Lü Lulu, Yang Jiantao, Gu Fanbin, Fan Jingyuan, Wang Chaoyang, Zhu Qingtang, Liu Xiaolin
Department of Microsurgery, Orthopedic Trauma and Hand Surgery, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou Guangdong, 510080, P. R. China.
Guangdong Provincial Center for Peripheral Nerve Tissue Engineering and Technology Research, Guangzhou Guangdong, 510080, P. R. China.
Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi. 2022 May 15;36(5):540-547. doi: 10.7507/1002-1892.202201078.
To validate the use of key point matrix technology based contactless automatic measurement for evaluation of joint motion of hand.
Thirty-three volunteers were enrolled to evaluate the extension and flexion of hand joints between May 2021 and November 2021. There were 20 males and 13 females, the age ranged from 16 to 70 years with an average of 30.2 years. The extension angles of 14 joints of 5 fingers (including hyperextension) and the flexion angles of 12 joints of 4 fingers (excluding thumb) of volunteers were measured by key point matrix technology and manual goniometer, respectively. Then 5 participants and repeated measurement experiment were employed to test the system repeatability and accuracy; 28 participants and paired measurement experiment were employed to test the system accuracy.
The average repeatability of finger joint motion measured by the key point matrix technology was 1.801° (extension) and 7.823° (flexion), respectively. Compared with manual measurement, the average differences of each finger joint measured by the key point matrix technology were 3.225° in extension and 14.145° in flexion, respectively. The key point matrix technology based contactless automatic evaluation system offered excellent consistency with the manual goniometers ( =0.875). While most of the consistency with manual goniometer of individual joints were at moderate levels (median of , 0.440). The correlation coefficients between the measurement results of the two methods were mainly positive in the extension of the joint ( <0.05) and negative in the flexion of the joints ( <0.05).
The key point matrix technology based contactless automatic evaluation provides sufficient measurement repeatability and accuracy in evaluation for the joint motion of hand.
验证基于关键点矩阵技术的非接触式自动测量在评估手部关节活动中的应用。
2021年5月至2021年11月招募了33名志愿者来评估手部关节的伸展和屈曲情况。其中男性20名，女性13名，年龄在16至70岁之间，平均年龄为30.2岁。分别采用关键点矩阵技术和手动量角器测量志愿者5根手指14个关节的伸展角度（包括过伸）和4根手指（不包括拇指）12个关节的屈曲角度。然后选取5名参与者进行重复测量实验以测试系统的重复性和准确性；选取28名参与者进行配对测量实验以测试系统的准确性。
关键点矩阵技术测量手指关节活动的平均重复性分别为伸展1.801°和屈曲7.823°。与手动测量相比，关键点矩阵技术测量的各手指关节平均差异在伸展时为3.225°，在屈曲时为14.145°。基于关键点矩阵技术的非接触式自动评估系统与手动量角器具有良好的一致性（=0.875）。而各个关节与手动量角器的一致性大多处于中等水平（中位数，0.440）。两种方法测量结果之间的相关系数在关节伸展时主要为正（<0.05），在关节屈曲时为负（<0.05）。
基于关键点矩阵技术的非接触式自动评估在评估手部关节活动时具有足够的测量重复性和准确性。
