HI-Shaped Antenna for Non-Invasive Diabetes Measurement and Monitor Fluctuating Diabetes
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Abstract
The HI antenna senses the human pancreas dielectric radiation for diabetic measurement. Existing passive sensor antennas sense the dielectric radiation from the pancreas region at frequencies of 402.5 MHz and 2.4 GHz for a relative permittivity of 61.2155 and 57.201, respectively. The proposed antenna senses the dielectric properties of diabetic-affected pancreas, such as low and high-fat diabetic pancreas, in the frequency range between 1.5 GHz and 3 GHz. The relative permittivity of the diabetic pancreas is in the range of 48.235 to 65.508. The proposed antenna can sense the diabetic range between 70 mg/dl and 475 mg/dl based on a change in dB level, whereas the existing diabetic sensing antenna measures the diabetic level based on resonance frequency. The resonance-frequency-based diabetic measurement shows inaccurate results. The HI antenna senses pancreas radiation effectively because of the shape and size of its slot, which covers the pancreas region of the human body without generating noise due to the crumbling effect during pancreas dielectric radiation acquisition. The proposed HI-shaped antenna is mounted in different parts of the human body, such as the hand, finger, stomach, and pancreas, for measuring fluctuating diabetes. Based on the experimental results of the proposed HI-shaped antenna, the pancreas is in an optimal location among the various parts of the body. The proposed HI-shaped antenna-based dielectric signal statical values were correlated with diabetic laboratory values for prediction of the diabetic value. The proposed antenna measures the fluctuation in diabetes with 85% accuracy
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References
“International Diabetes Federation (IDF): Diabetes complications accessed: 2020-02-06,” https://www.idf.org/aboutdiabetes/complications.
“CoG - Glucometer,” https://www.cnogacare.co/.
“Gluco-Wise,” http://gluco-wise.com/.
“GlucoTrack,” http://www.glucotrack.com/.
“iQuickIt Saliva Analyzer,” https://www.indiegogo.com/projects/iquickit saliva analyzer#/.
“Contact Lens,” https://www.webeyeclinic.com/smart contact-lenses/smart-contact-lens-that-measure glucose.
“Noviosense,” https://noviosense.com/.
Y. Kusunoki et al., “Evaluation of blood glucose fluctuation in Japanese patients with type 1 diabetes mellitus by self -monitoring of blood glucose and continuous glucose monitoring,” Diabetes Res Clin Pract, vol. 108, no. 2, pp. 342–349, May 2015, DOI: 10.1016/j.diabres.2015.01.040.
S. Templer, “Closed-Loop Insulin Delivery Systems: Past, Present, and Future Directions,” Front Endocrinol (Lausanne), vol. 13, Jun. 2022, DOI: 10.3389/fendo.2022.919942.
D. Sladić Rimac et al., “The Association of Personality Traits and Parameters of Glycemic Regulation in Type 1 Diabetes Mellitus Patients Using isCGM,” Healthcare, vol. 10, no. 9, p. 1792, Sep. 2022, DOI: 10.3390/healthcare10091792.
L. Olçomendy et al., “Towards the Integration of an Islet-Based Biosensor in Closed-Loop Therapies for Patients With Type 1 Diabetes,” Front Endocrinol (Lausanne), vol. 13, Apr. 2022, DOI: 10.3389/fendo.2022.795225.
S. Kumar Das, K. K. Nayak, P. R. Krishnaswamy, V. Kumar, and N. Bhat, “Review Electrochemistry and Other Emerging Technologies for Continuous Glucose Monitoring Devices,” ECS Sensors Plus, vol. 1, no. 3, p. 031601, Sep. 2022, DOI:10.1149/2754-2726/ac7abb.
I. Ahmed et al., “Recent advances in optical sensors for continuous glucose monitoring,” Sensors & Diagnostics, 2022, DOI: 10.1039/D1SD00030F.
S. Kumar, G. Soldatos, S. Ranasinha, H. Teede, and M. Pallin, “Continuous glucose monitoring versus self-monitoring of blood glucose in the management of cystic fibrosis related diabetes: A systematic review and meta-analysis,” Journal of Cystic Fibrosis, Jul. 2022, DOI: 10.1016/j.jcf.2022.07.013.
