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

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...

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Published in:Gait & Posture Vol. 87; pp. 19 - 27
Main Authors: Yeung, Ling-Fung, Yang, Zhenqun, Cheng, Kenneth Chik-Chi, Du, Dan, Tong, Raymond Kai-Yu
Format: research Journal Article
Published: Elsevier B.V. Jun2021
Online Access:View this record in EBSCOhost
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      dt: Jun2021
      vid: 87
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      pub: Elsevier B.V.
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        10.1016/j.gaitpost.2021.04.005
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        atl: Effects of camera viewing angles on tracking kinematic gait patterns using Azure Kinect, Kinect v2 and Orbbec Astra Pro v2.
      aug:
        au:
          Yeung, Ling-Fung
          Yang, Zhenqun
          Cheng, Kenneth Chik-Chi
          Du, Dan
          Tong, Raymond Kai-Yu
        affil: Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong
      sug:
        subj:
          Gait
          Kinematics
          Human
          Reproducibility of Results
          Comparative Studies
          Multicenter Studies
          Evaluation Research
          Validation Studies
      ab: 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°/22.5°/45°/67.5°/90°).Methods: Ten healthy subjects performed fifteen treadmill walking trials (3 speeds × 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 root-mean-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°/45°/67.5°/90°); while K2 performed better at frontal viewing angle (0°). 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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