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Study on Patient Gait Based on GaitSet

Published: 28 June 2024 Publication History

Abstract

This paper explores patient gait analysis using GaitSet and the YOLOv5 algorithm. The study addresses healthcare challenges posed by an aging population, proposing solutions through Internet+ medical technology. The methodology involves YOLOv5 for data capture, GaitSet for gait recognition, and a horizontal pyramid mapping structure for categorization. The study showcases the model's accuracy in identifying gait patterns, with promising applications in healthcare. The paper concludes with discussions on model improvements and extensions. This research contributes to advancing gait recognition for medical applications using state-of-the-art algorithms.

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    BIC '24: Proceedings of the 2024 4th International Conference on Bioinformatics and Intelligent Computing
    January 2024
    504 pages
    ISBN:9798400716645
    DOI:10.1145/3665689
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

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    Published: 28 June 2024

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