LAUSR

Fitness and activity trackers are hugely popular wearable devices that monitor various health-related metrics, such as step count, heartbeat rate, or even oxygen saturation. Utilizing personal health information obtained by users’ personal trackers provides promising results in the fields of telemedicine and personal well-being. However, we face challenges such as data quality, privacy and compliance with standards and regulations. This paper addresses such challenges, with the focus on the last one. Semantic constraints for healthcare datatypes are defined to ensure compliance with standards, making the information medically valid and relevant. A process of semantic verification and Schematron-based validation is proposed. The validation process suggested in this paper will enable the data to be transferred and incorporated into a formal Electronic Health Record. The process is then verified using datasets containing various health-related data types. The aim is to integrate personal health data into Electronic Health Record, which forms a part of Central Health Information System. This would provide personalized medical services to patients and help physicians to make more informed decisions.