How Mobile Health Can Change the Contexts of Living With HIV and Engaging With Treatment and Care in Iran: A Realist-Informed Qualitative Study.

Mobile health (mHealth) interventions are increasingly used to address the challenges of living with HIV and engaging with antiretroviral therapy. A wealth of evidence supports the efficacy of mHealth in supporting living with HIV. Yet, there is a dearth of evidence on how mHealth improves outcomes, which features are effective, and why these work in a particular setting. This study uses stakeholder views, including patients, providers, peer supporters, counsellors, and program directors, to conceptualize how specific mHealth features could interact with contexts of living with HIV and mechanisms that shape engagement with treatment. The study is part of an ongoing research project on engagement with HIV care in Iran. We draw on the perspectives of recently diagnosed and more treatment-experienced patients and their providers, using purposive sampling, conducting 9 focus group discussions with a total of 66 participants, in addition to 17 interviews. Our findings suggest that mHealth designs that feature provider connection, proactive care, and privacy and personalization are expected to dilute the harsh contexts of living with HIV. We build on previously identified socioecological pathways that disrupt antiretroviral therapy in Iran and find that mHealth can enhance the relation between the health system and patients. Our findings suggest that personalized mHealth features and provisions can partially mitigate the compounded impacts of harsh socioecological pathways that impede treatment success in Iran. Our social constructivist study was augmented with realist-informed analysis and could have transferability to similar contexts that trigger similar mechanisms of treatment disruption.

Association between glucose levels of children with type 1 diabetes and parental economic status in mobile health application.

BACKGROUND: The glycemic control of children with type 1 diabetes (T1D) may be influenced by the economic status of their parents. AIM: To investigate the association between parental economic status and blood glucose levels of children with T1D using a mobile health application. METHODS: Data from children with T1D in China's largest T1D online community, Tang-TangQuan®. Blood glucose levels were uploaded every three months and parental economic status was evaluated based on annual household income. Children were divided into three groups: Low-income (< 30000 Yuan), middle-income (30000-100000 Yuan), and high-income (> 100000 yuan) (1 Yuan = 0.145 United States Dollar approximately). Blood glucose levels were compared among the groups and associations were explored using Spearman's correlation analysis and multivariable logistic regression. RESULTS: From September 2015 to August 2022, 1406 eligible children with T1D were included (779 female, 55.4%). Median age was 8.1 years (Q1-Q3: 4.6-11.6) and duration of T1D was 0.06 years (0.02-0.44). Participants were divided into three groups: Low-income (n = 320), middle-income (n = 724), and high-income (n = 362). Baseline hemoglobin A1c (HbA1c) levels were comparable among the three groups (P = 0.072). However, at month 36, the low-income group had the highest HbA1c levels (P = 0.036). Within three years after registration, glucose levels increased significantly in the low-income group but not in the middle-income and high-income groups. Parental economic status was negatively correlated with pre-dinner glucose (r = -0.272, P = 0.012). After adjustment for confounders, parental economic status remained a significant factor related to pre-dinner glucose levels (odds ratio = 13.02, 95%CI: 1.99 to 126.05, P = 0.002). CONCLUSION: The blood glucose levels of children with T1D were negatively associated with parental economic status. It is suggested that parental economic status should be taken into consideration in the management of T1D for children.

Data Collection and Management of mHealth, Wearables, and Internet of Things in Digital Behavioral Health Interventions With the Awesome Data Acquisition Method (ADAM): Development of a Novel Informatics Architecture.

Unlabelled: The integration of health and activity data from various wearable devices into research studies presents technical and operational challenges. The Awesome Data Acquisition Method (ADAM) is a versatile, web-based system that was designed for integrating data from various sources and managing a large-scale multiphase research study. As a data collecting system, ADAM allows real-time data collection from wearable devices through the device's application programmable interface and the mobile app's adaptive real-time questionnaires. As a clinical trial management system, ADAM integrates clinical trial management processes and efficiently supports recruitment, screening, randomization, data tracking, data reporting, and data analysis during the entire research study process. We used a behavioral weight-loss intervention study (SMARTER trial) as a test case to evaluate the ADAM system. SMARTER was a randomized controlled trial that screened 1741 participants and enrolled 502 adults. As a result, the ADAM system was efficiently and successfully deployed to organize and manage the SMARTER trial. Moreover, with its versatile integration capability, the ADAM system made the necessary switch to fully remote assessments and tracking that are performed seamlessly and promptly when the COVID-19 pandemic ceased in-person contact. The remote-native features afforded by the ADAM system minimized the effects of the COVID-19 lockdown on the SMARTER trial. The success of SMARTER proved the comprehensiveness and efficiency of the ADAM system. Moreover, ADAM was designed to be generalizable and scalable to fit other studies with minimal editing, redevelopment, and customization. The ADAM system can benefit various behavioral interventions and different populations.

