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Using Kinect body joint detection system to predict energy expenditures during physical activities

  • Published:2021-11 Issue: Volume:97 Page:103540
  • ISSN:0003-6870
  • Container-title:Applied Ergonomics
  • language:en
  • Short-container-title:Applied Ergonomics

Author:

Woldegiorgis Bereket H.,Lin Chiuhsiang J.,Sananta Riotaro

Funder

Ministry of Science and Technology, Taiwan

Publisher

Elsevier BV

Subject

Physical Therapy, Sports Therapy and Rehabilitation,Engineering (miscellaneous),Safety, Risk, Reliability and Quality,Human Factors and Ergonomics

Reference64 articles.

1. RGB-D ergonomic assessment system of adopted working postures;Abobakr;Appl. Ergon.,2019

2. 2011 compendium of physical activities: a second update of codes and MET values;Ainsworth;Med. Sci. Sports Exerc.,2011

3. 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;Albert;Sensors,2020

4. A new technique for foot-off and foot contact detection in a gait cycle based on the knee joint angle using microsoft kinect v2;Amini,2017

5. Validation and comparison of two methods to assess human energy expenditure during free-living activities;Anastasopoulou;PloS One,2014

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1. Testing the Microsoft kinect skeletal tracking accuracy under varying external factors;MOJ Applied Bionics and Biomechanics;2022-07-06

2. Constructing a Violence Recognition Technique for Elderly Patients with Lower Limb Disability;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2022
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