Literature DB >> 23366110

Accuracy and robustness of Kinect pose estimation in the context of coaching of elderly population.

Stepán Obdrzálek1, Gregorij Kurillo, Ferda Ofli, Ruzena Bajcsy, Edmund Seto, Holly Jimison, Michael Pavel.   

Abstract

The Microsoft Kinect camera is becoming increasingly popular in many areas aside from entertainment, including human activity monitoring and rehabilitation. Many people, however, fail to consider the reliability and accuracy of the Kinect human pose estimation when they depend on it as a measuring system. In this paper we compare the Kinect pose estimation (skeletonization) with more established techniques for pose estimation from motion capture data, examining the accuracy of joint localization and robustness of pose estimation with respect to the orientation and occlusions. We have evaluated six physical exercises aimed at coaching of elderly population. Experimental results present pose estimation accuracy rates and corresponding error bounds for the Kinect system.

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Year:  2012        PMID: 23366110     DOI: 10.1109/EMBC.2012.6346149

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


  36 in total

1.  A Novel Methodology for Extracting and Evaluating Therapeutic Movements in Game-Based Motion Capture Rehabilitation Systems.

Authors:  Zhichao Yang; Mohammad H Rafiei; Alexis Hall; Caroline Thomas; Hali A Midtlien; Alexander Hasselbach; Hojjat Adeli; Lynne V Gauthier
Journal:  J Med Syst       Date:  2018-11-07       Impact factor: 4.460

2.  Portable Motion-Analysis Device for Upper-Limb Research, Assessment, and Rehabilitation in Non-Laboratory Settings.

Authors:  Won Joon Sohn; Rifat Sipahi; Terence D Sanger; Dagmar Sternad
Journal:  IEEE J Transl Eng Health Med       Date:  2019-11-13       Impact factor: 3.316

3.  Validity, Reliability, and Sensitivity of a 3D Vision Sensor-based Upper Extremity Reachable Workspace Evaluation in Neuromuscular Diseases.

Authors:  Jay J Han; Gregorij Kurillo; R Ted Abresch; Alina Nicorici; Ruzena Bajcsy
Journal:  PLoS Curr       Date:  2013-12-12

4.  Assessing upper extremity motor function in practice of virtual activities of daily living.

Authors:  Richard J Adams; Matthew D Lichter; Eileen T Krepkovich; Allison Ellington; Marga White; Paul T Diamond
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2014-09-24       Impact factor: 3.802

5.  Using motion capture to assess colonoscopy experience level.

Authors:  Morten Bo Svendsen; Louise Preisler; Jens Georg Hillingsoe; Lars Bo Svendsen; Lars Konge
Journal:  World J Gastrointest Endosc       Date:  2014-05-16

6.  Robot-Mediated Imitation Skill Training for Children With Autism.

Authors:  Zhi Zheng; Eric M Young; Amy R Swanson; Amy S Weitlauf; Zachary E Warren; Nilanjan Sarkar
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2015-09-03       Impact factor: 3.802

7.  Design and Evaluation of an Interactive Exercise Coaching System for Older Adults: Lessons Learned.

Authors:  Ferda Ofli; Gregorij Kurillo; Štěpán Obdržálek; Ruzena Bajcsy; Holly Brugge Jimison; Misha Pavel
Journal:  IEEE J Biomed Health Inform       Date:  2015-01-13       Impact factor: 5.772

8.  Kalman filtering with censored measurements.

Authors:  Kostas Loumponias; George Tsaklidis
Journal:  J Appl Stat       Date:  2020-08-25       Impact factor: 1.416

9.  A Machine Learning Model for Predicting Sit-to-Stand Trajectories of People with and without Stroke: Towards Adaptive Robotic Assistance.

Authors:  Thomas Bennett; Praveen Kumar; Virginia Ruiz Garate
Journal:  Sensors (Basel)       Date:  2022-06-24       Impact factor: 3.847

10.  Attentional Demand of a Virtual Reality-Based Reaching Task in Nondisabled Older Adults.

Authors:  Yi-An Chen; Yu-Chen Chung; Rachel Proffitt; Eric Wade; Carolee Winstein
Journal:  J Mot Learn Dev       Date:  2015-12
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