Discharge follow-up refers to the method of observation and treatment of patients treated in the hospital after discharge, in which medical workers continue to pay attention to the changes of patients’ condition and rehabilitation, and continue to guide patients’ rehabilitation. Encourage the continuous improvement of hospital service quality and patient satisfaction. An optimized design scheme for an intelligent patient tracking system based on the Internet of Things and sensor technology has been proposed. The Kalman filtering algorithm in sensor technology is applied to improve the patient tracking problem of the IoT intelligent tracking system constructed in this paper, thereby expanding the scope and accuracy of the system. Finally, the simulation test and analysis are carried out. The simulation results show that, in the simulated follow-up scenarios for neurology patients (including home rehabilitation environments and multi-target intersection scenes similar to community activity areas), the algorithm is 10.22% more accurate than the traditional algorithm.The simulation results show that the algorithm is 10.22% more accurate than the traditional algorithm. The results show that the intelligent follow-up system is reasonable and practical, and basically meets the requirements of the follow-up management of specialized cases in the Neurology Department of our hospital. The development and research of intelligent follow-up technology for neurology patients based on sensor technology has important practical significance for guiding the follow-up rehabilitation treatment of neurology diseases and patients.
Zhang et al. (Tue,) studied this question.