Adquisición, análisis y transmisión de información a través de una aplicación móvil médica a una base de datos utilizando el estándar HL7

Abstract

Medical information systems in the world use the HL7 standard to communicate, this is a set of standards that facilitates the exchange of information from any medical device, whether it is a computer or information system. This project proposes the development of a mobile application that acquires the patient's cardiac information from sensors and transmits it through a mobile device using the HL7 standard, to a database where from estimation-prediction, using Machine Learning, it is predicted whether there are risks to the patient's health and thus avoid medical fatalities that may occur in the long or short term depending on the prediction made. The information is acquired in the App, transmitted through the cellular mobile network and received in the server where it will be compared with a dataset that includes the patient's normal vital signs. The system will indicate if the data obtained are within the ideal ranges and the health professional can proceed with the corresponding treatment to avoid fatalities. In the healthcare field, research has been carried out with the intention of acquiring patient data and transmitting it using this standard, but there is no low-cost project in which the prediction of possible alterations in the patient is performed using Machine Learning and the HL7 standard together. In addition, the way in which the data is acquired is generally using sensors that are uncomfortable for the person who is going to use the system. For this project it is planned to use sensors that the patient can carry without inconvenience, the App can read data from any sensor that is connected to the interface, the main sensor that will be used is the ECG sensor for its great effectiveness when taking data from the patient since the movement does not alter the information acquired by the sensor as other devices do.