Non-invasive Blood Glucose Measurement System Research Articles

Non-invasive blood glucose concentration level estimation accuracy using ultra-wide band and artificial intelligence

Diabetes becomes a rapidly increasing global epidemic and getting serious health concern worldwide. There is no remedy except systematic management to keep blood glucose level under control. To achieve that regular glucose level monitoring is a routine task for a patient. This involves collection of blood physically from body with some discomfort and measuring using some device. To overcome this disadvantages and distress, non-invasive blood glucose measurement system is in demand. This article presents an ultra-wide band (UWB) microwave imaging and artificial intelligence based prospective solution to detect blood glucose concentration level non-invasively (without physical blood). The system consists of a pair of small UWB biomedical planar antenna, UWB transceiver as hardware and an artificial neural network with signal acquisition and processing interface as software module. The UWB signal with center frequency of 4.7 GHz was transmitted through ear lobe and forward scattering signals were received from other side. Characteristics features of received signal were extracted for pattern recognition and detection through deep artificial neural network. The system exhibits around 88% accuracy to detect glucose concentration in blood plasma. Besides, it is affordable, safe, user friendly and can be used with comfort in near future.

An Accurate Noninvasive Blood Glucose Measurement System Using Portable Near-Infrared Spectrometer and Transfer Learning Framework

Diabetes is considered one of the life-threatening diseases in the world, which needs regular monitoring of blood glucose levels. In this article, we developed a portable system that makes near-infrared spectroscopy (NIRS) technology available to non-professionals through a mobile application and a specially-made enclosure. It overcomes the shortcomings of traditional spectroscopy systems, such as large volume, high cost, complicated operation, and difficulty in online detection. To verify the feasibility of NIRS in noninvasive blood glucose concentration detection, after the pretreatment of the acquired original spectra, we compared two different feature extraction algorithms of synergy interval (Si) and genetic algorithm (GA). On this basis, two quantitative prediction models of partial least squares (PLS) and extreme learning machine (ELM) were established. The experimental results showed the model based on the combination of Si and GA and ELM (i.e., Si-GA-ELM model) as the most accurate among the selected models. At the same time, the prediction accuracy of the spectral waveband was higher than that of the full. To further overcome the difficulty of establishing a finite sample data model and reduce the influence of individual differences, the model transfer method TrAdaBoost was used to enhance the accuracy and stability of our model. The final experimental results show that the NIR spectrometer used is portable and light and can be encased as a handheld device form. Computation models combining machine learning and chemometric methods make the estimated blood glucose more feasible, which is an innovative work in noninvasive blood glucose measurement fields.

Near-Infrared Light Emitting Diode Based Non-Invasive Glucose Detection System.

Diabetes mellitus is a common disease that has affected people since antiquity. The complexity of diabetes mellitus lies in the fact that it requires continuous management in order to prevent serious complications. Various methods for managing diabetes mellitus through monitoring blood glucose levels have been studied and developed, and the most widely used method includes using an invasive blood glucose meter. Since the invasive blood glucose meter poses a major inconvenience for patients, in this study, we sought to develop a non-invasive blood glucose meter. We therefore proposed the development of a non-invasive blood glucose measurement system that is based on near-infrared spectroscopy. The system developed was composed of a light source for emitting different wavelengths, a light detector unit, and a computing system for recording signals. A prepared glucose solution was injected into a quartz cuvette and light at 780-1650 nm was emitted to pass through the cuvette. The degree of reaction was determined by recording the change in wavelength. The wavelength band used for the experiment was 780-1000 nm and the resolution was 20 nm. The glucose concentration was determined to be between 50 to 400 mg/dl compared to the normal range of 80 to 120 mg/dl. By examining which wavelength bands specifically reacted with glucose, we observed that the wavelength bands that decreased or increased in response to the glucose concentration were at 780 nm and 940 nm. For wavelength bands at 1000 nm or above, light was also absorbed by water and therefore it was difficult to distinguish the results. The most reliable wavelength band was at 940 nm with an R² of 0.9806. In conclusion, the near-infrared light emitting diode based non-invasive glucose detection system performed well and is expected to be a superior method for monitoring blood glucose levels in diabetes mellitus.

Levenberg–Marquardt-Based Non-Invasive Blood Glucose Measurement System

ABSTRACTThe present work focuses on the development of non-invasive blood glucose measurement device to revolutionize diabetes management and reduce severe complications associated with it. A low cost, painless and non-invasive blood glucose measurement system is designed using near-infrared (NIR) LED and four photodiodes for the purpose. NIR light emitted by LED passes through the skin and is detected by photodiodes after attenuation. The detector converts the attenuated light into a voltage signal. The interference due to background noise generated by human skin is removed by taking floating or internal reference. The voltage signal obtained from the photodiodes is calibrated using Levenberg–Marquardt-based Artificial Neural Network to obtain the glucose concentration. The accuracy of proposed prototype was examined by comparing non-invasively predicted data with invasively measured reference data. It is observed that all measurements lie in A and B zones of Clarke error grid and thus clinically accurate.

NIR Based Non-Invasive Blood Glucose Measurement

Objectives: This paper describes the method of measurement of glucose concentration in the human blood non-invasively using the near infrared optical technique. Methods/Analysis: In recent medical practice, the concentration of glucose in blood is measured using an invasive techniques which generally involves puncturing finger. In generic few ml of blood whereas in recent practice less than a drop of blood is taken out and passed through the standard chemical tests to measure glucose concentration. These methods are expensive as well as painful. The frequent finger puncturing causes calluses on the skin and also increases the risk of spreading infectious diseases. Findings: So, the development of a non-invasive blood glucose measurement system will be boon to the diabetic patients. This paper describes the method of blood sugar measurement in the human blood non-invasively using the painless near infrared based optical technique. The designed system consists of LED emitting signals of 940 nm wavelength. These optical signals are sent through the fingertip and reflected signals are detected by phototransistor placed beside the LED. The glucose concentration in the blood is determined by analyzing the variation in the intensity of received signal obtained after reflection. The results obtained from the designed system shows the feasibility of using NIR based non-invasive method for the measurement of blood glucose. Applications/Improvements: The described system is majorly useful for diabetic patients. The measurement accuracy of the proposed system can be improved by incorporating it with noise filtering techniques.

8I-19 位相シフト法を用いた光センサによる非侵襲血糖値計測システムの試作開発(OS-12 バイオヒート・マストランスファー(2))

8I-19 位相シフト法を用いた光センサによる非侵襲血糖値計測システムの試作開発(OS-12 バイオヒート・マストランスファー(2))