Digital Monitoring Research Articles

Digital biomarkers: 3PM approach revolutionizing chronic disease management — EPMA 2024 position

Non-communicable chronic diseases (NCDs) have become a major global health concern. They constitute the leading cause of disabilities, increased morbidity, mortality, and socio-economic disasters worldwide.Medical condition-specific digital biomarker (DB) panels have emerged as valuable tools to manage NCDs. DBs refer to the measurable and quantifiable physiological, behavioral, and environmental parameters collected for an individual through innovative digital health technologies, including wearables, smart devices, and medical sensors. By leveraging digital technologies, healthcare providers can gather real-time data and insights, enabling them to deliver more proactive and tailored interventions to individuals at risk and patients diagnosed with NCDs.Continuous monitoring of relevant health parameters through wearable devices or smartphone applications allows patients and clinicians to track the progression of NCDs in real time. With the introduction of digital biomarker monitoring (DBM), a new quality of primary and secondary healthcare is being offered with promising opportunities for health risk assessment and protection against health-to-disease transitions in vulnerable sub-populations. DBM enables healthcare providers to take the most cost-effective targeted preventive measures, to detect disease developments early, and to introduce personalized interventions. Consequently, they benefit the quality of life (QoL) of affected individuals, healthcare economy, and society at large.DBM is instrumental for the paradigm shift from reactive medical services to 3PM approach promoted by the European Association for Predictive, Preventive, and Personalized Medicine (EPMA) involving 3PM experts from 55 countries worldwide. This position manuscript consolidates multi-professional expertise in the area, demonstrating clinically relevant examples and providing the roadmap for implementing 3PM concepts facilitated through DBs.

Research on digital twin monitoring system for hot stamping

Research on digital twin monitoring system for hot stamping

Enhancing supervision efficiency and satisfaction: Evaluating the impact of the e-monprakerin model on vocational high school apprenticeship monitoring

This study presents a novel approach to addressing the challenges brought about by Industry 4.0 in vocational education, particularly within the context of Indonesia's evolving industrial landscape. With industries increasingly embracing digitalization and automation, traditional apprenticeship supervision methods have struggled to keep pace. In response, this research introduces the e-monPrakerin model, an electronic-based supervision system tailored for vocational high schools (Bahasa: Sekolah Menengah Kejuruan/SMK). Through rigorous evaluation employing a randomized control group pretest-posttest design, the study demonstrates the effectiveness of the e-monPrakerin model compared to conventional methods. Results reveal significant improvements in practicality and user satisfaction, with practicability scores soaring from 41.1% to 81.3% and user satisfaction scores escalating from 31.6% to 84.4% post-implementation. These outcomes underscore the e-monPrakerin model's ability to optimize apprenticeship monitoring, offering a cost-effective, user-friendly, and efficient solution for navigating the complexities of Industry 4.0. By leveraging information technology to bridge the gap between vocational education and industry demands, this research sheds light on the practical implications of digital monitoring solutions. Ultimately, the e-monPrakerin model represents a substantial advancement in vocational education, showcasing the efficacy of technology-driven approaches in enhancing monitoring efficiency and user satisfaction. This contribution adds valuable insights to the field, benefiting educators, policymakers, and stakeholders alike in their efforts to equip the workforce with the skills necessary to thrive in the era of Industry 4.0.

Scalable Compositional Digital Twin-Based Monitoring System for Production Management: Design and Development in an Experimental Open-Pit Mine

While digital twins (DTs) have recently gained prominence as a viable option for creating reliable asset representations, many existing frameworks and architectures in the literature involve the integration of different technologies and paradigms, including the Internet of Things (IoTs), data modeling, and machine learning (ML). This complexity requires the orchestration of these different technologies, often resulting in subsystems and composition frameworks that are difficult to seamlessly align. In this paper, we present a scalable compositional framework designed for the development of a DT-based production management system (PMS) with advanced production monitoring capabilities. The conducted approach used to design the compositional framework utilizes the Factory Design and Improvement (FDI) methodology. Furthermore, the validation of our proposed framework is illustrated through a case study conducted in a phosphate screening station within the context of the mining industry.

