Low-Complexity Inertial Sensor-based Characterization of the UPDRS Score in the Gait Task of Parkinsonians

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9th International Conference on Body Area Networks
Federico Parisi1, Matteo Giuberti2, Gianluigi Ferrari2, Laura Contin3, Veronica Cimolin4, Corrado Azzaro5, Giovanni Albani5, Alessandro Mauro6
1: Department of Information Engineering, University of Parma & CNIT Research Unit of Parma, Italy
2: Xsens Technologies B.V, The Netherlands
3: Research & Prototyping, Telecom Italia, Italy
4: Department of Electronics, Information, and Bioengineering, Polytechnic of Milan, Italy
5: Istituto Auxologico Italiano IRCCS, Italy
6: Istituto Auxologico Italiano IRCCS & Department of Neurosciences, University of Turin, Italy
    Abstract

    In this paper, we focus on the Gait Analysis (GA) for patients affected by Parkinson's Disease (PD) using a wireless Body Sensor Network (BSN) equipped with Inertial Measurement Units (IMUs). We estimate spatio-temporal parameters and other kinematic variables to characterize the gait, in both Parkinsonians and healthy people. Gait features are compared with scores assigned by neurologists within the Unified Parkinson's Disease Rating Scale (UPDRS), with the ultimate goal of automatically determining the UPDRS score of the Gait Task (GT) carried out by Parkinsonians. Preliminary results show a high correlation between a few gait parameters (such as double support, stride length, and thigh range of rotation) and UPDRS scores.

    http://dx.doi.org/10.4108/icst.bodynets.2014.257054