A Noncontact Method for Locating Radial Artery above Radial Styloid Process in Thermal Image

Xingguang Geng; Su Liu; Yitao Zhang; Jiena Hou; Shaolong Zhang; Jun Zhang; Haiying Zhang

doi:10.1155/2020/4057154

A Noncontact Method for Locating Radial Artery above Radial Styloid Process in Thermal Image

Evid Based Complement Alternat Med. 2020 May 7:2020:4057154. doi: 10.1155/2020/4057154. eCollection 2020.

Authors

Xingguang Geng^{1

2

3}, Su Liu^{1

3}, Yitao Zhang^{1

3}, Jiena Hou^{1

2

3}, Shaolong Zhang^{1

3}, Jun Zhang^{1

2

3}, Haiying Zhang^{1

2

3}

Affiliations

¹ Institute of Microelectronics of Chinese Academy of Sciences, Beijing, China.
² University of Chinese Academy of Sciences, Beijing, China.
³ Beijing Key Laboratory for Next Generation RF Communication Chip Technology, Beijing, China.

Abstract

A radial artery above the radial styloid process is called GUAN and is a critical position for collecting pulse wave in traditional Chinese medicine theory. Locating GUAN is a precondition for collecting radial pulse wave. However, existing methods for locating GUAN lead to large deviations. This paper proposes a novel nontouch method for locating GUAN based on thermal imaging and image processing. This method consists of three parts: the infrared thermal imaging location imaging platform, the wrist edge contour extraction algorithm based on arbitrary angle edge recognition, and radial protrusion recognition algorithm (x coordinate identification algorithm of GUAN) and radial artery fitting algorithm (y coordinate identification algorithm of GUAN). The infrared thermal imaging positioning imaging platform is used to ensure that the wrist of the subject enters the fixed imaging area in a fixed position during each measurement and transmits the thermal imaging images carrying the image information of radial processes and radial arteries to the upper computer. Arbitrary angle edge recognition algorithm is used to extract wrist contour and radial artery edge information. The x-axis coordinates of the radial artery were provided by the identification algorithm, and the y-axis coordinates of the radial artery were provided by the fitting algorithm. Finally, the x and y coordinates determine the GUAN position. The algorithm for locating GUAN could provide repeatable and reliable x and y coordinates. The proposed method shows that relative standard deviation (RSD) of x distance of GUAN is less than 9.0% and RSD of y distance of GUAN is less than 5.0%. The proposed method could provide valid GUAN coordinates and reduce deviations of locating GUAN.