Low-complexity inertial sensor-based characterization of the UPDRS score in the gait task of parkinsonians

Federico Parisi; Gianluigi Ferrari; Matteo Giuberti; Laura Contin; Veronica Cimolin; Corrado Azzaro; Giovanni Albani; Alessandro Mauro

doi:10.4108/icst.bodynets.2014.257054

Low-complexity inertial sensor-based characterization of the UPDRS score in the gait task of parkinsonians

Federico Parisi, Gianluigi Ferrari, Matteo Giuberti, Laura Contin, Veronica Cimolin, Corrado Azzaro, Giovanni Albani, Alessandro Mauro

Fondazione Istituto Auxologico Italiano

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	BODYNETS 2014 - 9th International Conference on Body Area Networks
Publisher	ICST
Pages	69-75
Number of pages	7
ISBN (Print)	9781631900471
DOIs	https://doi.org/10.4108/icst.bodynets.2014.257054
Publication status	Published - Nov 21 2014
Event	9th International Conference on Body Area Networks, BODYNETS 2014 - London, United Kingdom Duration: Sep 29 2014 → Oct 1 2014

Other

Other	9th International Conference on Body Area Networks, BODYNETS 2014
Country	United Kingdom
City	London
Period	9/29/14 → 10/1/14

Keywords

Gait Analysis (GA)
Inertial measurement unit (IMU)
Parkinson's disease
Unified Parkinson's Disease Rating Scale (UPDRS)

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications

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Low-complexity inertial sensor-based characterization of the UPDRS score in the gait task of parkinsonians. / Parisi, Federico; Ferrari, Gianluigi; Giuberti, Matteo; Contin, Laura; Cimolin, Veronica; Azzaro, Corrado; Albani, Giovanni; Mauro, Alessandro.

BODYNETS 2014 - 9th International Conference on Body Area Networks. ICST, 2014. p. 69-75.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Parisi, F, Ferrari, G, Giuberti, M, Contin, L, Cimolin, V, Azzaro, C, Albani, G & Mauro, A 2014, Low-complexity inertial sensor-based characterization of the UPDRS score in the gait task of parkinsonians. in BODYNETS 2014 - 9th International Conference on Body Area Networks. ICST, pp. 69-75, 9th International Conference on Body Area Networks, BODYNETS 2014, London, United Kingdom, 9/29/14. https://doi.org/10.4108/icst.bodynets.2014.257054

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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.",

keywords = "Gait Analysis (GA), Inertial measurement unit (IMU), Parkinson's disease, Unified Parkinson's Disease Rating Scale (UPDRS)",

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AU - Parisi, Federico

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AU - Azzaro, Corrado

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AU - Mauro, Alessandro

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