A depth camera motion analysis framework for tele-rehabilitation: motion capture and person-centric kinematics analysis

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16 Citations (Scopus)

Abstract

With increasing importance given to telerehabilitation, there is a growing need for accurate, low-cost, and portable motion capture systems that do not require specialist assessment venues. This paper proposes a novel framework for motion capture using only a single depth camera, which is portable and cost effective compared to most industry-standard optical systems, without compromising on accuracy. Novel signal processing and computer vision algorithms are proposed to determine motion patterns of interest from infrared and depth data. In order to demonstrate the proposed framework’s suitability for rehabilitation, we developed a gait analysis application that depends on the underlying motion capture
sub-system. Each subject’s individual kinematics parameters, which are unique to that subject, are calculated and these are stored for monitoring individual progress of the clinical therapy. Experiments were conducted on 14 different subjects, 5 healthy and 9 stroke survivors. The results show very close agreement of the resulting relevant joint angles with a 12-camera based VICON system, a mean error of at most 1.75% in detecting gait events w.r.t the manually generated ground-truth, and significant performance improvements in terms of accuracy and execution time compared to a previous Kinect-based system.
LanguageEnglish
Pages877-887
Number of pages11
JournalIEEE Journal on Selected Topics in Signal Processing
Volume10
Issue number5
DOIs
Publication statusPublished - 1 Aug 2016

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Patient rehabilitation
Kinematics
Cameras
Gait analysis
Optical systems
Computer vision
Costs
Signal processing
Infrared radiation
Monitoring
Industry
Experiments
Motion analysis

Keywords

  • signal processing for rehabilitation
  • depth image processing
  • motion analysis
  • feature extraction
  • tele-rehabilitation

Cite this

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title = "A depth camera motion analysis framework for tele-rehabilitation: motion capture and person-centric kinematics analysis",
abstract = "With increasing importance given to telerehabilitation, there is a growing need for accurate, low-cost, and portable motion capture systems that do not require specialist assessment venues. This paper proposes a novel framework for motion capture using only a single depth camera, which is portable and cost effective compared to most industry-standard optical systems, without compromising on accuracy. Novel signal processing and computer vision algorithms are proposed to determine motion patterns of interest from infrared and depth data. In order to demonstrate the proposed framework’s suitability for rehabilitation, we developed a gait analysis application that depends on the underlying motion capturesub-system. Each subject’s individual kinematics parameters, which are unique to that subject, are calculated and these are stored for monitoring individual progress of the clinical therapy. Experiments were conducted on 14 different subjects, 5 healthy and 9 stroke survivors. The results show very close agreement of the resulting relevant joint angles with a 12-camera based VICON system, a mean error of at most 1.75{\%} in detecting gait events w.r.t the manually generated ground-truth, and significant performance improvements in terms of accuracy and execution time compared to a previous Kinect-based system.",
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author = "Minxiang Ye and Cheng Yang and Vladimir Stankovic and Lina Stankovic and Andrew Kerr",
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