| Title: | A preliminary screening system for diabetes based on in-car electronic nose |
| Author(s): | Weng X; Li G; Liu Z; Liu R; Liu Z; Wang S; Zhao S; Ma X; Chang Z; |
| Address: | "School of Mechanical and Aerospace Engineering, Jilin University, Changchun, China. Weihai Institute for Bionics, Jilin University, Weihai, China. School of Mathematics, Jilin University, Changchun, China. Department of endocrinology, Jinshan Branch of Shanghai Sixth People's Hospital, Shanghai, China. Department of VIP Unit, China-Japan Union Hospital of Jilin University, Changchun, China. Digital Intelligent Cockpit Department, Intelligent Connected Vehicle Development Institute, China FAW Group Co LTD, Changchun, China. College of Biological and Agricultural Engineering, Jilin University, Changchun, China. Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun, China" |
| ISSN/ISBN: | 2049-3614 (Print) 2049-3614 (Electronic) 2049-3614 (Linking) |
| Abstract: | "Studies have found differences in the concentration of volatile organic compounds in the breath of diabetics and healthy people, prompting attention to the use of devices such as electronic noses to detect diabetes. In this study, we explored the design of a non-invasive diabetes preliminary screening system that uses a homemade electronic nose sensor array to detect respiratory gas markers. In the algorithm part, two feature extraction methods were adopted, gradient boosting method was used to select promising feature subset, and then particle swarm optimization algorithm was introduced to extract 24 most effective features, which reduces the number of sensors by 56% and saves the system cost. Respiratory samples were collected from 120 healthy subjects and 120 diabetic subjects to assess the system performance. Random forest algorithm was used to classify and predict electronic nose data, and the accuracy can reach 93.33%. Experimental results show that on the premise of ensuring accuracy, the system has low cost and small size after the number of sensors is optimized, and it is easy to install on in-car. It provides a more feasible method for the preliminary screening of diabetes on in-car and can be used as an assistant to the existing detection methods" |
| Keywords: | breath analysis diabetes screening electronic noses gas sensor; |
| Notes: | "PubMed-not-MEDLINEWeng, Xiaohui Li, Gehong Liu, Ziwei Liu, Rui Liu, Zhaoyang Wang, Songyang Zhao, Shishun Ma, Xiaotong Chang, Zhiyong eng England 2023/01/21 Endocr Connect. 2023 Feb 20; 12(3):e220437. doi: 10.1530/EC-22-0437. Print 2023 Mar 1" |
