Abstract
The paper proposes a glucose prediction model and hypoglycemia alarms technology based on CGMS. Method: By using kalman filter to smooth the glucose data from the CGMS, reducing noise interference; Then according to the non-stationary characteristics of glucose concentration signal ,Using adaptive autoregressive model (AR) glucose prediction model is established; Finally, the prediction model is applied to hypoglycemia alarms. Results: The prediction model can dynamically capture the changes of the glucose and predict glucose of 30 min ahead, RMSE、SSGPE were 5.069,5.276; And hypoglycemia can be timely detected.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
