Wireless Mobile Communication and Healthcare. Third International Conference, MobiHealth 2012, Paris, France, November 21-23, 2012, Revised Selected Papers

Research Article

Sensor-Based Mobile Functional Movement Screening

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  • @INPROCEEDINGS{10.1007/978-3-642-37893-5_25,
        author={Ulf Jensen and Fabian Weilbrenner and Franz Rott and Bjoern Eskofier},
        title={Sensor-Based Mobile Functional Movement Screening},
        proceedings={Wireless Mobile Communication and Healthcare. Third International Conference, MobiHealth 2012, Paris, France, November 21-23, 2012, Revised Selected Papers},
        proceedings_a={MOBIHEALTH},
        year={2013},
        month={4},
        keywords={Functional Movement Screen
                   Body Sensor Network intertial sensors semi-automatic screening Android app},
        doi={10.1007/978-3-642-37893-5_25}
    }
    
  • Ulf Jensen
    Fabian Weilbrenner
    Franz Rott
    Bjoern Eskofier
    Year: 2013
    Sensor-Based Mobile Functional Movement Screening
    MOBIHEALTH
    Springer
    DOI: 10.1007/978-3-642-37893-5_25
Ulf Jensen1,*, Fabian Weilbrenner1,*, Franz Rott2,*, Bjoern Eskofier1,*
  • 1: University of Erlangen-Nuremberg
  • 2: Adidas innovation team ait
*Contact email: ulf.jensen@cs.fau.de, fabian.weilbrenner@informatik.stud.uni-erlangen.de, franz.rott@adidas.com, bjoern.eskofier@cs.fau.de

Abstract

The Functional Movement Screen(FMS) is a useful tool to assess functional abilities in a pre-participation screening. Its seven dynamic movement tests reveal shortcomings in stability and mobility and screen the whole body. However, the current test protocol delivers results that are subjective, qualitative and have to be manually processed. This article presents a semi-automatic system to overcome these limitations for the Deep Squat test. The system consists of four wireless inertial sensors and a central Android-based processing node for data analysis and result storage. We developed our system based on data from ten subjects and evaluated the results with the FMS scoring guidelines. The sensor-based scoring system completely agreed with the manual scoring in eight out of ten subjects. In addition, quantitative information in case of compensation movements was logged. Thus, our system is capable of simplifying the FMS test and enhances the score with objective, quantitive and automatic results.