The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Innovations in Skeleton-Based Movement Recognition Bridging AI and Human Kinetics
|
|
Author(s): Kulbir Singh (Elevance Health, USA), L Maria Michael Visuwasam (R.M.K. College of Engineering and Technology, India), G. Rajasekaran (Dhaanish Ahmed College of Engineering, India), R. Regin (SRM Instıtute of Science and Technology, India), S. Suman Rajest (Dhaanish Ahmed College of Engineering, India)and Shynu T. (Agni College of Technology, India)
Copyright: 2024
Pages: 17
Source title:
Explainable AI Applications for Human Behavior Analysis
Source Author(s)/Editor(s): P. Paramasivan (Dhaanish Ahmed College of Engineering, India), S. Suman Rajest (Dhaanish Ahmed College of Engineering, India), Karthikeyan Chinnusamy (Veritas, USA), R. Regin (SRM Institute of Science and Technology, India)and Ferdin Joe John Joseph (Thai-Nichi Institute of Technology, Thailand)
DOI: 10.4018/979-8-3693-1355-8.ch008
Purchase
|
Abstract
This chapter stands at the forefront of an innovative intersection between artificial intelligence (AI) and human kinetics, focusing on the transformative realm of skeleton-based movement recognition. At its core, this chapter investigates the sophisticated technologies and methodologies that are pivotal in accurately identifying and analyzing human movements through the lens of skeletal data. This exploration is not just a mere analysis of motion but a deep dive into the intricate dance between the mechanical precision of AI and the fluid complexity of human movement. The chapter meticulously dissects how AI algorithms can interpret skeletal data to recognize and predict human actions, illuminating our physical expressions' nuances. It delves into the myriad of applications this synergy can unlock, from enhancing athletic performance to revolutionizing healthcare and rehabilitation practices. Additionally, the study critically examines the challenges ahead, such as ensuring accuracy in diverse scenarios and addressing ethical concerns related to privacy and data security. By encapsulating the current achievements and envisioning the future landscape, this study contributes significantly to the academic discourse. It paves the way for groundbreaking developments in understanding and augmenting human movement through the power of AI. This interdisciplinary approach promises to redefine our interaction with technology, blurring the lines between the digital and physical realms and unlocking new possibilities in human motion analysis and beyond.
Related Content
|
Kula A. Francis, Kenny A. Hendrickson.
© 2026.
26 pages.
|
|
Summyr Burton, Savannah Baus, Stephen A. Murphy.
© 2026.
50 pages.
|
|
Kesley Richardson, Colby Cavanaugh.
© 2026.
30 pages.
|
|
Angela M. Hill, Kevin B. Sneed, Deborah Austin, Deanna B. Wathington, Hiram B. Green, Michael B. Morgan, Janet B. Roman, Feng B. Cheng, John E. Clark, Natasha Rubie, Kristy Andre, Thea Moore, Antionette Davis, Feng Cheng, Karia Doreen MacAulay, Maisha Standifer, Judette Louis, Joseph Diamond, Kyaien Conner, Victor Obi, Samantha Thompson.
© 2026.
22 pages.
|
|
Angela Stephanie Mazzetti, Anniken Grønstad, John Blenkinsopp.
© 2026.
32 pages.
|
|
Marie Grace Avelino Gomez, Kenith B Villaruel.
© 2026.
30 pages.
|
|
Carolyn Allen.
© 2026.
30 pages.
|
|
|