Sensor Data-Driven Intelligent Health Monitoring and Early Warning System

The development of science and technology is the continuous development of health monitoring technology, intelligent health monitoring has gradually. This paper describes the technical principles, application scenarios and development trends of sensor data based intelligent health monitoring and early warning system. As an emerging health management tool, sensor data-driven intelligent health monitoring and early warning system is gradually changing people's lifestyles and health concepts. First, a systematic overview of the historical development of sensor technology and its application in the medical field is presented, highlighting the importance of sensor technology in the medical field. Second, the process of the health monitoring and early warning system is described in detail, including the steps of data acquisition, data preprocessing, data analysis, and result application. Statistical analysis and machine learning algorithms are used in the data analysis stage to realize the assessment of user's health status and the prediction of disease risk; the result application stage enables users to keep abreast of their health status by displaying and updating data in real time, as well as generating detailed health reports. This paper takes heart disease prediction as an example, uses SVM algorithm to verify the effectiveness of the system prediction, and achieves better results in the test set. The idea of collaborative filtering push line algorithm is combined in the early warning part for disease warning. The system in this paper provides users with real-time and comprehensive health information, which can effectively prevent and reduce the risk of diseases. However, the system still faces challenges such as data privacy and security, data quality, scalability, etc. With the development of sensors and artificial intelligence technology, the future system continues to break through in these aspects.