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Quantitative Analysis of Bradykinesia and Rigidity in Parkinson's Disease.
di Biase, Lazzaro; Summa, Susanna; Tosi, Jacopo; Taffoni, Fabrizio; Marano, Massimo; Cascio Rizzo, Angelo; Vecchio, Fabrizio; Formica, Domenico; Di Lazzaro, Vincenzo; Di Pino, Giovanni; Tombini, Mario.
Afiliação
  • di Biase L; Neurology Unit, Campus Bio-Medico University of Rome, Rome, Italy.
  • Summa S; NeXT: Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Università Campus Bio-Medico, Rome, Italy.
  • Tosi J; Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom.
  • Taffoni F; NeXT: Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Università Campus Bio-Medico, Rome, Italy.
  • Marano M; Unit of Biomedical Robotics and Biomicrosystems, School of Engineering, Campus Bio-Medico University of Rome, Rome, Italy.
  • Cascio Rizzo A; NeXT: Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Università Campus Bio-Medico, Rome, Italy.
  • Vecchio F; Unit of Biomedical Robotics and Biomicrosystems, School of Engineering, Campus Bio-Medico University of Rome, Rome, Italy.
  • Formica D; Unit of Biomedical Robotics and Biomicrosystems, School of Engineering, Campus Bio-Medico University of Rome, Rome, Italy.
  • Di Lazzaro V; Neurology Unit, Campus Bio-Medico University of Rome, Rome, Italy.
  • Di Pino G; Neurology Unit, Campus Bio-Medico University of Rome, Rome, Italy.
  • Tombini M; Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy.
Front Neurol ; 9: 121, 2018.
Article em En | MEDLINE | ID: mdl-29568281
ABSTRACT

BACKGROUND:

In the last decades, several studies showed that wearable sensors, used for assessing Parkinson's disease (PD) motor symptoms and recording their fluctuations, could provide a quantitative and reliable tool for patient's motor performance monitoring.

OBJECTIVE:

The aim of this study is to make a step forward the capability of quantitatively describing PD motor symptoms. The specific aims are identify the most sensible place where to locate sensors to monitor PD bradykinesia and rigidity, and identify objective indexes able to discriminate PD OFF/ON motor status, and PD patients from healthy subjects (HSs).

METHODS:

Fourteen PD patients (H&Y stage 1-2.5), and 13 age-matched HSs, were enrolled. Five magneto-inertial wearable sensors, placed on index finger, thumb, metacarpus, wrist, and arm, were used as motion tracking systems. Sensors were placed on the most affected arm of PD patients, and on dominant hand of HS. Three UPDRS part III tasks were evaluated rigidity (task 22), finger tapping (task 23), and prono-supination movements of the hands (task 25). A movement disorders expert rated the three tasks according to the UPDRS part III scoring system. In order to describe each task, different kinematic indexes from sensors were extracted and analyzed.

RESULTS:

Four kinematic indexes were extracted fatigability; total time; total power; smoothness. The last three well-described PD OFF/ON motor status, during finger-tapping task, with an index finger sensor. During prono-supination task, wrist sensor was able to differentiate PD OFF/ON motor condition. Smoothness index, used as a rigidity descriptor, provided a good discrimination of the PD OFF/ON motor status. Total power index, showed the best accuracy for PD vs healthy discrimination, with any sensor location among index finger, thumb, metacarpus, and wrist.

CONCLUSION:

The present study shows that, in order to better describe the kinematic features of Parkinsonian movements, wearable sensors should be placed on a distal location on upper limb, on index finger or wrist. The proposed indexes demonstrated a good correlation with clinical scores, thus providing a quantitative tool for research purposes in future studies in this field.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article