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Feasibility of Home-Based Automated Assessment of Postural Instability and Lower Limb Impairments in Parkinson’s Disease
by
Chimienti, Antonio
, Ferraris, Claudia
, Cau, Nicola
, Azzaro, Corrado
, Nerino, Roberto
, Cimolin, Veronica
, Mauro, Alessandro
, Pettiti, Giuseppe
, Priano, Lorenzo
in
at-home monitoring
/ automated assessment
/ center of mass
/ machine learning
/ movement disorders
/ neurorehabilitation
/ Parkinson’s disease
/ postural stability
/ posture
/ RGB-depth
/ UPDRS tasks
2019
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Feasibility of Home-Based Automated Assessment of Postural Instability and Lower Limb Impairments in Parkinson’s Disease
by
Chimienti, Antonio
, Ferraris, Claudia
, Cau, Nicola
, Azzaro, Corrado
, Nerino, Roberto
, Cimolin, Veronica
, Mauro, Alessandro
, Pettiti, Giuseppe
, Priano, Lorenzo
in
at-home monitoring
/ automated assessment
/ center of mass
/ machine learning
/ movement disorders
/ neurorehabilitation
/ Parkinson’s disease
/ postural stability
/ posture
/ RGB-depth
/ UPDRS tasks
2019
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Do you wish to request the book?
Feasibility of Home-Based Automated Assessment of Postural Instability and Lower Limb Impairments in Parkinson’s Disease
by
Chimienti, Antonio
, Ferraris, Claudia
, Cau, Nicola
, Azzaro, Corrado
, Nerino, Roberto
, Cimolin, Veronica
, Mauro, Alessandro
, Pettiti, Giuseppe
, Priano, Lorenzo
in
at-home monitoring
/ automated assessment
/ center of mass
/ machine learning
/ movement disorders
/ neurorehabilitation
/ Parkinson’s disease
/ postural stability
/ posture
/ RGB-depth
/ UPDRS tasks
2019
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Feasibility of Home-Based Automated Assessment of Postural Instability and Lower Limb Impairments in Parkinson’s Disease
Journal Article
Feasibility of Home-Based Automated Assessment of Postural Instability and Lower Limb Impairments in Parkinson’s Disease
2019
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Overview
A self-managed, home-based system for the automated assessment of a selected set of Parkinson’s disease motor symptoms is presented. The system makes use of an optical RGB-Depth device both to implement its gesture-based human computer interface and for the characterization and the evaluation of posture and motor tasks, which are specified according to the Unified Parkinson’s Disease Rating Scale (UPDRS). Posture, lower limb movements and postural instability are characterized by kinematic parameters of the patient movement. During an experimental campaign, the performances of patients affected by Parkinson’s disease were simultaneously scored by neurologists and analyzed by the system. The sets of parameters which best correlated with the UPDRS scores of subjects’ performances were then used to train supervised classifiers for the automated assessment of new instances of the tasks. Results on the system usability and the assessment accuracy, as compared to clinical evaluations, indicate that the system is feasible for an objective and automated assessment of Parkinson’s disease at home, and it could be the basis for the development of neuromonitoring and neurorehabilitation applications in a telemedicine framework.
Publisher
MDPI,MDPI AG
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