| Autor: |
Abdur Rehman Laili, Noor Nazurah Mohd Yatim, M. H. Laili, Mohd Hafizulfika Hisham, Zalhan Md Yusof, Mohd Zuli Jaafar, Zainiharyati Mohd Zain |
| Rok vydání: |
2014 |
| Předmět: |
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| Zdroj: |
2014 IEEE Conference on Systems, Process and Control (ICSPC 2014). |
| Popis: |
Fourier Transform Near Infrared Spectroscopy (FT-NIRS) is a bright method to estimate glucose concentration level by detecting glucose molecular properties in tissue and blood. NIRS technique consists of many method measurements including diffuse reflection method. It capable to predict blood glucose level in human blood noninvasively without pain. However the main weakness of FT-NIRS is the low absorption spectrum of glucose and not a straight forward signal for quantification analysis. Therefore, preprocessing data and chemometrics analysis is required to enhance the spectrum performance and identified certain chemical information present in the sample. The main objective in this paper is to evaluate the potential of low level detection using FT-NIRS towards glucose spectrum in water and intralipid. This study also observed the relationship between human skin spectrums with its blood glucose level value. Utilizing a few preprocessing method and PLS regression technique, Root Mean Square Error Cross Validation (RMSECV) and Coefficient of determination Cross validation (R2 CV ) were observed to validate the model. RMSECV obtained for glucose in water and intralipid were 47.05 mg/dl (2.6 mmol) and 31.17 mg/dl (1.7 mmol) respectively. Meanwhile R2 CV achieved for glucose in water and intralipid were at 0.94 and 0.97 respectively. The Clarke Error Grid shows 97% of the measurement fell within zone A and B. This study has shown that, glucose detection was possible to be monitored in human blood by using FT-NIRS and PLS regression analysis. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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