Comparing the Drop Vertical Jump Tracking Performance of the Azure Kinect to the Kinect V2

被引:0
|
作者
Abdelnour, Patrik [1 ]
Zhao, Kevin Y. [1 ,2 ]
Babouras, Athanasios [3 ]
Corban, Jason Philip Aaron Hiro [2 ]
Karatzas, Nicolaos [1 ]
Fevens, Thomas [4 ]
Martineau, Paul Andre [2 ]
机构
[1] McGill Univ, Fac Med & Hlth Sci, 3605 Rue Montagne, Montreal, PQ H3G 2M1, Canada
[2] McGill Univ, Hlth Ctr, Div Orthopaed Surg, 1650 Cedar Ave, Montreal, PQ H3G 1A4, Canada
[3] McGill Univ, Dept Expt Surg, 845 Sherbrooke St, Montreal, PQ H3A 0G4, Canada
[4] Concordia Univ, Dept Comp Sci & Software Engn, 1455 Maisonneuve Blvd W, Montreal, PQ H3G 1M8, Canada
关键词
ACL injury; injury prevention; motion analysis; kinematics; ANTERIOR CRUCIATE LIGAMENT; MICROSOFT KINECT; INJURY RISK; ACL INJURY; RELIABILITY; VALIDITY; PROGRAM;
D O I
10.3390/s24123814
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Traditional motion analysis systems are impractical for widespread screening of non-contact anterior cruciate ligament (ACL) injury risk. The Kinect V2 has been identified as a portable and reliable alternative but was replaced by the Azure Kinect. We hypothesize that the Azure Kinect will assess drop vertical jump (DVJ) parameters associated with ACL injury risk with similar accuracy to its predecessor, the Kinect V2. Sixty-nine participants performed DVJs while being recorded by both the Azure Kinect and the Kinect V2 simultaneously. Our software analyzed the data to identify initial coronal, peak coronal, and peak sagittal knee angles. Agreement between the two systems was evaluated using the intraclass correlation coefficient (ICC). There was poor agreement between the Azure Kinect and the Kinect V2 for initial and peak coronal angles (ICC values ranging from 0.135 to 0.446), and moderate agreement for peak sagittal angles (ICC = 0.608, 0.655 for left and right knees, respectively). At this point in time, the Azure Kinect system is not a reliable successor to the Kinect V2 system for assessment of initial coronal, peak coronal, and peak sagittal angles during a DVJ, despite demonstrating superior tracking of continuous knee angles. Alternative motion analysis systems should be explored.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] Color and Depth Image Correspondence for Kinect v2
    Kim, Changhee
    Yun, Seokmin
    Jung, Seung-Won
    Won, Chee Sun
    ADVANCED MULTIMEDIA AND UBIQUITOUS ENGINEERING: FUTURE INFORMATION TECHNOLOGY, 2015, 352 : 111 - 116
  • [32] Color and Depth Image Correspondence for Kinect v2
    Kim, Changhee
    Yun, Seokmin
    Jung, Seung-Won
    Won, Chee Sun
    ADVANCED MULTIMEDIA AND UBIQUITOUS ENGINEERING: FUTURE INFORMATION TECHNOLOGY, VOL 2, 2016, 354 : 333 - 340
  • [33] Evaluation of lower extremity gait analysis using Kinect V2® tracking system
    Usami, Takuya
    Nishida, Kazuki
    Iguchi, Hirotaka
    Okumura, Taro
    Sakai, Hiroaki
    Ida, Ruido
    Horiba, Mitsuya
    Kashima, Shuuto
    Sahashi, Kento
    Asai, Hayato
    Nagaya, Yuko
    Murakami, Hideki
    Ueki, Yoshino
    Kuroyanagi, Gen
    SICOT-J, 2022, 8
  • [34] Tracking a Real Liver Using a Virtual Liver and an Experimental Evaluation with Kinect v2
    Noborio, Hiroshi
    Watanabe, Kaoru
    Yagi, Masahiro
    Ida, Yasuhiro
    Nankaku, Shigeki
    Onishi, Katsuhiko
    Koeda, Masanao
    Kon, Masanori
    Matsui, Kosuke
    Kaibori, Masaki
    BIOINFORMATICS AND BIOMEDICAL ENGINEERING (IWBBIO 2016), 2016, 9656 : 149 - 162
  • [35] Repurposing the Microsoft Kinect for Windows v2 for external head motion tracking for brain PET
    Noonan, P. J.
    Howard, J.
    Hallett, W. A.
    Gunn, R. N.
    PHYSICS IN MEDICINE AND BIOLOGY, 2015, 60 (22): : 8753 - 8766
  • [36] Kinect v2 for Mobile Robot Navigation: Evaluation and Modeling
    Fankhauser, Peter
    Bloesch, Michael
    Rodriguez, Diego
    Kaestner, Ralf
    Hutter, Marco
    Siegwart, Roland
    PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS (ICAR), 2015, : 388 - 394
  • [37] Kinect v2 Accuracy as a Body Segment Measuring Tool
    Bernal, V. Espinoza
    Satterthwaite, N. A.
    Napoli, A.
    Glass, S. M.
    Tucker, C. A.
    Obeid, I.
    2017 IEEE SIGNAL PROCESSING IN MEDICINE AND BIOLOGY SYMPOSIUM (SPMB), 2017,
  • [38] A depth image acquisition platform based on Kinect V2
    Zhai, Yu
    Qu, Yanlin
    Xu, Peng
    Li, Mengyao
    Han, Shaokun
    AOPC 2021: OPTICAL SENSING AND IMAGING TECHNOLOGY, 2021, 12065
  • [39] Multispectral Hand Recognition Using the Kinect v2 Sensor
    Samoil, S.
    Yanushkevich, S. N.
    2016 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2016, : 4258 - 4264
  • [40] Evaluating and Improving the Depth Accuracy of Kinect for Windows v2
    Yang, Lin
    Zhang, Longyu
    Dong, Haiwei
    Alelaiwi, Abdulhameed
    El Saddik, Abdulmotaleb
    IEEE SENSORS JOURNAL, 2015, 15 (08) : 4275 - 4285