A Fully Implantable Subcutaneous Glucose Sensor Array: Enhanced Accuracy from Multiple Sensing Units and a Median-Based Algorithm

Abstract

Although continuous electrochemical glucose monitoring holds promise in the management of diabetes, its utility is limited in part because of error of unclear origin. The use of redundant glucose sensors in an array might reduce such error. We hypothesized that in a subcutaneously implanted array, a median-based continuous computation that excludes outlying data would lead to more accurate glucose measurement than averaging of all signals. Each rat was implanted with an array of four sensing units, and each unit transmitted data independently to an external monitoring device. Animals underwent perturbation of glucose by insulin infusions in diabetic animals and glucose infusions in nondiabetic animals, and in both, capillary glucose monitoring was performed frequently. Repeat glucose perturbation studies were performed every 1-2 weeks. We observed that a median-based technique, the Z-score with Median Absolute Deviation (ZMAD), consistently led to greater sensing accuracy as compared with signal averaging. The ZMAD technique yielded a correlation coefficient of 0.93, and 96% of values fell in the A and B regions of the Clarke error grid, demonstrating a high degree of accuracy of the unified signal. When tested in an implanted array of glucose sensors, a median-based technique (ZMAD) yields an accurate unified signal, and its accuracy is superior to signal averaging.

Continuous Glucose Monitoring: Real-Time Algorithms for Calibration, Filtering, and Alarms

“…Ward and colleagues 72 proposed a similar idea, but developed a sensor array with four implantable sensors. They used a medianbased algorithm to detect when one of the sensor signals is inconsistent with the other sensors.…”

Dynamic silver speciation as studied with fluorous-phase ion-selective electrodes: Effect of natural organic matter on the toxicity and speciation of silver

“…There have been few literature precedents with use of commercially available solid-state ISEs to study Ag + speciation (Benoit et al, 2013; Maurer-Jones et al, 2013b;Maurer et al, 2012; Peretyazhko et al, 2014; Sikora and Stevenson, 1988), possibly due to the common issue of solid state ISE biofouling in biological samples (biological molecules such as proteins adsorb strongly through sulfur groups to silver halide and sulfide electrodes) (Buhlmann et al, 1998; Chang et al, 1990; Kulpmann, 1989; Park et al, 1991). ISEs with polymeric sensing membranes suffer less from adsorption, but extraction of lipophilic biological interferents into their sensing membranes can still causing biofouling of these ISEs (Frost and Meyerhoff, 2002; Ward et al, 2003). In this work, we used ionophore-doped ISEs with fluorous sensing membranes that are less susceptible to biofouling effects.…”

An Implantable Subcutaneous Glucose Sensor Array in Ketosis‐prone Rats: Closed Loop Glycemic Control

“…Sensor glucose values were calculated in real time by taking all glucose values from the sensor array and calculating a unified glucose value using a median‐based Z ‐statistic (23). Specifically, this algorithm utilized a modified Z ‐score calculated for the array's glucose data set (obtained once per minute) from each of the four sensing anode units.…”