Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloAn integrated multi-sensor approach for the remote monitoring of parkinson's disease
Anno di pubblicazione2019
Formato
  • Elettronico
  • Cartaceo
Autore/iAlbani G. (1); Ferraris C. (2,3); Nerino R. (2); Chimienti A.(2); Pettiti G.(2); Parisi F.(4); Ferrari G.(4); Cau N(1).; Cimolin V.(5); Azzaro C.(1); Priano L.(1,3); Mauro A.(1,3)
Affiliazioni autori(1) Istituto Auxologico Italiano, IRCCS, Department of Neurology and Neuro-Rehabilitation; (2)Institute of Electronics, Computer and Telecommunication Engineering, National Research Council; (3) Department of Neurosciences, University of Turin; (4) CNIT Research Unit of Parma and Department of Information Engineering, University of Parma; (5) Department of Electronics, Information and Bioengineering, Politecnico di Milano
Autori CNR e affiliazioni
  • CLAUDIA FERRARIS
  • ROBERTO NERINO
  • GIUSEPPE PETTITI
  • ANTONIO CHIMIENTI
Lingua/e
  • inglese
AbstractThe increment of the prevalence of neurological diseases due to the trend in population aging demands for new strategies in disease management. In Parkinson's disease (PD), these strategies should aim at improving diagnosis accuracy and frequency of the clinical follow-up by means of decentralized cost-effective solutions. In this context, a system suitable for the remote monitoring of PD subjects is presented. It consists of the integration of two approaches investigated in our previous works, each one appropriate for the movement analysis of specific parts of the body: low-cost optical devices for the upper limbs and wearable sensors for the lower ones. The system performs the automated assessments of six motor tasks of the unified Parkinson's disease rating scale, and it is equipped with a gesture-based human machine interface designed to facilitate the user interaction and the system management. The usability of the system has been evaluated by means of standard questionnaires, and the accuracy of the automated assessment has been verified experimentally. The results demonstrate that the proposed solution represents a substantial improvement in PD assessment respect to the former two approaches treated separately, and a new example of an accurate, feasible and cost-effective mean for the decentralized management of PD.
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RivistaSensors (Basel)
Attiva dal 2001
Editore: Molecular Diversity Preservation International (MDPI), - Basel
Lingua: inglese
ISSN: 1424-8220
Titolo chiave: Sensors (Basel)
Titolo proprio: Sensors. (Basel)
Titolo abbreviato: Sensors (Basel)
Numero volume della rivista19
Fascicolo della rivista-
DOI10.3390/s19214764
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • Scopus (Codice:2-s2.0-85074547279)
Parole chiaveParkinson's disease, UPDRS assessment, RGB-Depth cameras, body sensor networks, hand tracking, human machine interface, machine learning, remote monitoring
Link (URL, URI)http://www.scopus.com/record/display.url?eid=2-s2.0-85074547279&origin=inward
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Strutture CNR
  • IEIIT — Istituto di elettronica e di ingegneria dell'informazione e delle telecomunicazioni
Moduli/Attività/Sottoprogetti CNR
  • DIT.AD009.003.003 : MULTISEN - Tecnologie multisensoriali per la salute e il benessere
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