Multi-sensor blind recalibration in mHealth applications

This paper considers the problem of self-calibration of multi-sensor systems for health care cyber-biological systems, such as closed-loop glucose control. The recalibration method is performed periodically in the cloud resulted in significant advantages over traditional methods, including increased on-line accessibility and fast automated recovery from failures. Since the size of dataset has direct impact on the recalibration quality, we use cloud database which let us have a more complete recalibration dataset compared to limited on-board logging at different times and situations. Three methods are presented and evaluated in terms of accuracy and time. The proposed Minimum Mean Square Error (MMSE) recalibration method delivers the superior precision compared to other two techniques which are based on average and correlation. While all these approaches are generic and applicable to different medical multi-sensor systems, the experimental results are evaluated on temperature sensors due to their simple and reliable setup.