semiconducting fluorescence emitting material, quantum dots on integration with IoT displayed interesting results in the healthcare sector, especially in hospitals and pathological laboratories. Presently, the integrated system is used to improve productivity without the interference of human and offer a cost-effective system. This integrated system can be used for the detection of various diseases like epilepsy, cancer, diabetes, etc., and various biomedical applications like energy storage, lights, sensor technology, light filters, etc. The integrated technology is implemented into the field of medicine for simplifying the approaches in therapeutics and diagnostic applications. The collected and analyzed data are further useful for healthcare professionals to find patient-centric solutions. Artificial Intelligence-aided IoT emerges as a novel technology for transmitting and securing health data. Despite some of the limitations like e-waste and the risk of hacking, an IoT-based QD system will be considered as a modern healthcare provider with life-saving products for enriching the medical quality and real-time accessibility.

Respiration Monitoring via Forcecardiography Sensors

In the last few decades, a number of wearable systems for respiration monitoring that help to significantly reduce patients’ discomfort and improve the reliability of measurements have been presented. A recent research trend in biosignal acquisition is focusing on the development of monolithic sensors for monitoring multiple vital signs, which could improve the simultaneous recording of different physiological data. This study presents a performance analysis of respiration monitoring performed via forcecardiography (FCG) sensors, as compared to ECG-derived respiration (EDR) and electroresistive respiration band (ERB), which was assumed as the reference. FCG is a novel technique that records the cardiac-induced vibrations of the chest wall via specific force sensors, which provide seismocardiogram-like information, along with a novel component that seems to be related to the ventricular volume variations. Simultaneous acquisitions were obtained from seven healthy subjects at rest, during both quiet breathing and forced respiration at higher and lower rates. The raw FCG sensor signals featured a large, low-frequency, respiratory component (R-FCG), in addition to the common FCG signal. Statistical analyses of R-FCG, EDR and ERB signals showed that FCG sensors ensure a more sensitive and precise detection of respiratory acts than EDR (sensitivity: 100% vs. 95.8%, positive predictive value: 98.9% vs. 92.5%), as well as a superior accuracy and precision in interbreath interval measurement (linear regression slopes and intercepts: 0.99, 0.026 s (R² = 0.98) vs. 0.98, 0.11 s (R² = 0.88), Bland–Altman limits of agreement: ±0.61 s vs. ±1.5 s). This study represents a first proof of concept for the simultaneous recording of respiration signals and forcecardiograms with a single, local, small, unobtrusive, cheap sensor. This would extend the scope of FCG to monitoring multiple vital signs, as well as to the analysis of cardiorespiratory interactions, also paving the way for the continuous, long-term monitoring of patients with heart and pulmonary diseases.

Internet of Things and Robotics in Transforming Current-Day Healthcare Services

Technology has become an integral part of everyday lives. Recent years have witnessed advancement in technology with a wide range of applications in healthcare. However, the use of the Internet of Things (IoT) and robotics are yet to see substantial growth in terms of its acceptability in healthcare applications. The current study has discussed the role of the aforesaid technology in transforming healthcare services. The study also presented various functionalities of the ideal IoT-aided robotic systems and their importance in healthcare applications. Furthermore, the study focused on the application of the IoT and robotics in providing healthcare services such as rehabilitation, assistive surgery, elderly care, and prosthetics. Recent developments, current status, limitations, and challenges in the aforesaid area have been presented in detail. The study also discusses the role and applications of the aforementioned technology in managing the current pandemic of COVID-19. A comprehensive knowledge has been provided on the prospect of the functionality, application, challenges, and future scope of the IoT-aided robotic system in healthcare services. This will help the future researcher to make an inclusive idea on the use of the said technology in improving the healthcare services in the future.

A Home Telemedicine System for Continuous Respiratory Monitoring

This article presents a continuous home telemonitoring system for chronic respiratory patients using 5G connectivity developed in partnership with Vodafone as a part of the 5G Trial in Milan established by the Italian Ministry of Economic Development. The system features a wearable respiratory and activity monitor, an environmental sensor and a pulse oximeter sending the data through a 5G router to a Multi-Edge Computing server, incorporated in the Vodafone 5G infrastructure, where they are stored and accessible for visualization. In particular, activity, respiratory and environmental data are continuously streamed and collected. The solution has been tested on 18 healthy volunteers during non-supervised recordings lasting at least 48 hours. The combination of recognized activities and associated respiratory parameters provided statistically significant variations in breathing patterns between one activity and the other, thus giving more complete information to the clinicians than previously studied telemedicine systems based on spot-checks. In particular, statistically significant differences are found in tidal volume and minute ventilation between horizontal and vertical postures (p < 0.001) and between vertical postures and dynamic activities (p < 0.001); the respiratory rate shows statistically significant differences between horizontal and vertical postures (p < 0.001). Some environmental parameters have different mean values between day and night, such as carbon dioxide (p < 0.001). Trials on patients are needed to further study this telemedicine solution and make it commercially available in the future. The main further technical development suggested is the use of commercial 5G smartphones as routers, in order to make the system usable outside of home settings.

