Telehealth program for symptomatic COVID-19 patients in Mindanao, Philippines: a whole-of-system, pragmatic interventional study on patient monitoring from isolation facilities to community reintegration.

The COVID-19 pandemic is impacting individuals and society's physical and mental health. Despite the lack of any definite and effective therapeutic regimen, public health measures such as quarantine and isolation have been instituted to contain this pandemic. However, these mitigating measures have also raised issues regarding isolated patients' mental and psychological well-being. Several stakeholders were engaged in this approach, including the university, the local health office, the tertiary hospital, and the local communities. This intervention addresses concerns regarding the health status of isolated individuals due to COVID-19 infection, making the program available to anyone who agrees to participate. This was done through telehealth services delivered via phone calls and SMS. The university provided technical support and telehealth manpower through medical students. The local health unit manages the isolation facilities, while the referral hospital offers specialty care for isolated patients through teleconsultation. Finally, the local community is the one that reintegrates discharged patients into their communities. Three hundred forty-four (344) participants were provided seven sessions on telehealth education and tracking of their COVID-19 prescribed practices and mental health. The mean age of the patients was 37 years; half were females, and 15% had comorbidities. Regarding their mental health status, the level of depression dropped from 6% to 1% (p<0.0001), the level of anxiety dropped from 12% to 2% (p<0.0001), and the level of stress dropped from 3% to 0% (p<0.0001) from the first day of admission to 2 weeks after discharge. Moreover, a general trend of statistically significant increase in various practices was noted: wearing face masks, physical distancing, disinfecting frequently held objects, hand hygiene, and self-monitoring for COVID-19 symptoms. Those with progressing symptoms of COVID-19 were referred immediately to the referral hospital. There were also no reports of complications of co-morbidities during their stay in the isolation facilities or social isolation upon community reintegration. The study concludes that telehealth services have the potential to address many challenges in providing continuous healthcare services to isolated patients until they are reintegrated into their community. Furthermore, a whole-of-society approach is necessary to provide holistic care to patients affected by the pandemic.

The Management of Pediatric Asthma Using Telehealth: An Integrative Review.

Introduction: Asthma is one of the most chronic noncommunicable diseases of childhood, affecting 1 in 12 children in the United States. The use of telemedicine for the management of pediatric asthma has shown improved health outcomes; however, it is important to understand what can impact its acceptance. The purpose of this review was to identify the facilitators and barriers to pediatric asthma management, as viewed by stakeholders. Methods: An electronic literature search was performed using PubMed, Scopus, and Cumulative Index to Nursing and Allied Health Literature Complete. Articles included in the review contained perceptions of the use of telemedicine for the management of pediatric asthma, as viewed by stakeholders. The socioecological model was used as the theoretical framework to extract data based on its five levels. Results: After reviewing full texts of 143 articles, 118 were excluded, leaving 25 articles included in this review. A majority of included articles focused on mobile health (m-Health) studies for the management of pediatric asthma, with the remaining articles studying synchronous telemedicine or a combination of modalities. Common themes were identified; however, most were focused on the use of m-Health and few studies contained the viewpoints of the caregiver, children, or providers regarding synchronous telemedicine. Discussion: This integrative review identified a number of facilitators and barriers for the management of asthma using telemedicine. However, more qualitative studies are needed to evaluate the perceptions of caregivers, patients, and primary providers regarding synchronous telehealth. It was also recognized that telemedicine may increase instead of reduce health care disparities.

Improving obstetric and perinatal outcomes with a remote patient monitoring program for hypertension in a large integrated care system.

OBJECTIVE: To determine the effect of a remote patient monitoring program for hypertension (RPM HTN) in patients diagnosed with hypertensive disorders of pregnancy. STUDY DESIGN: We used a matched retrospective cohort design to evaluate differences in obstetric and perinatal outcomes using data from electronic medical records. Patients enrolled in RPM HTN between November 1, 2019, and October 31, 2021, who delivered a pregnancy at ≥20 weeks gestation were compared to a cohort of patients matched by age, race, HTN and diabetes status, who delivered in the 48-month period before implementation of RPM HTN. RESULTS: 1030 patients were enrolled in RPM HTN and 937 were matched to historical controls. Five hundred and seventeen (50.2 %) were enrolled in the antepartum period and 513 (49.8 %) were enrolled postpartum. Patients in the RPM HTN cohort were more likely to have a post-hospital discharge blood pressure (BP) measured within the first 20 days after delivery (RR 1.56, 95 % CI: 1.47-1.65: p < 0.01) and were more likely to have that BP be normal (RR 1.43, 95 % CI: 1.31-1.55: p = 0.05). They were also more likely to be taking antihypertensives postpartum (RR 1.27, 95 % CI: 1.15-1.40; p < 0.01) and to be evaluated by an obstetric clinician within 20 days of delivery (RR 1.50, 95 % CI 1.42-1.58; p < 0.01). CONCLUSIONS: A remote HTN monitoring program for 937 obstetric patients was associated with improved BP monitoring, better postpartum BP control, and improved linkages to clinician care after delivery, when compared to historical controls.