Post-discharge surgical site infection surveillance using patient smartphones: a single-centre experience in cardiac surgery

Background/Aims Surgical site infections following cardiac surgery pose significant risks and financial burdens to both patients and healthcare systems. This study aimed to explore the implementation and outcomes of a novel surgical wound monitoring system using patient smartphones for post-discharge surveillance. Methods The study was conducted at a London-based cardiothoracic tertiary referral centre, where 1358 patients undergoing cardiac surgery between January 2021 and March 2023 were enrolled onto the surgical wound monitoring system. Data were collected from the National Cardiac Audit Programme dataset, the monitoring system and Hospital Episode Statistics data. Comparisons between patients who did or did not respond to surveillance requests were performed. A nested confirmatory analysis assessed antibiotics reported by patients through the digital route compared with antibiotics given by GPs or in outpatients. Results The overall response rate for surgical wound monitoring using patient smartphones was 86.6%. Patients who were female, from areas of higher deprivation and lived closer to the hospital were less likely to engage with surgical wound monitoring. Although not statistically significant, the current study suggests that patients with surgical site infections who used smartphones for surgical wound monitoring were less likely to be re-admitted or have further surgery and had shorter readmission stays. The accuracy of antibiotic use for surgical site infections using the surgical wound monitoring system was 96.5%. Conclusions This study underscores the potential of digital technologies, particularly smartphones, in efficient and accurate post-surgical monitoring. The findings suggest that the use of digital monitoring systems may improve patient outcomes, with potential for wider system-level benefits.

Factors Affecting Usage of a Digital Asthma Monitoring Application by Old-Age Asthmatics Living in Inner Central Portugal.

To analyse factors affecting the ability to use the digital asthma monitoring application Mask-Air® in old-age individuals living in inland Portugal. In this observational study, patients with medically confirmed asthma who agreed to participate were interviewed and subdivided into Non-users Group: those who could not use the application and Users Group: those who could. Sociodemographic and psychological data, comorbidities, and asthma status were compared between groups. Assessment of reasons for refusal was based on a 6-item questionnaire. Among the 72 sequentially recruited patients (mean age±SD 73.26±5.43 yrs; 61 women; 11 men), 44 (61.1%; mean age±SD 74.64±5.68 yrs; 38 women; 6 men)) were included in Non-users Group and 28 (38.9%; mean age±SD 71.11±4.26 yrs; 23 women; 5 men) in Users Group. Non-users Group patients were significantly older, had lower socioeconomic level, and more frequently had severe asthma (25% vs 3.6%; Odds ratio=0.08 (95% CI=0.01-0.81; p=0.033)) and diabetes (32.6% vs 7.4%; Odds ratio=0.17 (95% CI=0.03-0.80; p=0.025)) than Users Group. The main reasons for not using the App were "Lack of required hardware" (n=35) and "Digital illiteracy" (n=26), but lack of interest to use the App among those who had conditions to use it was uncommon. Most old-age asthmatics living in Beira Interior either lack a smartphone or digital skills, which are significant obstacles to implementing app-based monitoring studies.

A service-user digital intervention to collect real-time safety information on acute, adult mental health wards: the WardSonar mixed-methods study.

