AI-Powered Smartphone Application for Automated Gait Analysis: Real-Time Assessment (P1-2.005)

To leverage advanced deep learning algorithms and modern mobile phone technology for remote gait assessments, empowering untrained caregivers to conduct evaluations outside of the clinical setting. This innovation reduces the need for hospital visits while capturing real-world data, enhancing clinical decision-making and patient care.

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Publication Details

Journal
Neurology
Published
2025-04-07
DOI
https://doi.org/10.1212/wnl.0000000000212662
Primary Topic
Gait Recognition and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Powered Smartphone Application for Automated Gait Analysis: Real-Time Assessment (P1-2.005)

Abhay Moghekar, Siavash Shirzadeh Barough
Neurology
Gait Recognition and Analysis
article

AI-Powered Smartphone Application for Automated Gait Analysis: Real-Time Assessment (P1-2.005)

Abhay Moghekar, Siavash Shirzadeh Barough
article en

Abstract

To leverage advanced deep learning algorithms and modern mobile phone technology for remote gait assessments, empowering untrained caregivers to conduct evaluations outside of the clinical setting. This innovation reduces the need for hospital visits while capturing real-world data, enhancing clinical decision-making and patient care.

NeurologyVol. 104(7_Supplement_1)
Johns Hopkins University (US)
Openalex Percentile: Top 93%
Gait Recognition and Analysis
DOISourceOpenAlex
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AI-Powered Smartphone Application for Automated Gait Analysis: Real-Time Assessment (P1-2.005) — Abhay Moghekar, Siavash Shirzadeh Barough · Neurology (2025) | TGRS Research Map | TGRS