Soli-enabled noncontact heart rate detection for sleep and meditation tracking.

Heart rate (HR) is a crucial physiological signal that can be used to monitor health and fitness. Traditional methods for measuring HR require wearable devices, which can be inconvenient or uncomfortable, especially during sleep and meditation. Noncontact HR detection methods employing microwave radar can be a promising alternative. However, the existing approaches in the literature usually use high-gain antennas and require the sensor to face the user's chest or back, making them difficult to integrate into a portable device and unsuitable for sleep and meditation tracking applications. This study presents a novel approach for noncontact HR detection using a miniaturized Soli radar chip embedded in a portable device (Google Nest Hub). The chip has a [Formula: see text] dimension and can be easily integrated into various devices. The proposed approach utilizes advanced signal processing and machine learning techniques to extract HRs from radar signals. The approach is validated on a sleep dataset (62 users, 498 h) and a meditation dataset (114 users, 1131 min). The approach achieves a mean absolute error (MAE) of 1.69 bpm and a mean absolute percentage error (MAPE) of [Formula: see text] on the sleep dataset. On the meditation dataset, the approach achieves an MAE of 1.05 bpm and a MAPE of [Formula: see text]. The recall rates for the two datasets are [Formula: see text] and [Formula: see text], respectively. This study represents the first application of the noncontact HR detection technology to sleep and meditation tracking, offering a promising alternative to wearable devices for HR monitoring during sleep and meditation.

Towards A Framework for Implementing Remote Patient Monitoring From an Integrated Care Perspective: A Scoping Review.

BACKGROUND: Remote patient monitoring (RPM) has been increasingly adopted over the last decade, with the COVID-19 pandemic fostering its rapid development. As RPM implementation is recognised as complex and highly demanding in terms of resources and processes, there are multiple challenges in providing RPM in an integrated logic. METHODS: To examine the structural elements that are relevant for implementing RPM integrated care, a scoping review was conducted in PubMed, Scopus, and Web of Science, leveraging a search strategy that combines terms relative to (1) conceptual models and reallife initiatives; (2) RPM; and (3) care integration. RESULTS: 28 articles were included, covering nine conceptual models and 19 real-life initiatives. Eighteen structural elements of RPM integrated care implementation were identified among conceptual models, defining a structure for assessing real-life initiatives. 78.9% of those initiatives referred to at least ten structural elements, with patient education and self-monitoring promotion, multidisciplinary core workforce, ICTs (information and communications technologies) and telemonitoring devices, and health indicators measurement being present in all studies, and therefore being core elements to the design of RPM initiatives. CONCLUSION: RPM goes far beyond technology, with underlying processes and involved actors playing a central role in care provision. The structural elements identified can guide RPM implementation and promote maturity in adoption. Future research may focus on assessing design completeness, evaluating impacts, and analysing related financial arrangements.

A wireless physiological parameter monitoring system with a treatment feedback function during neonatal phototherapy.

Objective. Neonatal jaundice is a common condition in the early stages of newborns, and phototherapy is a fast, safe and effective method that is used to treat it. However, recent studies have shown that phototherapy may elicit side effects in infants, such as hypothermia, hyperthermia and dehydration. To improve the quality of phototherapy and the prognosis of patients, the changes in neonatal physiological parameters during phototherapy should be monitored to give better feedback to pediatricians or the phototherapy system. However, the current standard of clinical care during neonatal phototherapy with hard-wired devices limits this realization.Approach. Here, we developed a prototype of a neonatal wearable device, which can wirelessly potentially monitor the jaundice value, transepidermal water loss, skin wettedness factor and body orientation during phototherapy, and conducted prototype validation experiments. We also set up user-friendly interfaces and an analysis system on custom software, all designed to make the future addition of data interfaces for treatment feedback functions easier.Main results. The preliminaryin vitroexperiment demonstrated the effectiveness of simultaneous monitoring of the required physiological parameters. And further suggestions and specific operations are discussed in terms of optimization of the treatment of neonatal jaundice.Significance. It is believed that the established system has the potential to provide a basis for future phototherapy nursing guidelines and physiological monitoring standards.

