NON INVASIVE GLUCOSE BLODD MONITORING SYSTEM (1) (2) (1).pptx

A noninvasive glucose monitoring system is a device that is used to monitor the glucose level in humon body without disturbing the cells and without pain.

1. NON-INVASIVE BLOOD GLUCOSE MONITORING SYSTEM Alsamad Ansari (549 31 ) Rishabh Posti (5 4952 ) Ritik Goyal ( 5 4955 ) Simmy (54956) Sonakshi Arya (549 57 ) Project-II (495-B) Guided By – Dr. Paras

2. LIST OF CONTENTS 01 Introduction 02 Current Challenges 03 Hardware and Software Requirements 6 Benefits 5 Implementation 04 How it Works? 7 Future Development 8 Conclusion

3. INTRODUCTION Diabetes, a common chronic disease affecting millions worldwide, requires regular monitoring of blood glucose levels. However, the current invasive method, involving finger pricks, poses several challenges such as pain, expense, and the potential spread of infectious diseases. Moreover, long-term use of the invasive method can lead to tissue damage in the fingers.

4. By utilizing the variation in the intensity of NIR (Near-Infrared) light received from the finger, we can accurately determine the glucose level in the blood. Near-Infrared Spectroscopy Range

5. Current Challenges Invasiveness and Discomfort Limited Continuous Monitoring Cost and Accessibility Usability and applicability challenges Time Consuming

6. ARDUINO UNO (ATMEGA328P ) LCD 16x2 DISPLAY HARDWARE REQUIREMENTS

7. IR SENSOR MODULE PHOTODIODE (1450nm,1550nm) IR LED (1450nm,1550nm) GLUCOMETER

8. Arduino IDE Python IDE (Google Colab) SOFTWARE REQUIREMENTS

9. HOW IT WORKS? This project involves non-invasive monitoring of glucose using NIR and pulse sensor. Near-infrared spectroscopy is a method that uses the near-infrared region of electromagnetic spectrum. The basic pulse sensor consists of a light emitting diode and a detector like a light detecting resistor or a photodiode. W hen a tissue is illuminated with the light source i.e. light emitted by the led, the amount of light absorbed depends on the blood volume in that tissue. The detector output is in the form of electrical signal and is proportional to the pulse rate.

10. We determine the blood glucose level by passing NIR radiation through a region of the body we are interested in to monitor its glucose level. As light source, NIR LED from Thorlabs is used, with λ = 1300nm, 1450nm, and 1550nm. The correlation between absorbed radiation and glucose concentration id determined by Beer Lambert Law. Photodiode voltage is proportional to near infrared light transmittance. It is then correlated with blood glucose concentration.

11. BLOCK DIAGRAM

12. CIRCUIT DIAGRAM Circuit Diagram Of Non-Invasive Blood Glucose Monitoring System

13. IMPLEMENTATION

14. DATA COLLECTION We conducted a study involving diabetic individuals to analyze the relationship between their glucose levels and the corresponding analog voltage readings. Glucose levels were measured using the invasive laboratory method for all participants. Simultaneously, analog voltage readings were obtained using the proposed hardware setup

15. CURVE FITTING To establish the relationship between glucose levels and analog voltage, we employed polynomial regression analysis. We performed curve fitting by fitting polynomials of different orders (1st to 5th) to the data. The evaluation helped us select the polynomial regression equation that provided the best balance between accuracy and complexity.

16. After evaluating the performance of the polynomial regression models of different orders, we observed the following: The first-order polynomial (linear) had limited accuracy in capturing the non-linear relationship between glucose levels and analog voltage. F(x) = 0.677*x - 107.11

17. As the order of the polynomial increased, the models could capture more complex relationships, potentially improving prediction accuracy. F(x) = 665.091*x - 2.843*x*x + 0.005*x*x*x - .0000044031*x*x*x*x + .0000000002407*x*x*x*x*x - 58324.419;

18. RESULT Root Mean Square Error = Sqrt((Sum of Square of Individual Value)/Total No. of Sets) Root Mean Square Error = 22.80%

19. ARDUINO IMPLEMENTATION

20. BENEFITS Convenience and Comfort Improved Quality of Life Enhanced Compliance Real-Time Monitoring Early Detection of Highs and Lows Reduced Risk of Infections User Friendly Experience

21. FUTURE DEVELOPMENT Artificial Intelligence Integration Wearable Technology Continuous Monitoring Enhanced Connectivity Predictive Analytics Personalized Recommendations Improved Sensor Technology Collaboration and Partnerships

22. CONCLUSION The research successfully demonstrated a strong relationship between the sensor output voltage and glucose concentration through experiments. The proposed non-invasive glucose monitoring system showed good accuracy and has low manufacturing and maintenance costs. The results of the prototype indicate a promising future for the implementation of NIR technology in real-time and continuous non-invasive glucose monitoring. The proposed NIR spectroscopy experiment has great potential for non-invasive continuous monitoring of glucose levels in the human body. Future studies will investigate the impact of variables such as skin roughness and body fluid concentration to further improve calibration and system sensitivity.

23. REFRENCES https://www.e-dmj.org/journal/view.php?doi=10.4093/dmj.2019.0121 https://www.researchgate.net/publication/323526055_Design_of_no n- invasive_glucose_meter_using_near - infrared_technique https://iopscience.iop.org/article/10.1088/1742-6596/1361/1/012041 Sherman M, “How do blood glucose meters work?,” Chem, vol. 13, (2006).[Online]. NewsAvailable:https ://uwaterloo.ca/chem13news/sites/ca. chem13news/files/uploads/files/343_dec_2006_pages_5-6.pdf. https://www.researchgate.net/publication/323526055_Design_of_no n- invasive_glucose_meter_using_near - infrared_technique . https://chat.openai.com/?model=text-davinci-002-render-sha

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