Abstract-A method for preprocessing a time series of glucose measurements based on Kalman smoothing is presented. Given a glucose data time series that may be irregularly sampled, the method outputs an interpolated time series of glucose estimates with mean and variance. The method can provide homogenization of glucose data collected from different devices by using separate measurement noise parameters for differing glucose measurement equipment. We establish a link between the ISO 15197 standard and the measurement noise variance used by the Kalman smoother for Self Monitoring of Blood Glucose (SMBG) measurements. The method provides phaseless smoothing, and it can automatically correct errors in the original datasets like small fallouts and erroneous readings when surrounding data allows. The estimated variance can be used for deciding at which times the data are trustworthy. The method can be used as a preprocessing step in many kinds of glucose data processing and analysis tasks,

Freestyle Libre (FL) is a factory calibrated Flash Glucose Monitor (FGM). We investigated Mean Absolute Relative Difference (MARD) between Self Monitoring of Blood Glucose (SMBG) and FL measurements in the first day of sensor wear in 39 subjects with Type 1 diabetes. The overall MARD was 12.3%, while the individual MARDs ranged from 4% to 25%. Five participants had a MARD ≥ 20%. We estimated bias and lag between the FL and SMBG measurements. The estimated biases range from −1.8 mmol/L to 1.4 mmol/L, and lags range from 2 min to 24 min. Bias is identified as a main cause of poor individual MARDs. The biases seem to persist in days 2–7 of sensor usage. All cases of MARD ≥ 20% in the first day are eliminated by bias correction, and overall MARD is reduced from 12.3% to 9.2%, indicating that adding support for voluntary user-supplied bias correction in the FL could improve its performance.

are/were nurses at the Diabetes Laboratory who helped us through all the clamping procedures. Their professional, calm and friendly demeanor made experiment days much easier for both us and the patients. I can honestly say that every clamp procedure we did was enjoyable, they were truly a delight to work with. Gøril and Åsne deserve extra credit for also recruiting patients and keeping track of the paper work around this, preparing the clamp procedures and keeping track of all the different blood tests.All doctors and nurses involved in recruiting patients both at the outpatient diabetes clinic at Aker, and at the Norwegian Diabetics centre. Special thanks to Kirubalini Moorthy for tirelessly recruiting new patients when we struggled to reach our goal. Also thanks to the Norwegian journal for diabetes patients, "Diabetes", for making a small article that helped us in the recruitment process.All the nurses at the nephrology department's ward that helped us with blood glucose monitoring through the overnight stay before experiment days.Kristin Godang for helping us with measurements of adrenaline and noradrenaline. Jan Olav Høgetveit (my boss's boss), who was the person to give med a position for my civilian service many years ago, and is the reason why I work here at all. Since then he has been a good friend and colleague, and he and Christian together managed to get me back to the department in a PhDposition, and later in a permanent position, which basically means job security for life. It's like being blessed by the mafia, as long as I don't murder someone, I'm good.Geir Teigstad, the director of Oslo Hospital Services (my boss's boss's boss) for approving my position and being very supportive of our work at the R&D department. Level Glycaemic criteria/descriptionLevel 1 Glucose <70 mg/dL (3.9 mmol/L) and glucose ≥54 mg/dL (3.0 mmol/L)Level 2 Glucose <54 mg/dL (3.0 mmol/L) Level 3 A severe event characterized by altered mental and/or physical status requiring assistance