Applying the PRECEDE-PROCEED model to develop MommaConnect: a digital healthcare platform for addressing postpartum depression and improving infant well-being.

The PRECEDE-PROCEED model is a comprehensive planning and theoretical framework that incorporates epidemiological, environmental, behavioral, and social factors systematically to design, implement, and evaluate health promotion programs. As such, PRECEDE-PROCEED is a highly effective tool for addressing complex and significant public health concerns like postpartum depression (PPD). PPD negatively impacts mothers and their infants, with studies showing that approximately one in eight mothers experience PPD, leading to adverse effects on maternal functioning and infant development. However, access to specialized evidence-based treatment remains significantly limited due to barriers including social determinants of health. This paper explores the application of the PRECEDE-PROCEED model as a planning and theoretical framework for the design and development of MommaConnect, an innovative digital healthcare platform aimed at reducing PPD symptoms and improving maternal-infant interaction while overcoming barriers to treatment. Key components of the MommaConnect design and development process are mapped onto the steps of the PRECEDE-PROCEED model. MommaConnect features are aligned with specific stages of the model, from assessing, predisposing, enabling, and reinforcing factors to designing, implementing, and evaluating the intervention. By leveraging this model, MommaConnect represents a promising innovative approach to address PPD to improve maternal functioning and infant health in a digitally-enabled era. This paper underscores the importance of utilizing a framework like the PRECEDE-PROCEED model in the design and development of innovative healthcare solutions.

Online Survey Study on the Needs of Former Intensive-Care Patients for the Development of a User-Friendly App.

The aim of this online-survey study is the development and evaluation of a mobile health application specifically designed to meet the needs of individuals who have previously undergone intensive-care treatment. User acceptance and perception play a crucial role in refining and optimizing the app's features and functionalities. By actively incorporating suggestions and insights from users, the goal is to enhance the overall usability and better cater to the diverse needs of individuals in post-intensive care recovery. This iterative approach ensures that the application remains responsive to the evolving requirements of its target audience. Overall, the emphasis is on creating a user-centric and adaptive tool for former intensive care patients, to develop a user-friendly mobile app.

Insights into the Quality of Mobile Health Apps: Preliminary Results of an Analysis of MARS Scores.

Many mHelath applications have been developed, and the Mobile App Rating Scale (MARS) is a common tool for assessing them. This study aims to provide mean values for MARS scores found in recent literature. We systematically searched for literature in which MARS was used and analyzed them. MARS values for 5,920 applications from 215 studies were compiled. The mean MARS Quality Score is 3.51. The highest average score was achieved in the Functionality category (3.98), followed by Aesthetics (3.52), Information (3.33), Engagement (3.18) and Subjective (2.72). To the best of our knowledge, this is the first study to calculate average values for the five categories of the MARS and the MARS score based on such an extensive collection of data. The study shows that the overall quality of the applications is above the average value of 2.5.

Digital Transformation of the Healthcare Sector in Africa: First Results from a Study on Success Factors and Barriers for the Implementation of mHealth in South Africa and Tanzania.

This study explores the critical success factors and barriers to mHealth implementation in South Africa and Tanzania. Through an unstructured literature review and semi-structured interviews with eight mHealth experts, the study uncovers common challenges, including lack of alignment with user needs, inadequate government support, and sustainability issues. Critical success factors identified include user-friendly design and adaptable tools offered at low or no cost. The findings offer insights for organizations and startups in the mHealth sector, highlighting essential considerations for success and barriers alongside strategies for overcoming obstacles and fostering an environment conducive to mHealth integration.

Muzima Mobile Application for Screening Hypertension and Diabetes: A User Experience of the App Among Community Health Workers in Rwanda.