Review of Best Practices for Patient Monitoring to Improve the Effectiveness of Therapy in Pediatric Hospitals.

Context: Significant differences exist in the needs of an adult patient and those of a sick child with members of his or her family involved. Monitoring questionnaires of patients and their family members can show ways to improve medical care and develop methods for effective staff behavior. The Consumer Assessment System for Healthcare Service Providers and Systems (CAHPS) helps hospitals, using management data, to identify strengths and weaknesses, determine what needs improvement, and track progress over time. Objective: The study intended to identify the most effective methods for monitoring patients and their families in pediatric hospitals, which can lead to the achievement of high-level medical care. Design: The research team performed a narrative review by searching the Agency for Healthcare Research and Quality, PubMed Central, and the National Library of Medicine databases for scientific studies and reports from researchers who have used the innovations from CAHPS in their practices. The search used the keywords children and hospital, improving the quality of service, coordination of care, and medical care. Setting: The study took place in the Department of Pediatric Hematology, Oncology and Transplantation at the Medical University of Lublin in Lublin, Poland. Outcome Measures: The research team analyzed the selected studies to find specific, applicable, and successful monitoring methodology. Results: The study examined many important aspects of the stay of children in a hospital and of the difficulties that young patients and their families face and identified the most effective monitoring methods for various areas that affect the interests of a child and his or her family within the walls of the hospital. Conclusions: This review provides direction for medical institutions, allowing the possibility of improving the quality of patient monitoring. Researchers have carried out few studies in pediatric hospitals today, and the field needs further study.

A grounded theory study of alarm fatigue among nurses in intensive care units.

OBJECTIVES: The aim of this study was to explore the process of how nurses experienced and dealt with alarm fatigue in intensive care units based on Iranian nurses' perceptions and experiences. BACKGROUND: Alarm fatigue is the overstimulation of senses due to the constant ringing of alarms in intensive care units. It is associated with nurses' desensitization to critical alarms that can directly influence patient safety and quality of care. METHODS: A qualitative exploratory study using the grounded theory approach by Strauss and Corbin was carried out. Participants were 20 nurses working in intensive care units. The sampling process was started purposively and continued theoretically. Data were collected using semi-structured, in-depth, and individual interviews and continued to data saturation. The constant comparative analysis approach was used consisting of the following steps: open coding, developing concepts, analysing the context, entering the process into data analysis, integrating categories. FINDINGS: The participants' main concern in the exposure to alarm fatigue was 'threat to personal balance'. The core category in this research was 'trying to create a holistic balance', which reflected a set of strategies that the nurses consistently and continuously used to deal with alarm fatigue and consisted of four main categories as follows: 'smart care', 'deliberate balancing', 'conditional prioritisation', and 'negligent performance'. Threat to personal balance was strengthened by 'inappropriate circuit of individual roles', 'distortion of the organisational structure', and 'insecurity of the infrastructure'. The consequences of this process was harm to the patient, burnout among nurse, and damage to the healthcare organisation. CONCLUSIONS: The research findings have practical implications for healthcare management, policymaking, nursing education, research, and clinical practice. Mitigating staff shortages, improving staff competencies, enhancing nurses' authority for responding to alarms, modifying care routines, improving the physical environment, and removing problems related to alarm equipment can prevent alarm fatigue and its unappropriated consequences.

Physiological biomarker monitoring during arduous military training: Maintaining readiness and performance.

OBJECTIVES: Physiological and psychological stressors can degrade soldiers' readiness and performance during military training and operational environments. Integrative and holistic assessments of biomarkers across diverse human performance optimization domains during multistressor training can be leveraged to provide actionable insight to military leadership regarding service member health and readiness. DESIGN/METHOD: A broad categorization of biomarkers, to include biochemical measures, bone and body composition, psychometric assessments, movement screening, and physiological load can be incorporated into robust analytical pipelines for understanding the complex factors that impact military human performance. RESULTS: In this perspective commentary we overview the rationale, selection, and methodologies for monitoring biomarker domains that are relevant to military research and specifically highlight methods that have been incorporated in a research program funded by the Office of Naval Research, Code 34 Biological and Physiological Monitoring and Modeling of Warfighter Performance. CONCLUSIONS: The integration of screening and continuous monitoring methodologies via robust analytical approaches will provide novel insight for military leaders regarding health, performance, and readiness outcomes during multistressor military training.

