Detection of Blood Glucose Level in Humans using Non-Invasive Method-RL BGM
M. Julie Therese1, P. Dharanyadevi2, A. Devi3, C. Kalaiarasy4

1M. Julie Therese, Assistant Professor in the Department of ECE at Sri Manakula Vinayagar Engineering College, Pondicherry University, Pudhucherry, India.
2P. Dharanyadevi, Faculty, Pondicherry University, Pudhucherry, India.
3Devi, Assistant Professor in the department of ECE at IFET College of Engineering, Villupuram, India.
4C.Kalaiarasy, Faculty, CSE at Pondicherry University. 

Manuscript received on April 02, 2020. | Revised Manuscript received on April 18, 2020. | Manuscript published on May 30, 2020. | PP: 176-180 | Volume-9 Issue-1, May 2020. | Retrieval Number: F1209038620/2020©BEIESP | DOI: 10.35940/ijrte.F1209.059120
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Abstract: Blood sugar in the body is called glucose and it is important that the amount of sugar in the blood is fairly maintained. The body has sugar and blood that is used to store energy in the body. Low or high blood sugar is dangerous to life if it is not treated. The fasting blood glucose level in the morning ranges between 70 mg/dL to 110 mg/dL, after the meal the blood glucose should be less than 140 mg/dL. This paper proposes a method that is best suited to detect blood glucose in the human body and avoid serious health issues by sending a message instantly to the respective number of the patient. Currently, in market Blood Glucose Monitoring (BGM) techniques are vigorous and painful as the blood sample is pricked from the finger that leads to the risk of infection, the strips that were being used were also costly. The solution to this problem statement is a design of non-invasive smart equipment for observing the blood glucose level. One non-invasive method is Red Laser (RL) BGM technique, that is very superior to the other invasive method and non-invasive techniques. Here the refractive index of the laser light is analyzed to determine the blood glucose level. Several tests and experimental results are generated to prove the proposed method is highly accurate. 
Keywords: BGM, Blood glucose, Invasive method, non-invasive method, RL-BGM.
Scope of the Article: Artificial Intelligent Methods, Models, Techniques