Enhancing Online Yoga Instruction: Evaluating the Effectiveness of Visual Augmentations for Performance Assessment

Yoga is a mind-body practice known for its substantial psychological and physiological benefit, contributing to a healthy lifestyle. However, without professional guidance, individuals may experience reduced performance and increased risk of injury. While online yoga classes on platforms like Zoom have grown in popularity, tools to support instructors in accurately assessing and monitoring student performance remain insufficient. For certain populations, this lack of real-time professional guidance poses safety risks and limits the effectiveness of the practice. This study examined the effectiveness of using computer-vision-based visual augmentations in enhancing instructors' ability to assess student performance and ensure safety. Specifically, we investigated the effectiveness of various visual augmentations in aiding instructors' visual search for unstable or unsafe poses. Eleven certified yoga instructors (8 female, 3 male), each holding 200 to 500 RYT certifications, participated in the study. Instructors completed eight trials assessing 12 yoga poses using four different visual augmentations—Raw Video, Skeleton (joint locations overlay), Contour (participant outlines), and Contour + Skeleton—across two camera views (Single vs. Multiple Views). During each trial, eye-tracking data was collected as instructors identified potentially unstable (unsafe) poses, and they subsequently completed a usability questionnaire and NASA - TLX rating. Upon finishing all trials, instructors provided overall feedback on the usability of the visual augmentations and camera views Instructors showed no significant difference in their assessment performance across different visual augmentations and camera views. The Skeleton augmentation led to increased cognitive workload, as indicated by larger pupil diameters. The Contour alone augmentation was less effective for visual search based on the usability ratings, and combining Contour with Skeleton did not offer notable improvements. Simpler visualizations, such as Raw and Skeleton, received higher usability ratings, and instructors preferred Single View layouts over Multiple Views for their ease of use and lower cognitive demand. In conclusion, while Skeleton augmentation increased cognitive load, it did not significantly enhance visual search performance. Future research should explore alternative visual augmentation techniques and configurations to better assist instructors on performance assessment which increases overall performance while not substantially increasing cognitive workload.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Industrial and Systems Engineering

Department dc:contributor.department

Industrial and Systems Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2024

Author dc:creator

• Gopal, Ajit Ayyadurai

Chair dc:contributor.committeechair

• Lim, Sol Ie

Committee members dc:contributor.committeemember

• Harden, Samantha M.
• Lau, Nathan Ka Ching

• Online yoga
• computer vision
• pose estimation
• yoga instruction

Statement dc:rights

• Creative Commons Attribution 4.0 International

Licence dc:rights.uri

• http://creativecommons.org/licenses/by/4.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:41678

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/121379