Furniture-Integrated Respiration Sensors by Notched Transmission Lines

Non-invasive respiration sensors integrated into furniture can be invisible to the user and greatly enhance comfort and convenience to facilitate many applications. Current sensors often require user cooperation or fitting, which discourages frequent usage. We present a new respiration sensor integrated into a bed or a chair by modifying a radio-frequency (RF) coaxial cable structure with a designed notch. The lung motion is coupled to the electromagnetic leakage at the notch through near-field coherent sensing (NCS). The sensors, covered with fabrics and positioned under the abdomen and thorax, can capture the respiratory waveforms and derive the breath rate. The heart rate can also be evaluated in the same setup with proper filtering. The sensor design can tolerate large position variation to accommodate user uncertainties. Various voluntary exercises of normal, deep, fast, held and blocked breathing were measured under different postures of supine, recumbent and sitting by the carrier frequency range between 900MHz and 2.4GHz. The breath rate from 10 participants compare well with the synchronous commercial chest-belt sensors in all breathing routines.

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.

Sputum and salivary protein biomarkers and point-of-care biosensors for the management of COPD

Chronic obstructive pulmonary disease (COPD) has become one of the most fatal diseases of the century considering mortality and morbidity levels worldwide. This disease is an inflammatory response to environmental stress and tobacco smoking. Although spirometry is the gold-standard diagnostic test administrated in primary and secondary care, it often exhibits low accuracy in cases of predicting disease worsening and possible bias due to the operator, patient, and conditions. Recent developments in proteomics research suggest that the presence of protein biomarkers can aid in the accurate diagnosis and prediction of disease outcomes. This review presents the cutting-edge research progress in the area of protein biomarkers towards the management of COPD. The literature review was confined to protein biomarkers in saliva and sputum because testing these bodily fluids shows great promise for point-of-care (POC) testing due to its practicality, non-invasiveness and inexpensive handling and sampling. Although it is conclusive that more studies on sputum and saliva are needed, this review studies the promising clinical value of interleukin (IL)-6 and IL-8, matrix metalloproteinase (MMP)-8 and MMP-9, C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-α), and neutrophil elastase (NE). Following the critical analysis of salivary and sputum biomarkers, the recent development of POC biosensors for the multiplexed detection of biomarkers is also reported. Overall, the review aims to explore the possibility for the future development of POC sensors for chronic lung disease management utilizing clinically relevant biomarkers in saliva and sputum.

The Importance of Respiratory Rate Monitoring: From Healthcare to Sport and Exercise

Respiratory rate is a fundamental vital sign that is sensitive to different pathological conditions (e.g., adverse cardiac events, pneumonia, and clinical deterioration) and stressors, including emotional stress, cognitive load, heat, cold, physical effort, and exercise-induced fatigue. The sensitivity of respiratory rate to these conditions is superior compared to that of most of the other vital signs, and the abundance of suitable technological solutions measuring respiratory rate has important implications for healthcare, occupational settings, and sport. However, respiratory rate is still too often not routinely monitored in these fields of use. This review presents a multidisciplinary approach to respiratory monitoring, with the aim to improve the development and efficacy of respiratory monitoring services. We have identified thirteen monitoring goals where the use of the respiratory rate is invaluable, and for each of them we have described suitable sensors and techniques to monitor respiratory rate in specific measurement scenarios. We have also provided a physiological rationale corroborating the importance of respiratory rate monitoring and an original multidisciplinary framework for the development of respiratory monitoring services. This review is expected to advance the field of respiratory monitoring and favor synergies between different disciplines to accomplish this goal.

Wearable Sensors for Monitoring and Preventing Noncommunicable Diseases: A Systematic Review

Ensuring healthy lives and promoting a healthy well-being for all at all ages are listed as some of the goals in Agenda 2030 for Sustainable Development. Considering that noncommunicable diseases (NCDs) are the leading cause of death worldwide, reducing the mortality of NCDs is an important target. To reach this goal, means for detecting and reacting to warning signals are necessary. Here, remote health monitoring in real time has great potential. This article provides a systematic review of the use of wearable sensors for the monitoring and prevention of NCDs. In addition, this article not only provides in-depth information about the retrieved articles, but also discusses examples of studies assessing warning signals that may result in serious health conditions, such as stroke and cardiac arrest, if left untreated. One finding is that even though many good examples of wearable sensor systems for monitoring and controlling NCDs are presented, many issues also remain to be solved. One major issue is the lack of testing on representative people from a sociodemographic perspective. Even though substantial work remains, the use of wearable sensor systems has a great potential to be used in the battle against NCDs by providing the means to diagnose, monitor and prevent NCDs.