Mobile technology has become the leading utility in the social and well-being of people especially in low-resource settings. The use of mobile applications in healthcare promise to improve care and treatment. This study explored the user experience of muzima mobile application among community health workers in Rwanda. We used three data collection methods: observation, Key informant interviews and focus group discussions. We analysed data using thematic content analysis. We found that users were able to complete tasks in the app although some less experienced and older participants struggled to complete the tasks. Users felt that the application helped them to screen and manage patients with diabetes and hypertension in the community which reduced frequent visits to the health centers. Users felt that the application needs improvements in the workflow to facilitate the ease of use. They suggested to digitse other health programs implemented by community health workers. To improve the use and ensure wider implementation, there is a need to consider users' needs and concerns as discussed in this paper.

Quality of Electrocardiography Recorded with Consumer Smart Shirts.

Smart wearables support continuous monitoring of vital signs for early detection of deteriorating health. However, the devices and sensors require sufficient quality to produce meaningful signals, in particular, if data is acquired in motion. In this study, we equipped 48 subjects with smart shirts recording one-lead electrocardiography (ECG), thoracic and abdominal respiratory inductance plethysmography, and three-axis acceleration. For 10 min each, the subjects sit, stand, walk, and run, with a resting period of 5 min in between each activity. We preprocessed the electrocardiogram and applied a signal quality index. We analyzed the signal quality index grouped by the activity and participants. For sitting, standing, walking, and running, the ECG signals provide acceptable quality over 73.20 %, 91.85 %, 12.26 %, and 13.14 % of the recording time. In conclusion, smart wearables may be useful for continuous health monitoring of people with a sedentary lifestyle, but rather not for sportive activities.

Towards Automatic Migraine-Event Prediction Using Continuous Sensor Data.

Migraine is a chronic headache disorder. A prototype mobile app-based system was implemented to test data collection and improve data coverage for the Empatica E4 biometric sensor device. Results from the prototype testing are reported. Future iteration of the app will be tested with patients with migraine to predict events and potentially reduce event duration and therefore disease burden.

The Influence of Self-Efficacy on Older Adults' Use of Mobile Health Applications.

mHealth apps can especially benefit older adults with chronic conditions, but their usage rates remain often low. This study examines how older adults' self-perceived technical skills and confidence affect their use of a mHealth app. It was conducted in southern Germany and included older adults (65 years and older) with and without age-related chronic conditions. Results indicate that perceived self-efficacy does not always match actual capability. This discrepancy raises concerns about how it might impact the use and prescription of these apps.

Development of an mHealth App by Experts for Queer Individuals' Sexual-Reproductive Health Care Services and Needs: Nominal Group Technique Study.

BACKGROUND: Queer individuals continue to be marginalized in South Africa; they experience various health care challenges (eg, stigma, discrimination, prejudice, harassment, and humiliation), mental health issues (eg, suicide and depression), and an increased spread of HIV or AIDS and sexually transmitted illnesses (STIs; chlamydia, gonorrhea, and syphilis). Mobile health (mHealth) apps have the potential to resolve the health care deficits experienced by health care providers when managing queer individuals and by queer individuals when accessing sexual-reproductive health care services and needs, thus ensuring inclusivity and the promotion of health and well-being. Studies have proven that the nominal group technique (NGT) could be used to solve different social and health problems and develop innovative solutions. This technique ensures that different voices are represented during decision-making processes and leads to robust results. OBJECTIVE: This study aims to identify important contents to include in the development of an mHealth app for addressing the sexual-reproductive health care services and needs of queer individuals. METHODS: We invited a group of 13 experts from different fields, such as researchers, queer activists, sexual and reproductive health experts, private practicing health care providers, innovators, and private health care stakeholders, to take part in a face-to-face NGT. The NGT was conducted in the form of a workshop with 1 moderator, 2 research assistants, and 1 principal investigator. The workshop lasted approximately 2 hours 46 minutes and 55 seconds. We followed and applied 5 NGT steps in the workshop for experts to reach consensus. The main question that experts were expected to answer was as follows: Which content should be included in the mHealth app for addressing sexual-reproductive health care services and needs for queer individuals? This question was guided by user demographics and background, health education and information, privacy and security, accessibility and inclusivity, functionality and menu options, personalization and user engagement, service integration and partnerships, feedback and improvement, cultural sensitivity and ethical considerations, legal and regulatory compliance, and connectivity and data use. RESULTS: Overall, experts voted and ranked the following main icons: menu options (66 points), privacy and security (39 points), user engagement (27 points), information hub (26 points), user demographics (20 points), connectivity (16 points), service integration and partnerships (10 points), functionalities (10 points), and accessibility and inclusivity (7 points). CONCLUSIONS: Conducting an NGT with experts from different fields, possessing vast skill sets, knowledge, and expertise, enabled us to obtain targeted data on the development of an mHealth app to address sexual-reproductive health care services and needs for queer individuals. This approach emphasized the usefulness of a multidisciplinary perspective to inform the development of our mHealth app and demonstrated the future need for continuity in using this approach for other digital health care innovations and interventions.