An EMG-based Eating Behaviour Monitoring system with haptic feedback to promote mindful eating.

Mindless eating, or the lack of awareness of the food we are consuming, has been linked to health problems attributed to unhealthy eating behaviour, including obesity. Traditional approaches used to moderate eating behaviour often rely on inaccurate self-logging, manual observations or bulky equipment. Overall, there is a clear unmet clinical need to develop an intelligent and lightweight system which can automatically monitor eating behaviour and provide feedback. In this paper, we investigate: i) the development of an automated system for detecting eating behaviour using wearable Electromyography (EMG) sensors, and ii) the application of the proposed system combined with real-time wristband haptic feedback to facilitate mindful eating. For this, the collected data from 16 participants were used to develop an algorithm for detecting chewing and swallowing. We extracted 18 features from EMG which were presented to different classifiers, to develop a system enabling participants to self-moderate their chewing behaviour using haptic feedback. An additional experimental study was conducted with 20 further participants to evaluate the effectiveness of eating monitoring and haptic interface in promoting mindful eating. We used a standard validation scheme with a leave-one-participant-out to assess model performance using standard metrics (F1-score). The proposed algorithm automatically assessed eating behaviour accurately using the EMG-extracted features and a Support Vector Machine (SVM): F1-Score = 0.95 for chewing classification, and F1-Score = 0.87 for swallowing classification. The experimental study showed that participants exhibited a lower rate of chewing when haptic feedback was delivered in the form of wristband vibration, compared to a baseline and non-haptic condition (F (2,38) = 58.243, p < .001). These findings may have major implications for research in eating behaviour, providing key insights into the impact of automatic chewing detection and haptic feedback systems on moderating eating behaviour towards improving health outcomes.

The Kaiser Permanente Northern California Advance Alert Monitor Program: An Automated Early Warning System for Adults at Risk for In-Hospital Clinical Deterioration.

BACKGROUND: In-hospital deterioration among ward patients is associated with substantially increased adverse outcome rates. In 2013 Kaiser Permanente Northern California (KPNC) developed and implemented a predictive analytics-driven program, Advance Alert Monitor (AAM), to improve early detection and intervention for in-hospital deterioration. The AAM predictive model is designed to give clinicians 12 hours of lead time before clinical deterioration, permitting early detection and a patient goals-concordant response to prevent worsening. DESIGN OF THE AAM INTERVENTION: Across the 21 hospitals of the KPNC integrated health care delivery system, AAM analyzes electronic health record (EHR) data for patients in medical/surgical and telemetry units 24 hours a day, 7 days a week. Patients identified as high risk by the AAM algorithm trigger an alert for a regional team of experienced critical care virtual quality nurse consultants (VQNCs), who then cascade validated, actionable information to rapid response team (RRT) nurses at local hospitals. RRT nurses conduct bedside assessments of at-risk patients and formulate interdisciplinary clinical responses with hospital-based physicians, bedside nurses, and supportive care teams to ensure a well-defined escalation plan that includes clarification of the patients' goals of care. SUCCESS OF THE INTERVENTION: Since 2019 the AAM program has been implemented at all 21 KPNC hospitals. The use of predictive modeling embedded within the EHR to identify high-risk patients has produced the standardization of monitoring workflows, clinical rescue protocols, and coordination to ensure that care is consistent with patients' individual goals of care. An evaluation of the program, using a staggered deployment sequence over 19 hospitals, demonstrates that the AAM program is associated with statistically significant decreases in mortality (9.8% vs. 14.4%), hospital length of stay, and ICU length of stay. Statistical analyses estimated that more than 500 deaths were prevented each year with the AAM program. LESSONS LEARNED: Unlocking the potential of predictive modeling in the EHR is the first step toward realizing the promise of artificial intelligence/machine learning (AI/ML) to improve health outcomes. The AAM program leveraged predictive analytics to produce highly reliable care by identifying at-risk patients, preventing deterioration, and reducing adverse outcomes and can be used as a model for how clinical decision support and inpatient population management can effectively improve care.

Remote COVID-19 patient monitoring system: a qualitative evaluation.