A Wearable Device for Breathing Frequency Monitoring: A Pilot Study on Patients with Muscular Dystrophy

Patients at risk of developing respiratory dysfunctions, such as patients with severe forms of muscular dystrophy, need a careful respiratory assessment, and periodic follow-up visits to monitor the progression of the disease. In these patients, at-home continuous monitoring of respiratory activity patterns could provide additional understanding about disease progression, allowing prompt clinical intervention. The core aim of the present study is thus to investigate the feasibility of using an innovative wearable device for respiratory monitoring, particularly breathing frequency variation assessment, in patients with muscular dystrophy. A comparison of measurements of breathing frequency with gold standard methods showed that the device based on the inertial measurement units (IMU-based device) provided optimal results in terms of accuracy errors, correlation, and agreement. Participants positively evaluated the device for ease of use, comfort, usability, and wearability. Moreover, preliminary results confirmed that breathing frequency is a valuable breathing parameter to monitor, at the clinic and at home, because it strongly correlates with the main indexes of respiratory function.

Comparison between the Airgo™ Device and a Metabolic Cart during Rest and Exercise

The aim of this study is to compare the accuracy of Airgo™, a non-invasive wearable device that records breath, with respect to a gold standard. In 21 healthy subjects (10 males, 11 females), four parameters were recorded for four min at rest and in different positions simultaneously by Airgo™ and SensorMedics 2900 metabolic cart. Then, a cardio-pulmonary exercise test was performed using the Erg 800S cycle ergometer in order to test Airgo™'s accuracy during physical effort. The results reveal that the relative error median percentage of respiratory rate was of 0% for all positions at rest and for different exercise intensities, with interquartile ranges between 3.5 (standing position) and 22.4 (low-intensity exercise) breaths per minute. During exercise, normalized amplitude and ventilation relative error medians highlighted the presence of an error proportional to the volume to be estimated. For increasing intensity levels of exercise, Airgo™'s estimate tended to underestimate the values of the gold standard instrument. In conclusion, the Airgo™ device provides good accuracy and precision in the estimate of respiratory rate (especially at rest), an acceptable estimate of tidal volume and minute ventilation at rest and an underestimation for increasing volumes.

Smart Shirts for Monitoring Physiological Parameters: Scoping Review

BACKGROUND

The recent trends of technological innovation and widescale digitization as potential solutions to challenges in health care, sports, and emergency service operations have led to the conception of smart textile technology. In health care, these smart textile systems present the potential to aid preventative medicine and early diagnosis through continuous, noninvasive tracking of physical and mental health while promoting proactive involvement of patients in their medical management. In areas such as sports and emergency response, the potential to provide comprehensive and simultaneous physiological insights across multiple body systems is promising. However, it is currently unclear what type of evidence exists surrounding the use of smart textiles for the monitoring of physiological outcome measures across different settings.

OBJECTIVE

This scoping review aimed to systematically survey the existing body of scientific literature surrounding smart textiles in their most prevalent form, the smart shirt, for monitoring physiological outcome measures.

METHODS

A total of 5 electronic bibliographic databases were systematically searched (Ovid Medical Literature Analysis and Retrieval System Online, Excerpta Medica database, Scopus, Cumulative Index to Nursing and Allied Health Literature, and SPORTDiscus). Publications from the inception of the database to June 24, 2019 were reviewed. Nonindexed literature relevant to this review was also systematically searched. The results were then collated, summarized, and reported.

RESULTS

Following the removal of duplicates, 7871 citations were identified. On the basis of title and abstract screening, 7632 citations were excluded, whereas 239 were retrieved and assessed for eligibility. Of these, 101 citations were included in the final analysis. Included studies were categorized into four themes: (1) prototype design, (2) validation, (3) observational, and (4) reviews. Among the 101 analyzed studies, prototype design was the most prevalent theme (50/101, 49.5%), followed by validation (29/101, 28.7%), observational studies (21/101, 20.8%), and reviews (1/101, 0.1%). Presented prototype designs ranged from those capable of monitoring one physiological metric to those capable of monitoring several simultaneously. In 29 validation studies, 16 distinct smart shirts were validated against reference technology under various conditions and work rates, including rest, submaximal exercise, and maximal exercise. The identified observational studies used smart shirts in clinical, healthy, and occupational populations for aims such as early diagnosis and stress detection. One scoping review was identified, investigating the use of smart shirts for electrocardiograph signal monitoring in cardiac patients.