A. G. A. Aggidis, J. D. Newman, and G. A. Aggidis, “Investigating pipeline and state of the art blood glucose biosensors to formulate next steps,” Biosens Bioelectron, vol. 74, pp. 243–262, Dec. 2015, DOI: 10.1016/j.bios.2015.05.071.
V. N. Shah, L. M. Laffel, R. P. Wadwa, and S. K. Garg, “Performance of a Factory-Calibrated Real-Time Continuous Glucose Monitoring System Utilizing an Automated Sensor Applicator,” Diabetes Technol Ther, vol. 20, no. 6, pp. 428–433, Jun. 2018, DOI: 10.1089/dia.2018.0143.
C. Limban et al., “Synthesis and Characterization of New Fluoro/Trifluoromethyl-Substituted Acylth iourea Derivatives with Promising Activity against Planktonic and Biofilm-Embedded Microbial Cells,” Processes, vol. 8, no. 5, p. 503, Apr. 2020, DOI: 10.3390/pr8050503.
S. A. Siddiqui, Y. Zhang, J. Lloret, H. Song, and Z. Obradovic, “Pain-Free Blood Glucose Monitoring Using Wearable Sensors: Recent Advancements and Future Prospects,” IEEE Rev Biomed Eng, vol. 11, pp. 21–35, 2018, DOI: 10.1109/RBME.2018.2822301.
M. Baghelani, Z. Abbasi, M. Daneshmand, and P. E. Light, “Non-invasive continuous-time glucose monitoring system using a chipless printable sensor based on split ring microwave resonators,” Sci Rep, vol. 10, no. 1, p. 12980, Dec. 2020, DOI: 10.1038/s41598-020-69547-1.
N. Ahmadian, A. Manickavasagan, and A. Ali, “Comparative assessment of blood glucose monitoring techniques: a review,” J Med Eng Technol, pp. 1– 10, Jul. 2022, DOI: 10.1080/03091902.2022.2100496.
R. H. Yu, S. Y. Rhee, and K. H. Kim, “Basic Study on Measurement of Return Loss and Smith Chart Change Using Microstrip Patch Antenna with Concentration Transition for Non-invasive Blood Glucose Measurement,” Journal of Electrical Engineering and Technology, 2022, DOI: 10.1007/s42835- 022-01290-1.
A. E. Omer et al., “Multiple-Cell Microfluidic Dielectric Resonator for Liquid Sensing Applications,” IEEE Sens J, vol. 21, no. 5, pp. 6094–6104, Mar. 2021, DOI: 10.1109/JSEN.2020.3041700.
S. Raj, S. Tripathi, G. Upadhyay, S. S. Tripathi, and V. S. Tripathi, “An Electromagnetic Band Gap-Based Complementary Split Ring Resonator Loaded Patch Antenna for Glucose Level Measurement,” IEEE Sens J, vol. 21, no. 20, pp. 22679–22687, Oct. 2021, DOI: 10.1109/JSEN.2021.3107462.
V. V. Deshmukh and S. S. Chorage, “Non-invasive determination of blood glucose level using narrow band microwave sensor,” J Ambient Intell Humaniz Comput, 2021, DOI: 10.1007/s12652-021-03105-z.
M. el Gharbi, R. Fernández-García, and I. Gil, “Textile antenna-sensor for in vitro diagnostics of diabetes,” Electronics (Switzerland), vol. 10, no. 13, Jul. 2021, DOI: 10.3390/electronics10131570.
S. Raj, P. Tripathi, N. Kishore, S. S. Tripathi, and V. S. Tripathi, “A novel Antenna design for Non-Invasive Blood Glucose Measurement and its Sensitivity Optimization using ANN,” IEEE Access, pp. 355–358, Feb. 2020, DOI: 10.1109/ICE348803.2020.9122876.
A. E. Omer et al., “Non-Invasive Real-Time Monitoring of Glucose Level Using Novel Microwave Biosensor Based on Triple-Pole CSRR,” IEEE Trans Biomed Circuits Syst, 2020, DOI: 10.1109/TBCAS.2020.3038589.
S. K. Koul and P. Kaurav, “Non-invasive Sub Terahertz Blood Glucose Measurement,” 2022, pp. 93–126. DOI: 10.1007/978-981-19-3140-6_4.
