Noninvasive Total Cholesterol Level Measurement Using an E-Nose System and Machine Learning on Exhaled Breath Samples

被引：1

作者：

Paleczek, Anna ^{[1
]}

Grochala, Justyna ^{[2
]}

Grochala, Dominik ^{[1
]}

Slowik, Jakub ^{[1
,3
]}

Pihut, Malgorzata ^{[2
]}

Loster, Jolanta E. ^{[4
]}

Rydosz, Artur ^{[1
,5
]}

机构：

[1] AGH Univ Krakow, Inst Elect, Fac Comp Sci Elect & Telecommun, PL-30059 Krakow, Poland

[2] Jagiellonian Univ Med Coll, Dent Inst, Fac Med, Dept Prosthodont & Orthodont, PL-31008 Krakow, Poland

[3] Univ Opole, Univ Clin Hosp Opole, Inst Med Sci, PL-46020 Opole, Poland

[4] Jagiellonian Univ Med Coll, Fac Med, Private Practice, Prof Losters Orthodont, PL-30433 Krakow, Poland

[5] Univ Hosp Krakow, Lab Funct, Virtual Med 3D Imaging 3D vFMi Maging 3D FM, PL-30688 Krakow, Poland

来源：

ACS SENSORS | 2024年 / 9卷 / 12期

关键词：

E-nose system; exhaled breath analysis; gassensors; LGBMRegressor; machine learning; noninvasive measurement; predictive modeling; totalcholesterol level; ISOPRENE; BIOSYNTHESIS; TEDLAR;

D O I：

10.1021/acssensors.4c02198

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

In this paper, the first e-nose system coupled with machine learning algorithm for noninvasive measurement of total cholesterol level based on exhaled air sample was proposed. The study was conducted with the participation of 151 people, from whom a breath sample was collected, and the level of total cholesterol was measured. The breath sample was examined using e-nose and gas sensors, such as TGS1820, TGS2620, TGS2600, MQ3, Semeatech 7e4 NO2 and 7e4 H2S, SGX_NO2, SGX_H2S, K33, AL-03P, and AL-03S. The LGBMRegressor algorithm was used to predict cholesterol level based on the breath sample. Machine learning algorithms were developed for the entire measurement range and for the norm range <= 200 mg/dL achieving MAPE 13.7% and 8%, respectively. The results show that it is possible to develop a noninvasive device to measure total cholesterol level from breath.

引用

页码：6630 / 6637

页数：8

共 27 条

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