CONCLUSIONS

Although smart shirts have been found to be valid and reliable in the monitoring of specific physiological metrics, results were variable for others, demonstrating the need for further systematic validation. Analysis of the results has also demonstrated gaps in knowledge, such as a considerable lag of validation and observational studies in comparison with prototype design and limited investigation using smart shirts in pediatric, elite sports, and emergency service populations.

A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis

The use of wearable body sensors for health monitoring is a quickly growing field with the potential of offering a reliable means for clinical and remote health management. This includes both real-time monitoring and health trend monitoring with the aim to detect/predict health deterioration and also to act as a prevention tool. The aim of this systematic review was to provide a qualitative synthesis of studies using wearable body sensors for health monitoring. The synthesis and analysis have pointed out a number of shortcomings in prior research. Major shortcomings are demonstrated by the majority of the studies adopting an observational research design, too small sample sizes, poorly presented, and/or non-representative participant demographics (i.e., age, gender, patient/healthy). These aspects need to be considered in future research work.

Human Vital Signs Detection Methods and Potential Using Radars: A Review

Continuous monitoring of vital signs, such as respiration and heartbeat, plays a crucial role in early detection and even prediction of conditions that may affect the wellbeing of the patient. Sensing vital signs can be categorized into: contact-based techniques and contactless based techniques. Conventional clinical methods of detecting these vital signs require the use of contact sensors, which may not be practical for long duration monitoring and less convenient for repeatable measurements. On the other hand, wireless vital signs detection using radars has the distinct advantage of not requiring the attachment of electrodes to the subject's body and hence not constraining the movement of the person and eliminating the possibility of skin irritation. In addition, it removes the need for wires and limitation of access to patients, especially for children and the elderly. This paper presents a thorough review on the traditional methods of monitoring cardio-pulmonary rates as well as the potential of replacing these systems with radar-based techniques. The paper also highlights the challenges that radar-based vital signs monitoring methods need to overcome to gain acceptance in the healthcare field. A proof-of-concept of a radar-based vital sign detection system is presented together with promising measurement results.

A System for Monitoring Breathing Activity Using an Ultrasonic Radar Detection with Low Power Consumption

Continuous monitoring of breathing activity plays a major role in detecting and classifying a breathing abnormality. This work aims to facilitate detection of abnormal breathing syndromes, including tachypnea, bradypnea, central apnea, and irregular breathing by tracking of thorax movement resulting from respiratory rhythms based on ultrasonic radar detection. This paper proposes a non-contact, non-invasive, low cost, low power consumption, portable, and precise system for simultaneous monitoring of normal and abnormal breathing activity in real-time using an ultrasonic PING sensor and microcontroller PIC18F452. Moreover, the obtained abnormal breathing syndrome is reported to the concerned physician’s mobile telephone through a global system for mobile communication (GSM) modem to handle the case depending on the patient’s emergency condition. In addition, the power consumption of the proposed monitoring system is reduced via a duty cycle using an energy-efficient sleep/wake scheme. Experiments were conducted on 12 participants without any physical contact at different distances of 0.5, 1, 2, and 3 m and the breathing rates measured with the proposed system were then compared with those measured by a piezo respiratory belt transducer. The experimental results illustrate the feasibility of the proposed system to extract breathing rate and detect the related abnormal breathing syndromes with a high degree of agreement, strong correlation coefficient, and low error ratio. The results also showed that the total current consumption of the proposed monitoring system based on the sleep/wake scheme was 6.936 mA compared to 321.75 mA when the traditional operation was used instead. Consequently, this led to a 97.8% of power savings and extended the battery life time from 8 h to approximately 370 h. The proposed monitoring system could be used in both clinical and home settings.

Contact-Based Methods for Measuring Respiratory Rate

There is an ever-growing demand for measuring respiratory variables during a variety of applications, including monitoring in clinical and occupational settings, and during sporting activities and exercise. Special attention is devoted to the monitoring of respiratory rate because it is a vital sign, which responds to a variety of stressors. There are different methods for measuring respiratory rate, which can be classed as contact-based or contactless. The present paper provides an overview of the currently available contact-based methods for measuring respiratory rate. For these methods, the sensing element (or part of the instrument containing it) is attached to the subject's body. Methods based upon the recording of respiratory airflow, sounds, air temperature, air humidity, air components, chest wall movements, and modulation of the cardiac activity are presented. Working principles, metrological characteristics, and applications in the respiratory monitoring field are presented to explore potential development and applicability for each method.