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GaitKeeper: An AI-Enabled Mobile Technology to Standardize and Measure Gait Speed.
Davey, Naomi; Harte, Gillian; Boran, Aidan; Mc Elwaine, Paul; Kennelly, Seán P.
Afiliação
  • Davey N; Institute of Memory and Cognition, Tallaght University Hospital, D24 NR0A Dublin, Ireland.
  • Harte G; Department of Medical Gerontology, School of Medicine, Trinity College Dublin, 2 Dublin, Ireland.
  • Boran A; Institute of Memory and Cognition, Tallaght University Hospital, D24 NR0A Dublin, Ireland.
  • Mc Elwaine P; Department of Physiotherapy, Tallaght University Hospital, D24 NR0A Dublin, Ireland.
  • Kennelly SP; Insight Centre, Dublin City University, Collins Ave Ext, Whitehall, 9 Dublin, Ireland.
Sensors (Basel) ; 24(17)2024 Aug 28.
Article em En | MEDLINE | ID: mdl-39275462
ABSTRACT
Gait speed is increasingly recognized as an important health indicator. However, gait analysis in clinical settings often encounters inconsistencies due to methodological variability and resource constraints. To address these challenges, GaitKeeper uses artificial intelligence (AI) and augmented reality (AR) to standardize gait speed assessments. In laboratory conditions, GaitKeeper demonstrates close alignment with the Vicon system and, in clinical environments, it strongly correlates with the Gaitrite system. The integration of a cloud-based processing platform and robust data security positions GaitKeeper as an accurate, cost-effective, and user-friendly tool for gait assessment in diverse clinical settings.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Velocidade de Caminhada / Marcha Limite: Adult / Female / Humans / Male Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Velocidade de Caminhada / Marcha Limite: Adult / Female / Humans / Male Idioma: En Ano de publicação: 2024 Tipo de documento: Article