Literature DB >> 23365885

PAGAS: Portable and Accurate Gait Analysis System.

Rojay Wagner1, Aura Ganz.   

Abstract

Gait analysis systems are powerful tools in the monitoring and rehabilitation of many health conditions which result in an altered gait (such as Parkinson's disease and rheumatoid arthritis), along with the injury of lower limbs. However, current systems that provide accurate gait monitoring and analysis are large and expensive, and therefore are available only in professional settings. The goal of this research is to develop and test a Portable and Accurate Gait Analysis System, denoted PAGAS, which enables patients to monitor their own gait and track their progress and improvement over time. Moreover, PAGAS will enable therapists to follow the progress of their patients over time without the need for multiple visits required at a rehabilitation facility, thus saving significant healthcare costs. PAGAS includes footswitches and a micro-controller, which connects to an Android Smart-phone using Bluetooth communication. An application on the Smartphone analyzes the raw data to produce temporal gait parameters that are displayed to the user on a graphical user interface.

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Mesh:

Year:  2012        PMID: 23365885     DOI: 10.1109/EMBC.2012.6345924

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  A Validated Smartphone-Based Assessment of Gait and Gait Variability in Parkinson's Disease.

Authors:  Robert J Ellis; Yee Sien Ng; Shenggao Zhu; Dawn M Tan; Boyd Anderson; Gottfried Schlaug; Ye Wang
Journal:  PLoS One       Date:  2015-10-30       Impact factor: 3.240

Review 2.  Mobile health applications for the most prevalent conditions by the World Health Organization: review and analysis.

Authors:  Borja Martínez-Pérez; Isabel de la Torre-Díez; Miguel López-Coronado
Journal:  J Med Internet Res       Date:  2013-06-14       Impact factor: 5.428

3.  A Mobile Phone-Based Gait Assessment App for the Elderly: Development and Evaluation.

Authors:  Runting Zhong; Pei-Luen Patrick Rau
Journal:  JMIR Mhealth Uhealth       Date:  2020-02-29       Impact factor: 4.773

4.  A Validation Study of a Smartphone-Based Finger Tapping Application for Quantitative Assessment of Bradykinesia in Parkinson's Disease.

Authors:  Chae Young Lee; Seong Jun Kang; Sang-Kyoon Hong; Hyeo-Il Ma; Unjoo Lee; Yun Joong Kim
Journal:  PLoS One       Date:  2016-07-28       Impact factor: 3.240

  4 in total

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