Long-term monitoring of personal health parameters for the prevention of cardiovascular diseases

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Networked consumer health devices, including activity trackers and sleep monitors, offer valuable insights into health parameters in real-life settings. Their connection to internet services enables innovative applications, yet challenges remain regarding the reliability of measurements and the integration of diverse data sources. Many health professionals view these devices as toys rather than effective tools. This work explores how smart health devices can function within a socio-technical system aimed at preventing cardiovascular diseases. A comprehensive concept is proposed, emphasizing the human element as both the consumer of health information and the producer of data through daily interactions with the devices. The study examines user interactions over time to assess their impact on measurement accuracy and the overall effectiveness of the preventative system. It also investigates the properties and quality of data from smart health devices in relation to application requirements, introducing a data quality model that encompasses accuracy, relevance, and availability. This model acknowledges the trade-offs influenced by user engagement with the devices and suggests strategies to balance these dimensions. Additionally, it identifies requirements for utilizing data in preventative applications and presents a conceptual framework for processing information from various smart health devices, ultimately facilitating interve