BACKGROUND: Many COVID-19 patients are discharged home from hospital with instructions to self-isolate. This reduces the burden on potentially overwhelmed hospitals. The Royal Melbourne Hospital (RMH) Home Monitoring Programme (HMP) is a model of care for COVID-19 patients which chiefly tracks pulse oximetry and body temperature readings. OBJECTIVE: To evaluate the feasibility and acceptability of the HMP from a patient perspective. DESIGN, SETTINGS AND PARTICIPANTS: Of 46 COVID-19 patients who used the HMP through RMH during April to August 2020, 16 were invited to participate in this qualitative evaluation study; all accepted, including 6 healthcare workers. Attempts were made to recruit a gender-balanced sample across a range of COVID-19 severities and comorbidities. Participants completed a brief semistructured phone interview discussing their experience of using the HMP. OUTCOME MEASURES AND ANALYSIS: A thematic analysis of interview data was conducted. Feasibility was defined as the HMP's reported ease of use. Acceptability was considered holistically by reviewing themes in the interview data. RESULTS: The HMP allowed clinical deterioration to be recognised as it occurred enabling prompt intervention. All participants reported a positive opinion of the HMP, stating it was highly acceptable and easy to use. Almost all participants said they found using it reassuring. Patients frequently mentioned the importance of the monitoring clinicians as an information conduit. The most suggested improvement was to monitor a broader set of symptoms. CONCLUSIONS: The HMP is highly feasible and acceptable to patients. This model of care could potentially be implemented on a mass-scale to reduce the burden of COVID-19 on hospitals. A key benefit of the HMP is the ability to reassure patients they will receive suitable intervention should they deteriorate while isolating outside of hospital settings.

Technical, Regulatory, Economic, and Trust Issues Preventing Successful Integration of Sensors into the Mainstream Consumer Wearables Market.

Sensors that track physiological biomarkers of health must be successfully incorporated into a fieldable, wearable device if they are to revolutionize the management of remote patient care and preventative medicine. This perspective article discusses logistical considerations that may impede the process of adapting a body-worn laboratory sensor into a commercial-integrated health monitoring system with a focus on examples from sleep tracking technology.

Can serum albumin level affect the transcutaneous bilirubinometry in term neonates?

BACKGROUND: Jaundice is the quite common benign condition in neonates, but due to its potential toxicity, neonates must be monitored. This study was aimed to evaluate the effect of serum albumin level on the transcutaneous bilirubin (TcB) measurements in term neonates with unconjugated hyperbilirubinemia. METHODS: Serum albumin and total serum bilirubin (TSB) of 252 jaundiced term neonates were estimated and simultaneously TcB was measured over sternum and the effect of serum albumin on TcB measurements was evaluated. RESULTS: The correlation between TSB and TcB was linear and significant for the entire cohort. When this correlation was studied separately in the groups with different albumin levels, maximum correlation (r = 0.888, R2 linear = 0.789, p < 0.001) was observed in group 1 with hypo-albuminemia followed by in group 2 with normal albumin levels (r = 0.854, R2 linear = 0.729, p < 0.001) and group 3 with higher albumin levels (r = 0.809, R2 linear = 0.689, p < 0.001). Bland-Altman plot analysis of whole study population demonstrate good agreement between TSB and TcB [95% CI = -0.038 to 0.493 mg/dL, 17/252 = 6.75% outside the limits of agreement, Mean difference = 0.227]. This analysis in different groups also show good agreement between TSB and TcB. CONCLUSIONS: The correlation between the TSB and TcB may affected by serum albumin level. Therefore, transcutaneous bilirubinometry is not able to replace invasive TSB measurement. However, in the absence of TSB it could be an alternative to measure the level of bilirubin in term neonates.

New Internet of Medical Things for Home-Based Treatment of Anorectal Disorders.

Home-based healthcare provides a viable and cost-effective method of delivery for resource- and labour-intensive therapies, such as rehabilitation therapies, including anorectal biofeedback. However, existing systems for home anorectal biofeedback are not able to monitor patient compliance or assess the quality of exercises performed, and as a result have yet to see wide spread clinical adoption. In this paper, we propose a new Internet of Medical Things (IoMT) system to provide home-based biofeedback therapy, facilitating remote monitoring by the physician. We discuss our user-centric design process and the proposed architecture, including a new sensing probe, mobile app, and cloud-based web application. A case study involving biofeedback training exercises was performed. Data from the IoMT was compared against the clinical standard, high-definition anorectal manometry. We demonstrated the feasibility of our proposed IoMT in providing anorectal pressure profiles equivalent to clinical manometry and its application for home-based anorectal biofeedback therapy.

The Dewey Monitor: Pulse Oximetry can Warn of Hypoxia in an Immersed Rebreather Diver in Multiple Scenarios.

