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Personalized IoT-based Physical Activity Monitoring System for Heart Failure Patients
NCT07171372
Current literature emphasizes the importance of increasing physical activity, ensuring its continuity, and reducing sedentary behaviors in patients with heart failure (HF). Many patients are referred to exercise-based rehabilitation programs following hospital discharge or an acute cardiac event. Although the benefits of these programs on cardiovascular health have been consistently demonstrated, adherence to recommended exercise regimens remains a major challenge. Previous studies indicate that through repeated and effective national health policies, large segments of society have adopted strategies to promote physical activity. However, despite the availability of various exercise and physical activity protocols, patients with HF remain prone to sedentary behaviors due to physical limitations, psychosocial factors, and lack of motivation.
Healthcare professionals play a critical role in promoting physical activity among HF patients, as encouraging participation in structured programs may improve health outcomes and reduce sedentary behaviors. Therefore, developing new and effective strategies to increase physical activity levels in this population is essential. Such strategies should focus on tailoring interventions to individual needs and health conditions, implementing long-term monitoring and support mechanisms to ensure continuity, and integrating technological innovations (e.g., smart wristbands, mobile applications) through user-friendly interfaces.
This study aims to improve physical activity levels and reduce sedentary behaviors among HF patients by designing a personalized, Internet of Things (IoT)-based physical activity monitoring system (IoT-HFActive). The central innovation of this system lies in its ability to generate personalized physical activity goals for the first time through automated mathematical algorithms that process real-time data collected from wearable devices.
During supervised exercise sessions, heart rate measurements obtained via smart wristbands will be used to calculate individual heart rate reserves (HRR). Based on these data, personalized activity goals will be established, including target heart rate zones, exercise intensity, and weekly activity duration. Subsequently, the server system will continuously monitor participants' daily physical activity levels and, through a specifically developed mobile application, provide real-time visualization of the results on participants' smartphones.
The system is designed with multiple functional components. Beyond setting personalized, patient-centered physical activity goals, it will also monitor adherence, deliver behavioral support techniques, and adapt targets over time. Participants will receive periodic individualized feedback, rewards such as virtual badges, progress visualizations, and video-supported motivational messages to reinforce engagement. Repeated time-series measurements of physical activity will allow dynamic recalibration of goals based on participants' performance.
In addition, participants will be able to track their personal progress, receive visual and video-based feedback, and observe how their activity behavior improves over time. These features are expected to strengthen motivation and adherence to exercise programs. Throughout the study, all procedures will be designed to align with participants' abilities and will be supported by user-friendly, intuitive interfaces to ensure accessibility and usability.
By combining personalized physical activity goals, real-time monitoring, and behaviorally informed feedback strategies, this study introduces an innovative, patient-centered IoT-based approach. The IoT-HFActive system is expected to address the long-standing challenge of exercise adherence in HF patients and to provide valuable evidence for the integration of technological innovations into cardiac rehabilitation services.
Heart FailureReduced Ejection Fraction Heart Failure
Abant Izzet Baysal University82 participantsStarted Dec 2025 