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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2016

Joint pain detection by gait analysis for elderly healthcare

The record

Type
Publication
Date
15 March 2016
Level
National
Journal
Proceedings of 2015 IEEE International Conference on Research in Computational Intelligence and Communication Networks Icrcicn 2015
Pages
220-224
Published
15 March 2016
DOI
10.1109/icrcicn.2015.7434239
Scopus ID
84965107277
Authors
3
Open access
No
Citations
3
International co-authorship
No
Co-author countries
IN

Classification

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UN Sustainable Development Goals

  1. 3 Ensure healthy lives and promote well-being for all at all ages

    GoalPrimaryHigh confidenceJudged

    Gait analysis using Kinect differencing and differential evolution identifies joint pain patterns in elderly healthcare achieving 87.91% classification accuracy.

    High confidence
    The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
    Judged
    Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-1.2 Health and well-being

    Sub-themePrimaryHigh confidenceJudged

    Non-intrusive gait-based pain detection supports elderly healthcare monitoring and functional assessment improving diagnostic and care outcomes.

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “Joint pain detection by gait analysis for elderly healthcare”. Kortex.

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