"Digital humans that are customized to the needs of workers and are able to engage in conversation could be more effective than typical online training methods," Aguilar said.
![]()
Digital Humans Are as Effective as Real Humans in Ergonomics: Study
By Jace Dela Cruz, Tech Times Apr 02, 2024 03:40 AM EDT
Recent research conducted by scholars from Texas A&M University School of Public Health explores the efficacy of digital humans, lifelike virtual entities equipped with text-to-speech and speech-to-text functionalities, in providing ergonomics training akin to that offered by real humans.
The study involved researchers Kaysey Aguilar, Mark Benden, Matthew Lee Smith from Texas A&M University School of Public Health, and a colleague from the university's Department of Psychology.
(Photo : Pete Linforth from Pixabay)
Digital Humans for Ergonomics
Ergonomics is the study of designing and arranging things people use so that the people and things interact most efficiently and safely. It aims to optimize human interaction and environment interaction to enhance comfort, performance, and overall well-being.
The team's investigation focused on whether digital human-led training could equip remote workers with adequate ergonomics knowledge to positively influence their work behavior. The findings suggest that digital human-led training yields outcomes comparable to traditional online training methods.
Aguilar highlights the significance of this discovery in light of the escalating use of chatbots and other AI-driven interfaces.
"This is significant, given the dramatic growth in chatbots and other AI-driven interfaces. Digital humans can be customized in terms of their appearance, language, personality, script and gestures, which means that they might provide customizable training that is not possible with conventional online training technologies," Aguilar said in a statement.
In the study, remote workers from a telecommunications company were randomly assigned to three groups: digital human-led training, conventional online training, and a control group receiving no training.
Both training methods covered identical content for accurate comparison, with twice as many participants allocated to the digital human group to address potential technological adoption challenges.
Pre- and post-training questionnaires assessed participants' demographics, remote work practices, ergonomics knowledge, ergonomic behavior, and musculoskeletal discomfort.
Analysis revealed that both training methods led to improved ergonomics knowledge and reduced musculoskeletal discomfort, indicating comparable efficacy. However, only the conventional online training group demonstrated statistically significant improvements in ergonomic behavior.
Further Exploration
Despite digital human training's comparable outcomes, the researchers emphasize the need for further exploration, particularly in leveraging digital humans' conversational capabilities.
While the study underscores the potential of digital human-led training to address remote workers' ergonomics needs, it acknowledges the importance of ongoing innovation and research in this domain, given the prevalence of remote work and technological advancements.
The research findings suggest that while digital human-led training may not surpass traditional methods, it presents a viable option for meeting the training needs of remote workers on a large scale.
"Digital humans that are customized to the needs of workers and are able to engage in conversation could be more effective than typical online training methods," Aguilar said.
The findings of the study were published in the journal Applied Ergonomics.
Related Article: Epic Games' New App Creates Realistic Animated Humans: Everything You Need to Know About MetaHuman Creator
- Forums
- ASX - By Stock
- UNT
- General Discussion
General Discussion, page-3081
-
-
- There are more pages in this discussion • 2,581 more messages in this thread...
You’re viewing a single post only. To view the entire thread just sign in or Join Now (FREE)
Featured News
Add UNT (ASX) to my watchlist
|
|||||
Last
2.0¢ |
Change
0.000(0.00%) |
Mkt cap ! $23.93M |
Open | High | Low | Value | Volume |
2.0¢ | 2.0¢ | 1.9¢ | $6.609K | 337.8K |
Buyers (Bids)
No. | Vol. | Price($) |
---|---|---|
15 | 2337199 | 1.9¢ |
Sellers (Offers)
Price($) | Vol. | No. |
---|---|---|
2.0¢ | 444298 | 3 |
View Market Depth
No. | Vol. | Price($) |
---|---|---|
15 | 2337199 | 0.019 |
8 | 2959722 | 0.018 |
10 | 2058362 | 0.017 |
7 | 1742500 | 0.016 |
3 | 1060000 | 0.015 |
Price($) | Vol. | No. |
---|---|---|
0.020 | 444298 | 3 |
0.022 | 830978 | 2 |
0.023 | 1154714 | 4 |
0.024 | 884660 | 4 |
0.025 | 1000000 | 1 |
Last trade - 15.44pm 09/09/2024 (20 minute delay) ? |
Featured News
UNT (ASX) Chart |