Wireless implantable electronic platform for blood glucose level monitoring

Valdastri, Pietro; Susilo, E.; Forster, Thilo; Strohhöfer, C.; Menciassia, A.; Dario, P.

doi:10.1016/j.proche.2009.07.313

Cited by 12 publications

(7 citation statements)

References 3 publications

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“…This system was composed of the chronoamperometric glucose biosensor, potentiostat circuit and ISO 18000-3 (The passive 13.56 MHz RFID standard) transponder interface and the average sensitivity of the glucose biosensor was about 0.75 μA/(mM/dl). Valdastri et al [36] proposed the wireless programmable electronic platform for the monitoring of the blood glucose and the wireless sensing system based on the IEEE 802.15.4-2003 protocol. Furthermore, because of the use of the ZigBee Transceiver, the wireless sensing system allowed extremely low power bidirectional telemetry.…”

Section: B Wireless Sensing Measurement Of Ruo 2 /Graphene/ Magneticmentioning

confidence: 99%

Dynamic and Wireless Sensing Measurements of Potentiometric Glucose Biosensor Based on Graphene and Magnetic Beads

et al. 2015

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In this paper, the arrayed flexible pH sensor and glucose biosensor modified by magnetic beads and graphene were proposed. The ruthenium dioxide (RuO 2 ) sensing films were deposited by radio frequency sputtering system and the screenprinted technique was used to construct the silver conducting wires and insulation layer of the RuO 2 electrodes. In order to enhance performance of the pH sensor and glucose biosensor, the microfluidic device had been utilized and developed. In the measurement processes, the different pH and glucose solutions were investigated in various flow rates. According to the experimental results, the average sensitivity of the pH sensor was enhanced from 52.280 to 57.981 mV/pH and the average sensitivity of the RuO 2 /graphene/magnetic bead-GO x -Nafion glucose biosensor was enhanced from 10.628 to 13.541 mV/mM. With regard to the wireless sensing measurements, the wireless sensing system which complied the ZigBee standard was employed to transmit the signals of the pH or glucose measurements in this investigation, and the system consisted of the Xbee device, Arduino Mega 2560, readout circuit, pH or glucose biosensor and computer. According to the experimental results, the average sensitivity and linearity of the pH sensor were 51.063 mV/pH and 0.988, respectively, and the average sensitivity and linearity of the RuO 2 /graphene/magnetic bead-GO x -Nafion glucose biosensor were 11.005 mV/mM and 0.995, respectively.

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Section: B Wireless Sensing Measurement Of Ruo 2 /Graphene/ Magneticmentioning

confidence: 99%

Dynamic and Wireless Sensing Measurements of Potentiometric Glucose Biosensor Based on Graphene and Magnetic Beads

et al. 2015

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“…Engineering of advanced CMOS-based circuits to attain extreme miniaturization and reduce the overall power consumption (McKean and Gough 1988; Shults, Rhodes et al 1994; Haider, Islam et al 2007; Serra, Rocchitta et al 2007; Zhang, Haider et al 2007; Ahmadi and Jullien 2009; Bolomey, Meurville et al 2009; Valdastri, Susilo et al 2009). …”

Section: Introductionmentioning

confidence: 99%

A miniaturized transcutaneous system for continuous glucose monitoring

Croce

Vaddiraju

Kondo

et al. 2012

Biomed Microdevices

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Implantable sensors for continuous glucose monitoring hold great potential for optimal diabetes management. This is often undermined by a variety of issues associated with: (1) negative tissue response; (2) poor sensor performance; and (3) lack of device miniaturization needed to reduce implantation trauma. Herein, we report our initial results towards constructing an implantable device that simultaneously address all three aforementioned issues. In terms of device miniaturization, a highly miniaturized CMOS (complementary metal-oxide-semiconductor) potentiostat and signal processing unit was employed (with a combined area of 0.665 mm2). The signal processing unit converts the current generated by a transcutaneous, Clark-type amperometric sensor to output frequency in a linear fashion. The Clark-type amperometric sensor employs stratification of five functional layers to attain a well-balanced mass transfer which in turn yields a linear sensor response from 0 to 25 mM of glucose concentration, well beyond the physiologically observed (2 to 22 mM) range. In addition, it is coated with a thick polyvinyl alcohol (PVA) hydrogel with embedded poly(lactic-co-glycolic acid) (PLGA) microspheres intended to provide continuous, localized delivery of dexamethasone to suppress inflammation and fibrosis. In vivo evaluation in rat model has shown that the transcutaneous sensor system reproducibly tracks repeated glycemic events. Clarke’s error grid analysis on the as –obtained glycemic data has indicated that all of the measured glucose readings fell in the desired Zones A & B and none fell in the erroneous Zones C, D and E. Such reproducible operation of the transcutaneous sensor system, together with low power (140 μW) consumption and capability for current-to-frequency conversion renders this a versatile platform for continuous glucose monitoring and other biomedical sensing devices.

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“…Noninvasive techniques that measure glucose look for variables that substitute blood as the main element, the aim is also to make the system portable for the patient. One of the first efforts was based on the principle of detecting the change in fluorescence resonance energy transfer efficiency of a protein synthesized as a function of analyte concentration [9]. Technologies such as GSM (global system for mobile communications) have been used in glucose monitoring.…”

Section: Related Workmentioning

confidence: 99%

An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications

et al. 2020

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Diabetes mellitus (DM) is a metabolic disorder characterized by blood glucose levels above normal limits. The impact of this disease on the population has increased in recent years. It is already a public health problem worldwide and one of the leading causes of death. Recently, several proposals have been developed for better and regular monitoring of glucose. However, theses proposals do not discard erroneous readings and they are not able to anticipate a critical condition. In this work, we propose an algorithm based on the double moving average supported by an IoT architecture to prevent possible complications in elderly patients. The algorithm uses historical readings to construct a series. Given a number of periods, it is possible to calculate averages of different subsets and trends for the next periods and, in this way, the prognosis is obtained. With the prognosis, it is possible to notify the doctor and relatives in advance about a possible critical condition in the patient. The aim of our work is to validate the architecture and prognosis algorithm used for elderly persons. Tests of the algorithm and the architecture were performed with different readings and it was shown that the system generated corresponding notifications before the glucose values were higher than those defined by the WHO (World Health Organization), thus avoiding unnecessary alarms.

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Wireless implantable electronic platform for blood glucose level monitoring

Cited by 12 publications

References 3 publications

Dynamic and Wireless Sensing Measurements of Potentiometric Glucose Biosensor Based on Graphene and Magnetic Beads

Dynamic and Wireless Sensing Measurements of Potentiometric Glucose Biosensor Based on Graphene and Magnetic Beads

A miniaturized transcutaneous system for continuous glucose monitoring

An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications

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