Divers who wish to prolong their time underwater while carrying less equipment often use devices called rebreathers, which recycle the gas expired after each breath instead of discarding it as bubbles. However, rebreathers' need to replace oxygen used by breathing creates a failure mechanism that can and frequently does lead to hypoxia, loss of consciousness, and death. The purpose of this study was to determine whether a pulse oximeter could provide a useful amount of warning time to a diver with a rebreather after failure of the oxygen addition mechanism. Twenty-eight volunteer human subjects breathed on a mixed-gas rebreather in which the oxygen addition system had been disabled. The subjects were immersed in water in four separate environmental scenarios, including cold and warm water, and monitored using pulse oximeters placed at multiple locations. Pulse oximeters placed on the forehead and clipped on the nasal ala provided a mean of 32 s (±10 s SD) of warning time to divers with falling oxygen levels, prior to risk of loss of consciousness. These devices, if configured for underwater use, could provide a practical and inexpensive alarm system to warn of impending loss of consciousness in a manner that is redundant to the rebreather.

Data fusion of middle-resolution NMR spectroscopy and low-field relaxometry using the Common Dimensions Analysis (ComDim) to monitor diesel fuel adulteration.

Medium-resolution (MR-NMR) and time-domain NMR relaxometry (TD-NMR) using benchtop and low-field NMR instruments are powerful tools to tackle fuel adulteration issues. In this work, for the first time, we investigate the possibility of enhancing the low-field NMR capability on fuel analysis using data fusion of MR and TD-NMR. We used the ComDim (Common Dimensions Analysis) multi-block analysis to join the data, which allowed exploration, classification, and quantification of common adulterations of diesel fuel by vegetable oils, biodiesel, and diesel of different sources as well as the sulfur content. After data exploration using ComDim, classification (applying linear discriminant analysis, LDA), and regression (applying multiple linear regression, MLR), models were built using ComDim scores as input variables on the LDA and MLR analyses. This approach enabled 100% of accuracy in classifying diesel fuel source (refinery), sulfur content (S10 or S500), vegetable oil, and biodiesel source. Moreover, in the quantification step, all MLR models showed a root mean square error of prediction (RMSEP) and the residual prediction deviation (RPD) values comparable to the literature for determining diesel, vegetable oil, and biodiesel contents.

Ultrafast-Response/Recovery Flexible Piezoresistive Sensors with DNA-Like Double Helix Yarns for Epidermal Pulse Monitoring.

A key challenge in textile sensors is to adequately solve the hysteresis for more broad and exacting applications. Unlike the conventional strategy in integrating elastic polymers into the textile, the hysteretic issue is critically addressed here through the structural design of yarns to provide a twisting force. The underlying mechanism is fully discussed based on theory and modeling, which are in good agreement with experimental data. Impressively, the pressure sensor outperforms almost all reported textile-based sensors in terms of recovery index, which refers to the ability to overcome the lagged deformation reflected by the hysteresis (5.3%) and relaxation time (2 ms). Besides, the sensor superiority is also demonstrated by way of its ultrafast response time (2 ms). Thanks to these merits, this pressure sensor is demonstrated to be capable of monitoring epidermal pulses and meanwhile shows great potential to advance the standardization and modernization of pulse palpation in traditional Chinese medicine.

Deep learning enabled classification of real-time respiration signals acquired by MoSSe quantum dot-based flexible sensors.

Respiration rate is a vital parameter which is useful for the earlier identification of diseases. In this context, various types of devices have been fabricated and developed to monitor different breath rates. However, the disposability and biocompatibility of such sensors and the poor classification of different breath rates from sensor data are significant issues in medical services. This report attempts to focus on two important things: the classification of respiration signals from sensor data using deep learning and the disposability of devices. The use of the novel Janus MoSSe quantum dot (MoSSe QD) structure allows for stable respiration sensing because of unchanged wear rates under humid conditions, and also, the electron affinity and work function values suggest that MoSSe has a higher tendency to donate electrons and interact with the hydrogen molecule. Furthermore, for the real-time classification of different respiration signals, a 1D convolutional neural network (1D CNN) was incorporated. This algorithm was applied to four different breath patterns which achieved a state-of-the-art 10-trial accuracy of 98.18% for normal, 95.25% for slow, 97.64% for deep, and 98.18% for fast breaths. The successful demonstration of a stable, low-cost, and disposable respiration sensor with a highly accurate classification of signals is a major step ahead in developing wearable respiration sensors for future personal healthcare monitoring systems.