The Model of near infrared sensor output voltage as a function of glucose concentration in solution

Julian, Engelin Shintadewi; Prawiroredjo, Kiki; Tjahjadi, Gunawan

doi:10.1109/qir.2017.8168471

Cited by 7 publications

(3 citation statements)

References 5 publications

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“…The 1450 nm sensor output voltages in Table 2 show that at the output voltages tend to lower when the glucose concentration is higher. This result is consistent with our previous result [21] and the other team results [13,14,22].…”

Section: Results and Analysissupporting

confidence: 94%

Comparative study of 940 nm and 1450 nm near infrared sensor for glucose concentration monitoring

Prawiroredjo

Julian

2019

TELKOMNIKA

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In order to manage their blood glucose level, diabetics have to test their blood glucose level regularly. Unfortunately, the current blood glucose measurement device is uncomfortable, painful, event costly for the diabetics; therefore, a lot of effort is given to develop a noninvasive blood glucose meter. We studied the potential of two near infrared wavelength i.e. 1450 and 940 nm as glucose sensor. Each sensor consists of a light emitting diode (LED) as light source, a photodiode that is sensitive to that wavelength, transimpedance amplifier, and filters. An acrylic box size 5cmx1cmx5cm was used as glucose solution container. The LED and photodiode were located at each side of box width, at 1 cm distance. The container was than filled with various concentrations of glucose solution, and the sensor output voltages were measured. The results show that for glucose concentration 0 to 500 mg/dl, the output voltages of the 1450 nm sensor tend to lower when the glucose concentration is higher, therefore it has the potential to be used as glucose sensor. Different result is obtained from the 940 nm sensor where the output voltages were remained the same when the glucose concentration was varied.

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Section: Results and Analysissupporting

confidence: 94%

Comparative study of 940 nm and 1450 nm near infrared sensor for glucose concentration monitoring

Prawiroredjo

Julian

2019

TELKOMNIKA

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“…Reddy et al [ 21 ] designed a device to monitor blood glucose level using near infrared sensors. Julian et al [ 22 ] also proposed a near infrared sensor to measure glucose concentration. Pai et al [ 23 ] implemented FPGA-based glucose monitoring with photoacoustic signal amplitude.…”

Section: Literature Reviewmentioning

confidence: 99%

Hyperglycemia Identification Using ECG in Deep Learning Era

Cordeiro

Karimian

Park

2021

Sensors

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A growing number of smart wearable biosensors are operating in the medical IoT environment and those that capture physiological signals have received special attention. Electrocardiogram (ECG) is one of the physiological signals used in the cardiovascular and medical fields that has encouraged researchers to discover new non-invasive methods to diagnose hyperglycemia as a personal variable. Over the years, researchers have proposed different techniques to detect hyperglycemia using ECG. In this paper, we propose a novel deep learning architecture that can identify hyperglycemia using heartbeats from ECG signals. In addition, we introduce a new fiducial feature extraction technique that improves the performance of the deep learning classifier. We evaluate the proposed method with ECG data from 1119 different subjects to assess the efficiency of hyperglycemia detection of the proposed work. The result indicates that the proposed algorithm is effective in detecting hyperglycemia with a 94.53% area under the curve (AUC), 87.57% sensitivity, and 85.04% specificity. That performance represents an relative improvement of 53% versus the best model found in the literature. The high sensitivity and specificity achieved by the 10-layer deep neural network proposed in this work provide an excellent indication that ECG possesses intrinsic information that can indicate the level of blood glucose concentration.

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“…For spectrophotometric experiments, Beer Lambert's law is applicable to measure the attenuation of light that is proportional to the level of glucose solution, thickness of the sample and molar extinction coefficient. The (1) shows the attenuation A according to Beer Lamberts law [19].…”

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confidence: 99%

Effects of noises on near infrared sensor for blood glucose level measurement

Prawiroredjo

Julian

2020

TELKOMNIKA

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This paper proposed the method of measuring glucose level in solution using near infrared light (NIR) and photodiode sensor. We studied noises that occurred on the output signal of NIR sensor in three different room conditions in order to know the effects on this sensor output voltage stability. The sensor's circuit consisted of a 1450 nm NIR light emitting diode, a photodiode as the receiver, transimpedance amplifier, a notch filter, and a 4 th order low pass filter. The results indicated that sunlight passing through windows was the most influencing factor caused the unstable sensor output voltage. Filters removed the effective voltages and the average sensor output voltages from the three rooms were 4.6825 V for air media, 2.2809 V for water media and 2.3368 V for glucose solution media. The output voltages tended to increase for one-hour measurement about 10 to 40 mV for air media, 40 to 90 mV for water media and 30 to 80 mV for glucose solution media. This sensor could only be used in a short time and suitable in a room without sunlight. Based on the voltage difference of the average sensor output voltage with water and glucose solution media, the sensor had the potential to be a blood glucose level meter.

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The Model of near infrared sensor output voltage as a function of glucose concentration in solution

Cited by 7 publications

References 5 publications

Comparative study of 940 nm and 1450 nm near infrared sensor for glucose concentration monitoring

Comparative study of 940 nm and 1450 nm near infrared sensor for glucose concentration monitoring

Hyperglycemia Identification Using ECG in Deep Learning Era

Effects of noises on near infrared sensor for blood glucose level measurement

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