Academic Paper

Advancing Pain Recognition through Statistical Correlation-Driven Multimodal Fusion

share this
Download our latest
Academic Paper

This research presents a novel multimodal data fusion methodology for pain behavior recognition, integrating statistical correlation analysis with human-centered insights. Our approach introduces two key innovations:

  1. integrating data driven statistical relevance weights into the fusion strategy to effectively utilize complementary information from heterogeneous modalities, and
  2. incorporating human-centric movement characteristics into multimodal representation learning for detailed modeling of pain behaviors.
Advancing Pain Recognition through Statistical Correlation-Driven Multimodal Fusion

See the industry-leading AI governance platform in action

Schedule a call with one of our experts

Get a demo
product
Holistic AI SafeguardHolistic AI TrackerHolistic AI AuditsHolistic AI Governance Platform
Resources
BlogPapers & ResearchNewsEvents & WebinarsGlossaryGitHubDocumentationEU AI Act Risk Calculator
COmpany
About Holistic AI
Careers
We're Hiring
CustomersPress ReleasesAnalyst CoverageMedia CoverageExecutive BiosMedia LibrarySitemap
legal
Privacy PolicyTerms & Conditions
we@holisticai.com
© Holistic AI. All rights reserved.

DISCLAIMER: The information provided on this website does not, and is not intended to, constitute legal advice; instead, all information, content, and materials available on this site are for general informational purposes only. Information on this website may not constitute the most up-to-date legal or other information. This website contains links to other third-party websites. Such links are only for the convenience of the reader, user or browser; Holistic AI does not recommend or endorse the contents of the third-party sites.

Readers of this website should contact their attorney to obtain advice with respect to any particular legal matter. No reader, user, or browser of this site should act or refrain from acting on the basis of information on this site without first seeking legal advice from counsel in the relevant jurisdiction. Only your individual attorney can provide assurances that the information contained herein – and your interpretation of it – is applicable or appropriate to your particular situation. Use of, and access to, this website or any of the links or resources contained within the site do not create an attorney-client relationship between the reader, user, or browser and website authors, contributors, contributing law firms, or committee members and their respective employers.

The views expressed at, or through, this site are those of the individual authors writing in their individual capacities only – not those of their respective employers, Holistic AI, or committee/task force as a whole. All liability with respect to actions taken or not taken based on the contents of this site are hereby expressly disclaimed. The content on this posting is provided "as is;" no representations are made that the content is error-free.