Exercise RecommendationKey IdeaWe consider the problem of long-term healthy and happy living assisted by technology. Specifically, we explore how to use Explainable AI and Ubiquitous Computing for better, personalized health with Yoga learning, practice, performance and environment monitoring, and group recommendation, for long-term exercise adherence. Quick Start
Conceptual Overview - SN PersonalizationKey Contacts: Hari P Gupta, Biplav Srivastava To the best of our knowledge, this is the first paper that comprehensively examines decision support issues around Yoga personalization, from pose sensing to recommendation of corrections for a complete regimen, and illustrates with a case study of Surya Namaskar (SN) - a set of 12 choreographed poses. Representative Publications
Modeling for SNKey Contacts: Mansi Dodiya, Bharath C Muppasani, Hari P Gupta, Biplav Srivastava The SN Yoga ontology (SN-YO) models Surya Namaskar as asanas, numbered pose occurrences, and sequence variants. It also includes a pose correction layer for the SN-variant followed at IIT BHU (our baseline). This layer models body parts, breathing patterns, safety notes, pose errors, and correction instructions. With information in multiple languages, any user application, like the SN-YE tool, can retrieve SN information in English or other supported languages (currently, Hindi and Telugu). Representative Publications
FundingThis work has been possible due to a VAIBHAV Fellowship (2025-2028; 17 proposals from among 216 selected globally) for summer visit and collaboration with IIT-BHU. This is in additon to support for group recommendation work from USC and SCRA. |