Literature DB >> 28269301

Accurate upper body rehabilitation system using kinect.

Sanjana Sinha, Brojeshwar Bhowmick, Kingshuk Chakravarty, Aniruddha Sinha, Abhijit Das.   

Abstract

The growing importance of Kinect as a tool for clinical assessment and rehabilitation is due to its portability, low cost and markerless system for human motion capture. However, the accuracy of Kinect in measuring three-dimensional body joint center locations often fails to meet clinical standards of accuracy when compared to marker-based motion capture systems such as Vicon. The length of the body segment connecting any two joints, measured as the distance between three-dimensional Kinect skeleton joint coordinates, has been observed to vary with time. The orientation of the line connecting adjoining Kinect skeletal coordinates has also been seen to differ from the actual orientation of the physical body segment. Hence we have proposed an optimization method that utilizes Kinect Depth and RGB information to search for the joint center location that satisfies constraints on body segment length and as well as orientation. An experimental study have been carried out on ten healthy participants performing upper body range of motion exercises. The results report 72% reduction in body segment length variance and 2° improvement in Range of Motion (ROM) angle hence enabling to more accurate measurements for upper limb exercises.

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Year:  2016        PMID: 28269301     DOI: 10.1109/EMBC.2016.7591753

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  1 in total

1.  A 3D Computer Vision-Guided Robotic Companion for Non-Contact Human Assistance and Rehabilitation.

Authors:  Tao Shen; Md Rayhan Afsar; He Zhang; Cang Ye; Xiangrong Shen
Journal:  J Intell Robot Syst       Date:  2020-09-21       Impact factor: 2.646

  1 in total

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