Acute inpatient mental health services report high levels of safety incidents. The application of patient safety theory has been sparse, particularly concerning interventions that proactively seek patient perspectives. Develop and evaluate a theoretically based, digital monitoring tool to collect real-time information from patients on acute adult mental health wards about their perceptions of ward safety. Theory-informed mixed-methods study. A prototype digital monitoring tool was developed from a co-design approach, implemented in hospital settings, and subjected to qualitative and quantitative evaluation. Phase 1: scoping review of the literature on patient involvement in safety interventions in acute mental health care; evidence scan of digital technology in mental health contexts; qualitative interviews with mental health patients and staff about perspectives on ward safety. This, alongside stakeholder engagement with advisory groups, service users and health professionals, informed the development processes. Most data collection was virtual. Phase 1 resulted in the technical development of a theoretically based digital monitoring tool that collected patient feedback for proactive safety monitoring. Phase 2: implementation of the tool in six adult acute mental health wards across two UK NHS trusts; evaluation via focused ethnography and qualitative interviews. Statistical analysis of WardSonar data and routine ward data involving construction of an hour-by-hour data set per ward, permitting detailed analysis of the use of the WardSonar tool. A total of 8 patients and 13 mental health professionals participated in Phase 1 interviews; 33 staff and 34 patients participated in Phase 2 interviews. Patients could use a web application (the WardSonar tool) to record real-time perceptions of ward safety. Staff could access aggregated, anonymous data to inform timely interventions. Coronavirus disease 2019 restrictions greatly impacted the study. Stakeholder engagement permeated the project. Phase 1 delivered a theory-based, collaboratively designed digital tool for proactive patient safety monitoring. Phase 2 showed that the tool was user friendly and broadly acceptable to patients and staff. The aggregated safety data were infrequently used by staff. Feasibility depended on engaged staff and embedding use of the tool in ward routines. There is strong evidence that an incident leads to increased probability of further incidents within the next 4hours. This puts a measure on the extent to which social/behavioural contagion persists. There is weak evidence to suggest that an incident leads to a greater use of the WardSonar tool in the following hour, but none to suggest that ward atmosphere predicts future incidents. Therefore, how often patients use the tool seems to send a stronger signal about potential incidents than patients' real-time reports about ward atmosphere. Implementation was limited to two NHS trusts. Coronavirus disease 2019 impacted design processes including stakeholder engagement; implementation; and evaluation of the monitoring tool in routine clinical practice. Higher uptake could enhance validity of the results. WardSonar has the potential to provide a valuable route for patients to communicate safety concerns. The WardSonar monitoring tool has a strong patient perspective and uses proactive real-time safety monitoring rather than traditional retrospective data review. The WardSonar tool can be refined and tested further in a post Coronavirus disease 2019 context. This study is registered as ISRCTN14470430. This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR128070) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 14. See the NIHR Funding and Awards website for further award information.

Digital Remote Monitoring Using an mHealth Solution for Survivors of Cancer: Protocol for a Pilot Observational Study.

Healthy lifestyle interventions have a positive impact on multiple disease trajectories, including cancer-related outcomes. Specifically, appropriate habitual physical activity, adequate sleep, and a regular wholesome diet are of paramount importance for the wellness and supportive care of survivors of cancer. Mobile health (mHealth) apps have the potential to support novel tailored lifestyle interventions. This observational pilot study aims to assess the feasibility of mHealth multidimensional longitudinal monitoring in survivors of cancer. The primary objective is to test the compliance (user engagement) with the monitoring solution. Secondary objectives include recording clinically relevant subjective and objective measures collected through the digital solution. This is a monocentric pilot study taking place in Bangor, Wales, United Kingdom. We plan to enroll up to 100 adult survivors of cancer not receiving toxic anticancer treatment, who will provide self-reported behavioral data recorded via a dedicated app and validated questionnaires and objective data automatically collected by a paired smartwatch over 16 weeks. The participants will continue with their normal routine surveillance care for their cancer. The primary end point is feasibility (eg, mHealth monitoring acceptability). Composite secondary end points include clinically relevant patient-reported outcome measures (eg, the Edmonton Symptom Assessment System score) and objective physiological measures (eg, step counts). This trial received a favorable ethical review in May 2023 (Integrated Research Application System 301068). This study is part of an array of pilots within a European Union funded project, entitled "GATEKEEPER," conducted at different sites across Europe and covering various chronic diseases. Study accrual is anticipated to commence in January 2024 and continue until June 2024. It is hypothesized that mHealth monitoring will be feasible in survivors of cancer; specifically, at least 50% (50/100) of the participants will engage with the app at least once a week in 8 of the 16 study weeks. In a population with potentially complex clinical needs, this pilot study will test the feasibility of multidimensional remote monitoring of patient-reported outcomes and physiological parameters. Satisfactory compliance with the use of the app and smartwatch, whether confirmed or infirmed through this study, will be propaedeutic to the development of innovative mHealth interventions in survivors of cancer. PRR1-10.2196/52957.

