Correlation Between Fingerprint-Guided Sweat Ducts Features From OCT and Diabetic Neuropathy Using Voronoi Diagram
Wangbiao Li
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
Search for more papers by this authorZhida Chen
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
Search for more papers by this authorHui Lin
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
Search for more papers by this authorShidi Hu
Department of Endocrinology and Metabolism, Southern Medical University Third Hospital, Guangzhou, China
Search for more papers by this authorKaihong Chen
The Internet of Things and Artificial Intelligence College, Fujian Polytechnic of Information Technology, Fuzhou, China
Search for more papers by this authorYong Guo
The Internet of Things and Artificial Intelligence College, Fujian Polytechnic of Information Technology, Fuzhou, China
Search for more papers by this authorShulian Wu
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
Search for more papers by this authorHui Li
School of Arts and Sciences, Fuyao University of Science and Technology, Fuzhou, China
Search for more papers by this authorCorresponding Author
Yu Chen
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
Correspondence:
Yu Chen ([email protected])
Zhifang Li ([email protected])
Search for more papers by this authorCorresponding Author
Zhifang Li
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
The Internet of Things and Artificial Intelligence College, Fujian Polytechnic of Information Technology, Fuzhou, China
Correspondence:
Yu Chen ([email protected])
Zhifang Li ([email protected])
Search for more papers by this authorWangbiao Li
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
Search for more papers by this authorZhida Chen
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
Search for more papers by this authorHui Lin
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
Search for more papers by this authorShidi Hu
Department of Endocrinology and Metabolism, Southern Medical University Third Hospital, Guangzhou, China
Search for more papers by this authorKaihong Chen
The Internet of Things and Artificial Intelligence College, Fujian Polytechnic of Information Technology, Fuzhou, China
Search for more papers by this authorYong Guo
The Internet of Things and Artificial Intelligence College, Fujian Polytechnic of Information Technology, Fuzhou, China
Search for more papers by this authorShulian Wu
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
Search for more papers by this authorHui Li
School of Arts and Sciences, Fuyao University of Science and Technology, Fuzhou, China
Search for more papers by this authorCorresponding Author
Yu Chen
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
Correspondence:
Yu Chen ([email protected])
Zhifang Li ([email protected])
Search for more papers by this authorCorresponding Author
Zhifang Li
Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China
The Internet of Things and Artificial Intelligence College, Fujian Polytechnic of Information Technology, Fuzhou, China
Correspondence:
Yu Chen ([email protected])
Zhifang Li ([email protected])
Search for more papers by this authorFunding: This work was supported by the National Natural Science Foundation of China (61875038).
Wangbiao Li and Zhida Chen contributed equally to this work.
ABSTRACT
Diabetic neuropathy (DN) is a prevalent chronic complication of diabetes. Sweat glands are directly controlled by the sympathetic nervous system, whose neuropathy affects the thermal regulation of the skin and results in morphological changes in sweat ducts. This study aims to investigate the correlation between the characteristics of fingerprint-guided sweat ducts assessed by optical coherence tomography and DN based on a predictive model using a back propagation neural network (BPNN) and principal component analysis (PCA). The results demonstrate that the number, volume, and spacing of sweat ducts are correlated with the severity of DN. The Voronoi diagram of the sweat duct distribution demonstrates irregularities in the spatial distribution among patients with DN. Furthermore, the PCA-based BPNN model has good predictive accuracy between patients with non-neuropathic, neuropathic, and severe neuropathic diabetes. These findings suggest that OCT-assessed sweat duct features may serve as non-invasive biomarkers for DN in patients with diabetes.
Conflicts of Interest
The authors declare no conflicts of interest.
Open Research
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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