Feasibility and Acceptability of a Mobile Game to Support Smoking Cessation: Repeated Measures Study.

BACKGROUND: Approximately half of smokers attempt to quit, but 90% of these attempts fail. Video game-based interventions have the potential to address common barriers to evidence-based smoking cessation treatment, including high cost, lack of health care access, and low engagement. OBJECTIVE: The purpose of this study was to evaluate the feasibility and acceptability of a video game-based smoking cessation intervention called Inspired and its impact on the 7-day smoking point prevalence at the 30-day follow-up. METHODS: US adults (n=48) were recruited via the web to use Inspired on their smartphones for 7 weeks. The object of the game was to defend a healing tree against attackers. Levels of the game were unlocked twice daily when participants self-reported the number of cigarettes they smoked since the previous entry. Completion of the levels awarded players in-game currency, which could strengthen in-game abilities. Participants received additional in-game rewards to aid gameplay by submitting either smoking self-reports only or self-reports indicating abstinence, determined through random assignment. In addition, participants completed a web-based survey at intake, week 4, week 7, and the 30-day follow-up. RESULTS: Of the 48 participants, who had an average age of 39.8 (SD 10.7) years, 27 (56%) were female, 4 (8%) Hispanic, 37 (77%) White, and 27 (56%) employed; 26 (54%) earned

[The problems related to implementation of AI into health care system: A review].

The AI technologies are more and more widely implemented into modern health care. the mobile medical applications permit to monitor course of chronic diseases and form healthier behavior in patients, to reduce number of visits to medical organizations and to improve accessibility of medical care for limited mobile patients. However, actually there are number of problems limiting implementation of AI into functioning of health services. The article discusses problems associated with computer technologies themselves and medical research using them. The ethical nuances of widespread application of AI are described. The modes of overcoming existing disadvantages of computer and mobile health care are proposed.

Exploring User Experiences of the Mom2B mHealth Research App During the Perinatal Period: Qualitative Study.

BACKGROUND: Perinatal depression affects a significant number of women during pregnancy and after birth, and early identification is imperative for timely interventions and improved prognosis. Mobile apps offer the potential to overcome barriers to health care provision and facilitate clinical research. However, little is known about users' perceptions and acceptability of these apps, particularly digital phenotyping and ecological momentary assessment apps, a relatively novel category of apps and approach to data collection. Understanding user's concerns and the challenges they experience using the app will facilitate adoption and continued engagement. OBJECTIVE: This qualitative study explores the experiences and attitudes of users of the Mom2B mobile health (mHealth) research app (Uppsala University) during the perinatal period. In particular, we aimed to determine the acceptability of the app and any concerns about providing data through a mobile app. METHODS: Semistructured focus group interviews were conducted digitally in Swedish with 13 groups and a total of 41 participants. Participants had been active users of the Mom2B app for at least 6 weeks and included pregnant and postpartum women, both with and without depression symptomatology apparent in their last screening test. Interviews were recorded, transcribed verbatim, translated to English, and evaluated using inductive thematic analysis. RESULTS: Four themes were elicited: acceptability of sharing data, motivators and incentives, barriers to task completion, and user experience. Participants also gave suggestions for the improvement of features and user experience. CONCLUSIONS: The study findings suggest that app-based digital phenotyping is a feasible and acceptable method of conducting research and health care delivery among perinatal women. The Mom2B app was perceived as an efficient and practical tool that facilitates engagement in research as well as allows users to monitor their well-being and receive general and personalized information related to the perinatal period. However, this study also highlights the importance of trustworthiness, accessibility, and prompt technical issue resolution in the development of future research apps in cooperation with end users. The study contributes to the growing body of literature on the usability and acceptability of mobile apps for research and ecological momentary assessment and underscores the need for continued research in this area.