Perancangan Monitoring Coal Handling System PLTU Kaltim Teluk Berbasis Internet of Things

Abstract— Balikpapan Bay PLTU is a large capacity power plant located in the city of Balikpapan, which is located in East Kalimantan. This PLTU with a capacity of 2X110 MW meets the electricity needs of the Barito Mahakam network, which consists of the East Kalimantan, North Kalimantan, Central Kalimantan and South Kalimantan regions. The main fuel for electricity generation is low grade coal (LRC) or low calorie coal. High Speed Diesel (HSD) oil is used as initial fuel. DCS (Distributed Control System) is used for wood management at PLTU Kaltim Teluk. DCS helps operations by monitoring and controlling the main and supporting components, however, management, supervisors and other staff have difficulty knowing the operating conditions of the generating unit remotely because the monitoring system can only be accessed by the control room operator at the CCR. The aim of this research is to design an Internet of Things-based coal handling system control system for PLTU Kaltim Teluk. This real time based digital monitoring system can collect and display data from every sensor in the field. The research method is a literature study method and a field method to apply the design results and collect monitoring data at the two Balikpapan Bay PLTUs. The results show that testing, which includes integration testing with MySQL, functional testing, and URL and Endpoint testing, was carried out successfully. As expected, all the main features and functions of the PLTU monitoring system are running well. This system has averagepercentage error 0.1%. So this study has an accuracy rate of 99.9%. This system has the ability to make it easier for managers to monitor the system.

Fortifying Uzbekistan's integrity landscape: Harnessing India's tech-driven anti-corruption strategies

Corruption poses significant challenges to sustainable development and social justice in Uzbekistan. This paper explores how Uzbekistan can strengthen its anti-corruption framework by leveraging emerging technologies and drawing lessons from India's experience in using information and communication technology (ICT) to combat corruption. The study employs a qualitative research methodology, analysing data from government reports, case studies, and expert interviews to identify specific areas where Uzbekistan can learn from India's successes and challenges in applying ICT solutions. The findings highlight several key ways ICT can bolster anti-corruption efforts in Uzbekistan, such as increasing transparency through e-governance platforms, improving accountability via digital monitoring systems, and enabling citizen participation with online reporting tools. The paper provides concrete examples and data from India demonstrating how technologies like biometrics, blockchain, and data analytics have helped detect fraud, streamline bureaucratic processes, and empower citizens to report corruption. However, the research also reveals critical legal, institutional and cultural barriers Uzbekistan must address to effectively implement these tech-based approaches, such as outdated regulations, lack of technical expertise, and public distrust. Comparing India and Uzbekistan's contexts, the paper offers tailored recommendations for how Uzbekistan can adapt India's ICT models to overcome its unique constraints. The study concludes that while technology is not a panacea, strategically integrating ICT into Uzbekistan's anti-corruption arsenal – with insights from India's experience – can be a powerful tool to promote good governance, curb corruption, and ultimately advance social justice for citizens. More research is needed to assess the long-term impacts and scalability of specific ICT interventions.

Enhancing Dementia Risk Mitigation: Standardized Digital Monitoring in Clinical Trials and Platform Design for At-Risk Elderly Individuals.

Dementia is becoming a significant public health concern, affecting approximately 130,000 individuals in Austria, whereby nearly 40% of the cases are attributed to modifiable risk factors. Multidomain lifestyle interventions have thereby demonstrated significant effects in reducing the risk of dementia. The goal was to define an interoperability framework to conduct standardized monitoring in clinical trials for enhancing dementia risk mitigation. In addition, the identified standards should be integrated into the components of the project. A step-by-step approach was used, where initially data collection, aggregation and harmonization was carried out with retrospective data from various clinical centers. Afterwards, the interoperability framework was defined including the prospective data that is gathered during a clinical trial. A guideline for integrating healthcare standards was developed and incorporated into the technical components for the clinical trial. The interoperability framework was designed in a scalable way and will be regularly updated for future needs.

