Multivariate prediction of subcutaneous glucose concentration in type 1 diabetes patients based on support vector regression.

Abstract Data-driven techniques have recently drawn significant interest in the predictive modeling of subcutaneous (s.c.) glucose concentration in type 1 diabetes. In this study, the s.c. glucose prediction is treated as a multivariate regression problem, which is addressed using support vector regression (SVR). The proposed method is based on variables concerning: (i) the s.c. glucose profile, (ii) the plasma insulin concentration, (iii) the appearance of meal-derived glucose in the systemic circulation, and (iv) the energy expenditure during physical activities. Six cases corresponding to different combinations of the aforementioned variables are used to investigate the influence of the input on the daily glucose prediction. The proposed method is evaluated using a dataset of 27 patients in free-living conditions. 10-fold cross validation is applied to each dataset individually to both optimize and test the SVR model. In the case where all the input variables are considered, the average prediction errors are 5.21, 6.03, 7.14 and 7.62 mg/dl for 15, 30, 60 and 120 min prediction horizons, respectively. The results clearly indicate that the availability of multivariable data and their effective combination can significantly increase the accuracy of both short-term and long-term predictions

Circuits and systems for biosensing with microultrasound

Ultrasound imaging is a well-established, noninvasive imaging modality used in many clinical procedures. New developments in high-resolution microultrasound are well suited to biosensing, including applications such as material characterisation, biometrics and chemical sensing. Electronic system design for ultrasound and microultrasound is most commonly associated with the use of piezoelectric transducers to generate and sense the ultrasonic pressure waves. This chapter covers the basics of ultrasound physics and piezoelectric transducers as well as their context within the larger field of biosensing. An example of an ultrasound imaging system is presented, and the availability and suitability of commercial solutions are discussed in comparison to individual approaches seen in the research domain. Finally, possible variations in ultrasound device characteristics are discussed, and the impact of these and overall system concerns on ASIC development is considered