Effects of camera viewing angles on tracking kinematic gait patterns using Azure Kinect, Kinect v2 and Orbbec Astra Pro v2

被引:87
作者
Yeung, Ling-Fung [1 ]
Yang, Zhenqun [1 ]
Cheng, Kenneth Chik-Chi [1 ]
Du, Dan [1 ,2 ]
Tong, Raymond Kai-Yu [1 ]
机构
[1] Chinese Univ Hong Kong, Dept Biomed Engn, Hong Kong, Peoples R China
[2] Sichuan Univ, Coll Comp Sci, Chengdu, Sichuan, Peoples R China
关键词
Motion capture; Depth sensor; Accuracy; Treadmill walking; Kinematics; MICROSOFT KINECT; CONCURRENT VALIDITY; POSE TRACKING; RELIABILITY; PARAMETERS; ACCURACY;
D O I
10.1016/j.gaitpost.2021.04.005
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Background: Depth sensors could be a portable, affordable, marker-less alternative to three-dimension motion capture systems for gait analysis, but the effects of camera viewing angles on their joint angle tracking performance have not been fully investigated. Research questions: This study evaluated the accuracies of three depth sensors [Azure Kinect (AK); Kinect v2 (K2); Orbbec Astra (OA)] for tracking kinematic gait patterns during treadmill walking at five camera viewing angles (0 degrees /22.5 degrees/45 degrees/67.5 degrees /90 degrees). Methods: Ten healthy subjects performed fifteen treadmill walking trials (3 speeds x 5 viewing angles) using the three depth sensors to measure joint angles in sagittal hip, frontal hip, sagittal knee, and sagittal ankle. Ten walking steps were recorded and averaged for each walking trial. Range of motion in terms of maximum and minimum joint angles measured by the depth sensors were compared with the Vicon motion capture system as the gold standard. Depth sensors tracking accuracies were compared against the Vicon reference using rootmean-square error (RMSE) on the joint angle time series. Effects of different walking speeds, viewing angles, and depth sensors on the tracking accuracy were observed using three-way repeated-measure analysis of variance (ANOVA). Results: ANOVA results on RMSE showed significant interaction effects between viewing angles and depth sensors for sagittal hip [F(8,72) = 4.404, p = 0.005] and for sagittal knee [F(8,72)=13.211, p < 0.001] joint angles. AK had better tracking performance when subjects walked at non-frontal camera viewing angles (22.5 degrees/45 degrees/67.5 degrees/90 degrees); while K2 performed better at frontal viewing angle (0 degrees). The superior tracking performance of AK compared with K2/OA might be attributed to the improved depth sensor resolution and body tracking algorithm. Significance: Researchers should be cautious about camera viewing angle when using depth sensors for kinematic gait measurements. Our results demonstrated Azure Kinect had good tracking performance of sagittal hip and sagittal knee joint angles during treadmill walking tests at non-frontal camera viewing angles.
引用
收藏
页码:19 / 26
页数:8
相关论文
共 28 条
[1]   Evaluation of the Pose Tracking Performance of the Azure Kinect and Kinect v2 for Gait Analysis in Comparison with a Gold Standard: A Pilot Study [J].
Albert, Justin Amadeus ;
Owolabi, Victor ;
Gebel, Arnd ;
Brahms, Clemens Markus ;
Granacher, Urs ;
Arnrich, Bert .
SENSORS, 2020, 20 (18) :1-22
[2]   Validity and sensitivity of the longitudinal asymmetry index to detect gait asymmetry using Microsoft Kinect data [J].
Auvinet, E. ;
Multon, F. ;
Manning, V. ;
Meunier, J. ;
Cobb, J. P. .
GAIT & POSTURE, 2017, 51 :162-168
[3]  
Bamji CS, 2018, ISSCC DIG TECH PAP I, P94, DOI 10.1109/ISSCC.2018.8310200
[4]   Exergame technology and interactive interventions for elderly fall prevention: A systematic literature review [J].
Choi, Sang D. ;
Guo, Liangjie ;
Kang, Donghun ;
Xiong, Shuping .
APPLIED ERGONOMICS, 2017, 65 :570-581
[5]   Three-dimensional cameras and skeleton pose tracking for physical function assessment: A review of uses, validity, current developments and Kinect alternatives [J].
Clark, Ross A. ;
Mentiplay, Benjamin F. ;
Hough, Emma ;
Pua, Yong Hao .
GAIT & POSTURE, 2019, 68 :193-200
[6]   A Review of the Evolution of Vision-Based Motion Analysis and the Integration of Advanced Computer Vision Methods Towards Developing a Markerless System [J].
Colyer, Steffi L. ;
Evans, Murray ;
Cosker, Darren P. ;
Salo, Aki I. T. .
SPORTS MEDICINE-OPEN, 2018, 4
[7]   A GAIT ANALYSIS DATA-COLLECTION AND REDUCTION TECHNIQUE [J].
DAVIS, RB ;
OUNPUU, S ;
TYBURSKI, D ;
GAGE, JR .
HUMAN MOVEMENT SCIENCE, 1991, 10 (05) :575-587
[8]   Concurrent validity of the Microsoft Kinect for Windows v2 for measuring spatiotemporal gait parameters [J].
Dolatabadi, Elham ;
Taati, Babak ;
Mihailidis, Alex .
MEDICAL ENGINEERING & PHYSICS, 2016, 38 (09) :952-958
[9]   Microsoft Kinect can distinguish differences in over-ground gait between older persons with and without Parkinson's disease [J].
Eltoukhy, Moataz ;
Kuenze, Christopher ;
Oh, Jeonghoon ;
Jacopetti, Marco ;
Wooten, Savannah ;
Signorile, Joseph .
MEDICAL ENGINEERING & PHYSICS, 2017, 44 :1-7
[10]   Reliability of four models for clinical gait analysis [J].
Kainz, Hans ;
Graham, David ;
Edwards, Julie ;
Walsh, Henry P. J. ;
Maine, Sheanna ;
Boyd, Roslyn N. ;
Lloyd, David G. ;
Modenese, Luca ;
Carty, Christopher P. .
GAIT & POSTURE, 2017, 54 :325-331