A Digital Vaccination Pass Using Fast Healthcare Interoperability Resources: A Proof of Concept

The traditional manual recording of vaccination records in Germany faced challenges during the COVID-19 pandemic, prompting the introduction of a COVID smartphone app with QR codes. However, this solution brought new challenges, emphasizing the need for a centrally managed European digital vaccination record for efficiency and validity. This study assesses the feasibility of using the HL7 FHIR standard in the healthcare industry for implementing a digital vaccination pass management and monitoring system. The system aims to offer convenience and improved efficiency for both patients and healthcare providers while promoting interoperability with other healthcare systems. To this end, we developed a prototype using modern technologies, such as React, Quarkus, and Keycloak. Results indicate potential benefits for patients and healthcare providers, offering access to immunization records, personalized recommendations, and streamlined management. However, integrating nuanced vaccination processes into the standardized FHIR system requires custom extensions, which might hinder interoperability. Manual data entry and the integration of an identity provider present further obstacles in industry scenarios. Despite these challenges, this study suggests that implementing HL7 FHIR can enhance efficiency, data accessibility, and accuracy in the vaccination process, supporting broader digitization efforts in the German healthcare system and beyond.

Perceptions and Experiences of Healthcare Providers and Patients Towards Digital Health Services in Primary Health Care: A Cross-Sectional Study.

Digital health has the potential to help achieve the Sustainable Development Goals (SDGs) by supporting health systems and enhancing health promotion and disease prevention. However, obstacles such as restricted internet access, inadequate technical assistance, clinical resource disparity, and insufficient user training can impede the utilization and growth of digital health. Researchers should examine healthcare providers' and patients' perspectives to identify challenges and enhance usability. The study was conducted among women health volunteers, staff nurses, and patients who used the VinCense mobile application (MedIoTek Health Systems Private Limited, Chennai, India) to record vital signs. A semi-structured questionnaire was used to evaluate participants' sociodemographic characteristics, perception of digital health monitoring, and patients' attitudes toward digital health monitoring devices. The data were analyzed using R programming, Version 4.3.3 (www.r-project.org). A multinomial logistic regression analysis was used to examine the association between sociodemographic characteristics and attitudes of patients toward digital health monitoring. The study involved 27 healthcare providers and 406 patients. The majority (66.6%) of healthcare providers found the device convenient and efficient. Around 74.1% faced technical difficulties like internet connectivity and device battery issues. Among patients, 79.8% were satisfied with their digital health monitoring experience, 86.2% found device usage comfortable and 78.1% expressed satisfaction with health education and feedback.Around 354 (87.2%) patients stated that technology has improved healthcare, and 326 (80.3%) said that health technologies have improved ease. The results indicate that female gender (p=0.00), age above 50 years (p=0.04), and occupation status as a semiskilled worker (p=0.03), skilled worker (p=0.00), and clerical/shop/farmer (p=0.01) were statistically significant and associated with the positive attitude for digital health monitoring. The digital health monitoring experience was found satisfactory by both patients and healthcare providers. The mobile health (mHealth) has tremendous potential for enhancing patient health. Therefore, it is advisable to contemplate an expansion of the VinCense mHealth Platform and other digital solutions to improve service delivery in primary healthcare setups.