Intelligent health in the IS area: A literature review and research agenda.

As the global demand for healthcare services continues to grow, improving the efficiency and effectiveness of the healthcare ecosystem has become a pressing concern. Information systems are transforming the healthcare delivery process, shifting the focus of healthcare services from passive disease treatment to proactive health prevention and the healthcare management model from hospital-centric to patient-centric. This study focuses on reviewing research in IS journals on the topic of e-health and is dedicated to constructing a theoretical model of intelligent health to provide a research basis for future discussions in this field. In addition, as the innovation of intelligent healthcare services has led to changes in its elements (e.g., an increase in the number of stakeholders), there is an urgent need to sort out and analyze the existing research.

Co-Designing a Smoking Cessation Chatbot: Focus Group Study of End Users and Smoking Cessation Professionals.

BACKGROUND: Our prototype smoking cessation chatbot, Quin, provides evidence-based, personalized support delivered via a smartphone app to help people quit smoking. We developed Quin using a multiphase program of co-design research, part of which included focus group evaluation of Quin among stakeholders prior to clinical testing. OBJECTIVE: This study aimed to gather and compare feedback on the user experience of the Quin prototype from end users and smoking cessation professionals (SCPs) via a beta testing process to inform ongoing chatbot iterations and refinements. METHODS: Following active and passive recruitment, we conducted web-based focus groups with SCPs and end users from Queensland, Australia. Participants tested the app for 1-2 weeks prior to focus group discussion and could also log conversation feedback within the app. Focus groups of SCPs were completed first to review the breadth and accuracy of information, and feedback was prioritized and implemented as major updates using Agile processes prior to end user focus groups. We categorized logged in-app feedback using content analysis and thematically analyzed focus group transcripts. RESULTS: In total, 6 focus groups were completed between August 2022 and June 2023; 3 for SCPs (n=9 participants) and 3 for end users (n=7 participants). Four SCPs had previously smoked, and most end users currently smoked cigarettes (n=5), and 2 had quit smoking. The mean duration of focus groups was 58 (SD 10.9; range 46-74) minutes. We identified four major themes from focus group feedback: (1) conversation design, (2) functionality, (3) relationality and anthropomorphism, and (4) role as a smoking cessation support tool. In response to SCPs' feedback, we made two major updates to Quin between cohorts: (1) improvements to conversation flow and (2) addition of the "Moments of Crisis" conversation tree. Participant feedback also informed 17 recommendations for future smoking cessation chatbot developments. CONCLUSIONS: Feedback from end users and SCPs highlighted the importance of chatbot functionality, as this underpinned Quin's conversation design and relationality. The ready accessibility of accurate cessation information and impartial support that Quin provided was recognized as a key benefit for end users, the latter of which contributed to a feeling of accountability to the chatbot. Findings will inform the ongoing development of a mature prototype for clinical testing.

A mobile health intervention for emerging adults with regular cannabis use: A micro-randomized pilot trial design protocol.

BACKGROUND: Emerging adult (EA) cannabis use is associated with increased risk for health consequences. Just-in-time adaptive interventions (JITAIs) provide potential for preventing the escalation and consequences of cannabis use. Powered by mobile devices, JITAIs use decision rules that take the person's state and context as input, and output a recommended intervention (e.g., alternative activities, coping strategies). The mHealth literature on JITAIs is nascent, with additional research needed to identify what intervention content to deliver when and to whom. METHODS: Herein we describe the protocol for a pilot study testing the feasibility and acceptability of a micro-randomized trial for optimizing MiWaves mobile intervention app for EAs (ages 18-25; target N = 120) with regular cannabis use (≥3 times per week). Micro-randomizations will be determined by a reinforcement learning algorithm that continually learns and improves the decision rules as participants experience the intervention. MiWaves will prompt participants to complete an in-app twice-daily survey over 30 days and participants will be micro-randomized twice daily to either: no message or a message [1 of 6 types varying in length (short, long) and interaction type (rate message, rate message + click additional resources, rate message + fill in the blank/select an option)]. Participants recruited via social media will download the MiWaves app, and complete screening, baseline, weekly, post-intervention, and 2-month follow-up assessments. Primary outcomes include feasibility and acceptability, with additional exploratory behavioral outcomes. CONCLUSION: This study represents a critical first step in developing an effective mHealth intervention for reducing cannabis use and associated harms in EAs.

