Repository logo
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Scholalry Output
  3. Publications
  4. Lower-Limb Strategy Assessment during a Virtual Reality based Dual-Motor-Task
 
  • Details

Lower-Limb Strategy Assessment during a Virtual Reality based Dual-Motor-Task

Source
Proceedings of the IEEE Ras and EMBS International Conference on Biomedical Robotics and Biomechatronics
ISSN
21551774
Date Issued
2020-11-01
Author(s)
Singh, Yogesh
Rodrigues, Vinayvivian
Prado, Antonio
Agrawal, Sunil K.
Vashista, Vineet  
DOI
10.1109/BioRob49111.2020.9224418
Volume
2020-November
Abstract
The technical development of the virtual reality platform provides multiple levels to understand human behaviors in simulated environments and to develop interventions for functional rehabilitation. In this study, a dual-task paradigm in a virtual environment is designed where both tasks demand motor skills. Three healthy adults (mean age: 24.3 years) participated in this study. The experiment involved two conditions of overground walking in virtual reality - normal walking and catch and throw a ball while walking. In this work, we investigated the dual-task gait characteristics and the strategy adopted at the lower limb to perform better in the secondary task of throwing the ball. Results show that more balls were thrown during the terminal stance and pre-swing phase of the dominant leg. Thus, the participants utilized the forward momentum built during the foot-to-foot transition by the lagging dominant foot while throwing. This study provides a new and engaging paradigm to analyze dual-motor-task in a virtual reality environment. It can be used as a powerful tool to characterize gait and cognitive performance measures in individuals.
Unpaywall
URI
https://d8.irins.org/handle/IITG2025/23944
IITGN Knowledge Repository Developed and Managed by Library

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Privacy policy
  • End User Agreement
  • Send Feedback
Repository logo COAR Notify