M. Sun et al., “A Flexible Microfluidic Chip-Based Universal Fully Integrated Nanoelectronic System with Point-of-Care Raw Sweat, Tears, or Saliva Glucose Monitoring for Potential Noninvasive Glucose Management,” Anal Chem, vol. 94, no. 3, pp. 1890–
, Jan. 2022, DOI: 10.1021/acs.analchem.1c05174.
J. Al-Nabulsi et al., “Non-invasive sensing techniques for glucose detection: a review,” Bulletin of Electrical Engineering and Informatics, vol. 11, no. 4, pp. 1926–1937, Aug. 2022, DOI: 10.11591/eei.v11i4.3584.
V. V. Deshmukh and S. S. Chorage, “Non-invasive determination of blood glucose level using narrow band microwave sensor,” J Ambient Intell Humaniz Comput, Mar. 2021, DOI: 10.1007/s12652-021-03105- z.
M. Adeel, Md. M. Rahman, I. Caligiuri, V. Can zonieri, F. Rizzolio, and S. Daniele, “Recent advances of electrochemical and optical enzyme-free glucose sensors operating at physiological conditions,” Biosens Bioelectron, vol. 165, p. 112331, Oct. 2020, DOI: 10.1016/j.bios.2020.112331.
C. Jang, J.-K. Park, H.-J. Lee, G.-H. Yun, and J.- G. Yook, “Non-Invasive Fluidic Glucose Detection Based on Dual Microwave Complementary Split Ring Resonators With a Switching Circuit for Environmental Effect Elimination,” IEEE Sens J, vol. 20, no. 15, pp. 8520–8527, Aug. 2020, DOI:10.1109/JSEN.2020.2984779.
S. Saha et al., “Evaluation of the sensitivity of transmission measurements at millimeter waves using patch antennas for non-invasive glucose sensing,” IEEE Access, pp. 1–4, Apr. 2016, DOI: 10.1109/EuCAP.2016.7481304.
T. Arakawa et al., “Mouth guard type biosensor ‘cavitous sensor’ for monitoring of saliva glucose with telemetry system,” IEEE Access, pp. 46–49, Dec. 2015, DOI: 10.1109/ICSensT.2015.7438362.
D. Guo, D. Zhang, L. Zhang, and G. Lu, “Non invasive blood glucose monitoring for diabetics by means of breath signal analysis,” Sens Actuators B Chem, vol. 173, pp. 106–113, Oct. 2012, DOI: 10.1016/j.snb.2012.06.025.
A. E. Omer, S. Gigoyan, G. Shaker, and S. Safavi-Naeini, “WGM-Based Sensing of Characterized Glucose- Aqueous Solutions at mm-Waves,” IEEE Access, vol. 8, pp. 38809–38825, 2020, DOI: 10.1109/ACCESS.2020.2975805.
S. Z. A. Jalil, H. Abdullah, and M. N. Taib, “Human body radiation wave analysis on the human torso,” IEEE Access, pp. 22–27, May 2015, doi: 10.1109/ICBAPS.2015.7292211.
S.-A. Zhou and M. Uesaka, “Bioelectrodynamics in living organisms,” Int J Eng Sci, vol. 44, no. 1–2, pp. 67–92, Jan. 2006, DOI: 10.1016/j.ijengsci.2005.11.001.
M. Sebakor, “Layer 2 Path Evaluation System using Machine Learning,” ECTI Transactions on Electrical Engineering, Electronics, and Communications, vol. 19, no. 3, Sep. 2021, DOI: 10.37936/ectieec.2021193.244943.
T. bin Shams, Md. S. Hossain, Md. F. Mahmud, Md. S. Tehjib, Z. Hossain, and Md. I. Pramanik, “EEG-based Biometric Authentication Using Machine Learning: A Comprehensive Survey,” ECTI Transactions on Electrical Engineering, Electronics, and Communications, vol. 20, no. 2, pp. 225–241, Jun. 2022, DOI: 10.37936/ecti-eec.2022202.246906.
P. K. Chandrashekhar and S. G. Srivani, “Synchrophasor-Based Online Transient Stability Assessment Using Regression Models,” ECTI Transactions on Electrical Engineering, Electronics, and Communications, vol. 20, no. 2, pp. 143–151,
Jun. 2022, DOI: 10.37936/ecti-eec.2022202.246763.