Entity Footprinting: Modeling Contextual User States via Digital Activity Monitoring

Our digital life consists of activities that are organized around tasks and exhibit different user states in the digital contexts around these activities. Previous works have shown that digital activity monitoring can be used to predict entities that users will need to perform digital tasks. There have been methods developed to automatically detect the tasks of a user. However, these studies typically support only specific applications and tasks, and relatively little research has been conducted on real-life digital activities. This article introduces user state modeling and prediction with contextual information captured as entities, recorded from real-world digital user behavior, called entity footprinting —a system that records users’ digital activities on their screens and proactively provides useful entities across application boundaries without requiring explicit query formulation. Our methodology is to detect contextual user states using latent representations of entities occurring in digital activities. Using topic models and recurrent neural networks, the model learns the latent representation of concurrent entities and their sequential relationships. We report a field study in which the digital activities of 13 people were recorded continuously for 14 days. The model learned from this data is used to (1) predict contextual user states and (2) predict relevant entities for the detected states. The results show improved user state detection accuracy and entity prediction performance compared to static, heuristic, and basic topic models. Our findings have implications for the design of proactive recommendation systems that can implicitly infer users’ contextual state by monitoring users’ digital activities and proactively recommending the right information at the right time.

Application of Clustering Algorithm in Fault State Classification of Low Voltage Watt-Hour Meter

In this paper, a low-voltage digital watt-hour meter monitoring system for smart grid is designed. The system includes information acquisition system, low-voltage digital meter and power service system. The low-voltage digital meter uses RFID chip inside, which can accurately locate the target through high-speed transmission and remote identification. It can effectively overcome the security risks caused by information collision and the problem of slow recognition speed. According to different fault categories, community clustering method is used to classify them. In the actual determination of the fault causes of 32 electric energy meters with this method correctly analyzed the fault causes of 26 electric energy meters. The accuracy rate reached 81.25%.

Advancing horizons in vegetable cultivation: a journey from ageold practices to high-tech greenhouse cultivation-a review.

Vegetable cultivation stands as a pivotal element in the agricultural transformation illustrating a complex interplay between technological advancements, evolving environmental perspectives, and the growing global demand for food. This comprehensive review delves into the broad spectrum of developments in modern vegetable cultivation practices. Rooted in historical traditions, our exploration commences with conventional cultivation methods and traces the progression toward contemporary practices emphasizing the critical shifts that have refined techniques and outcomes. A significant focus is placed on the evolution of seed selection and quality assessment methods underlining the growing importance of seed treatments in enhancing both germination and plant growth. Transitioning from seeds to the soil, we investigate the transformative journey from traditional soil-based cultivation to the adoption of soilless cultures and the utilization of sustainable substrates like biochar and coir. The review also examines modern environmental controls highlighting the use of advanced greenhouse technologies and artificial intelligence in optimizing plant growth conditions. We underscore the increasing sophistication in water management strategies from advanced irrigation systems to intelligent moisture sensing. Additionally, this paper discusses the intricate aspects of precision fertilization, integrated pest management, and the expanding influence of plant growth regulators in vegetable cultivation. A special segment is dedicated to technological innovations, such as the integration of drones, robots, and state-of-the-art digital monitoring systems, in the cultivation process. While acknowledging these advancements, the review also realistically addresses the challenges and economic considerations involved in adopting cutting-edge technologies. In summary, this review not only provides a comprehensive guide to the current state of vegetable cultivation but also serves as a forward-looking reference emphasizing the critical role of continuous research and the anticipation of future developments in this field.

Promoting a Patient-Centered Understanding of Safety in Acute Mental Health Wards: A User-Centered Design Approach to Develop a Real-Time Digital Monitoring Tool.

Acute mental health services report high levels of safety incidents that involve both patients and staff. The potential for patients to be involved in interventions to improve safety within a mental health setting is acknowledged, and there is a need for interventions that proactively seek the patient perspective of safety. Digital technologies may offer opportunities to address this need. This research sought to design and develop a digital real-time monitoring tool (WardSonar) to collect and collate daily information from patients in acute mental health wards about their perceptions of safety. We present the design and development process and underpinning logic model and programme theory. The first stage involved a synthesis of the findings from a systematic review and evidence scan, interviews with patients (n=8) and health professionals (n=17), and stakeholder engagement. Cycles of design activities and discussion followed with patients, staff, and stakeholder groups, to design and develop the prototype tool. We drew on patient safety theory and the concepts of contagion and milieu. The data synthesis, design, and development process resulted in three prototype components of the digital monitoring tool (WardSonar): (1) a patient recording interface that asks patients to input their perceptions into a tablet computer, to assess how the ward feels and whether the direction is changing, that is, "getting worse" or "getting better"; (2) a staff dashboard and functionality to interrogate the data at different levels; and (3) a public-facing ward interface. The technology is available as open-source code. Recent patient safety policy and research priorities encourage innovative approaches to measuring and monitoring safety. We developed a digital real-time monitoring tool to collect information from patients in acute mental health wards about perceived safety, to support staff to respond and intervene to changes in the clinical environment more proactively.

