An integrated multi-sensor approach for the remote monitoring of parkinson’s disease

Giovanni Albani, Claudia Ferraris, Roberto Nerino, Antonio Chimienti, Giuseppe Pettiti, Federico Parisi, Gianluigi Ferrari, Nicola Cau, Veronica Cimolin, Corrado Azzaro, Lorenzo Priano, Alessandro Mauro

Research output: Contribution to journalArticlepeer-review

Abstract

The 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.

Original languageEnglish
Article number4764
JournalSensors (Switzerland)
Volume19
Issue number21
DOIs
Publication statusPublished - Nov 1 2019

Keywords

  • Body sensor networks
  • Hand tracking
  • Human machine interface
  • Machine learning
  • Parkinson’s disease
  • Remote monitoring
  • RGB-depth cameras
  • UPDRS assessment

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'An integrated multi-sensor approach for the remote monitoring of parkinson’s disease'. Together they form a unique fingerprint.

Cite this