Usability of the BigO system in pediatric obesity treatment: A mixed-methods evaluation of clinical end-users.

Objective: To assess technical usability of the BigO app and clinical portal among diverse participants and explore the overall user experiences of both. Methods: Methods included technical usability testing by measuring the relative user efficiency score (RUS) for the app and measuring Relative User Efficiency (RUE) using the 'think aloud' method with the clinical portal. Qualitative approaches involved focus groups with adolescent app users and semi-structured one-to-one interviews with clinician participants. Thematic analysis was applied to analyze qualitative data. Participants: Clinical participants consisted of adolescents seeking treatment for severe obesity and were invited via telephone/face to face to attend technical usability testing and a focus group. Healthcare professionals (HCPs) and researchers using the BigO clinical portal interface were invited to participate in usability testing and semi-structured interviews. Results: From 14 families invited to attend, seven consented to join the study and four adolescents (mean age=13.8 (SD 0.8) years) participated. Additionally, six HCPs and one pediatric obesity researcher took part. RUS for adolescents indicated that the tasks required of them via myBigO app were feasible, and technically efficient. No user-related errors were observed during tasks. Technical barriers reported by adolescents included notifications of battery optimization, misunderstanding image annotation language, and compatibility challenges with certain phone models. RUS for the HCPs and researcher indicated that basic technical skills are a potential barrier for clinical portal use and qualitative findings revealed that clinical users wanted a logging option for monitoring goals and providing feedback on the portal. Conclusion: Our study provided valuable formative findings from clinical end-users in Ireland indicating that adolescents being treated for obesity rated myBigO app as usable, acceptable and that it may assist other key stakeholders to understand food marketing and to monitor dietary and physical activity behaviors. Several key suggestions for future iterations of the clinical portal were provided to enhance its value in pediatric obesity treatment.

Evaluation of a New Telemedicine System for Early Detection of Cardiac Instability in Patients With Chronic Heart Failure: Real-Life Out-of-Hospital Study.

BACKGROUND: For a decade, despite results from many studies, telemedicine systems have suffered from a lack of recommendations for chronic heart failure (CHF) care because of variable study results. Another limitation is the hospital-based architecture of most telemedicine systems. Some systems use an algorithm based on daily weight, transcutaneous oxygen measurement, and heart rate to detect and treat acute heart failure (AHF) in patients with CHF as early on as possible. OBJECTIVE: The aim of this study is to determine the efficacy of a telemonitoring system in detecting clinical destabilization in real-life settings (out-of-hospital management) without generating too many false positive alerts. METHODS: All patients self-monitoring at home using the system after a congestive AHF event treated at a cardiology clinic in France between March 2020 and March 2021 with at least 75% compliance on daily measurements were included retrospectively. New-onset AHF was defined by the presence of at least 1 of the following criteria: transcutaneous oxygen saturation loss, defined as a transcutaneous oxygen measurement under 90%; rise of cardiac frequency above 110 beats per minute; weight gain of at least 2 kg; and symptoms of congestive AHF, described over the phone. An AHF alert was generated when the criteria reached our definition of new-onset acute congestive heart failure (HF). RESULTS: A total of 111 consecutive patients (n=70 men) with a median age of 76.60 (IQR 69.5-83.4) years receiving the telemonitoring system were included. Thirty-nine patients (35.1%) reached the HF warning level, and 28 patients (25%) had confirmed HF destabilization during follow-up. No patient had AHF without being detected by the telemonitoring system. Among incorrect AHF alerts (n=11), 5 patients (45%) had taken inaccurate measurements, 3 patients (27%) had supraventricular arrhythmia, 1 patient (9%) had a pulmonary bacterial infection, and 1 patient (9%) contracted COVID-19. A weight gain of at least 2 kg within 4 days was significantly associated with a correct AHF alert (P=.004), and a heart rate of more than 110 beats per minute was more significantly associated with an incorrect AHF alert (P=.007). CONCLUSIONS: This single-center study highlighted the efficacy of the telemedicine system in detecting and quickly treating cardiac instability complicating the course of CHF by detecting new-onset AHF as well as supraventricular arrhythmia, thus helping cardiologists provide better follow-up to ambulatory patients.