Smartphone-based Remote Digital Monitoring for Parkinson’s Disease and Dementia (S35.007)

Smartphone-based Remote Digital Monitoring for Parkinson’s Disease and Dementia (S35.007)

Timing and Patient Position During Cuff Blood Pressure Measurement Affect Myocardial Work Parameters Measured by Echocardiography

Although cuff blood pressure measurement is a critical parameter to calculate myocardial work noninvasively, there is no recommendation about when and how to measure it. Accordingly, we sought to evaluate the effects of the timing during the echo study and the patient's position on the scanning bed during the cuff blood pressure measurement on myocardial work parameter calculations. One hundred one consecutive patients (44 women, 66±14years) undergoing clinically indicated echocardiography were prospectively enrolled. During the echocardiographic study, we measured the cuff blood pressure 4 times, using a fully automatic digital blood pressure monitor applied to the right and left arm in the same position throughout the study: BP1, before the start of the echo study, with the patient lying in the supine position; BP2, after positioning the patients on their left side to start the echo study; BP3, at the time of the acquisition of the 3 apical views (4- and 2-chamber and long-axis) used to measured left ventricular global longitudinal strain; and BP4, at the end of the echo study with the patient again in the supine position. Systolic blood pressureat BP1 was 147±21mm Hg. Between BP1 and BP2, it dropped by 17±9mm Hg (P<.05). Systolic blood pressure at BP3 was significantly lower than BP2 (130±20mm Hg vs 122±18mm Hg, P<.05), and at BP4 was significantly lower than at BP1 (-9 ± 13mm Hg, P<.05). The average global longitudinal strain was -16%±3%. Accordingly, the global work index was 1,929±441mm Hg% at BP1, dropped to 1,717±421 at BP2, decreased to 1,602±351mm Hg% at BP3, and increased to 1,815±386mm Hg% at BP4 (P<.001). The timing during the echocardiography study and the patient's position on the scanning bed are critical determinants of the measured cuff systolic blood pressure and the resulting values of myocardial work parameters.

Evaluating the Accuracy of O’Tracker: A Stick-To-Skin Wireless BBT Sensor to Identify Fertility Window

Objective: The study identifies the event of ovulation using an IoT-based device called “O’Tracker” in contrast with thetransvaginal ultrasound in trying to conceive women.Methods: This prospective study includes a total of 30 cycles from 27 women who were trying to conceive. They were asked to use the O’Tracker device from the 10th day of their menstrual cycle to the 18th day, i.e., 8 days for 7 hours per night.Result: In the conclusive evaluation, a total of 30 cycles underwent scrutiny, wherein the O’Tracker predictions of theovulation window were aligned with physicians’ predicted ovulation window from the USG reports in 27 cycles, indicatinga commendable accuracy rate of 90%. Upon proximity to the ovulation window predicted by O’Tracker with those derivedfrom the USG report (considered as the ground truth for validation) the concordance was observed in 25 out of 27 accuratelypredicted ovulatory cycles. Furthermore, when compared to the physician-predicted ovulation window from USG reports,O’Tracker exhibited concordance in 23 out of 27 cycles.Conclusion: The study evaluation reveals that O’Tracker attains a 90% accuracy in predicting ovulation as compared tophysician assessment, demonstrating a match rate exceeding 90% with fertile windows ascertained through ultrasoundmonitoring. This level of precision stands on with established traditional diagnostics methodologies. O’Tracker manifests auser-friendly and accessible digital ovulation monitoring platform.