9th International Conference on Body Area Networks

Research Article

Remote monitoring and rehabilitation for patients with neurological diseases

  • @INPROCEEDINGS{10.4108/icst.bodynets.2014.257005,
        author={Roberto NERINO and Claudia FERRARIS and Antonio CHIMIENTI and Giuseppe PETTITI and Daniele PIANU and Giovanni ALBANI and Laura CONTIN and Veronica CIMOLIN and Alessandro MAURO and Corrado AZZARO},
        title={Remote monitoring and rehabilitation for patients with neurological diseases},
        proceedings={9th International Conference on Body Area Networks},
        publisher={ICST},
        proceedings_a={BODYNETS},
        year={2014},
        month={11},
        keywords={tele-rehabilitation upper limbs adaptive motor/cognitive training real-time hand tracking color glove rgb-d camera kinect© exergames neurological diseases automatic evaluation motion analysis ict platform cloud file sharing},
        doi={10.4108/icst.bodynets.2014.257005}
    }
    
  • Roberto NERINO
    Claudia FERRARIS
    Antonio CHIMIENTI
    Giuseppe PETTITI
    Daniele PIANU
    Giovanni ALBANI
    Laura CONTIN
    Veronica CIMOLIN
    Alessandro MAURO
    Corrado AZZARO
    Year: 2014
    Remote monitoring and rehabilitation for patients with neurological diseases
    BODYNETS
    ACM
    DOI: 10.4108/icst.bodynets.2014.257005
Roberto NERINO1,*, Claudia FERRARIS1, Antonio CHIMIENTI1, Giuseppe PETTITI1, Daniele PIANU1, Giovanni ALBANI2, Laura CONTIN3, Veronica CIMOLIN4, Alessandro MAURO2, Corrado AZZARO2
  • 1: Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni (IEIIT CNR)
  • 2: Division of Neurology and Neurorehabilitation, Istituto Auxologico Italiano IRCCS
  • 3: Strategy&Innovation Telecom Italia
  • 4: Department of Electronics, Information, and Bioengineering, Polytechnic of Milan
*Contact email: roberto.nerino@polito.it

Abstract

In this paper we present an upper-limb tele-rehabilitation solution suitable for patients suffering motor impairments due to neurological diseases (e.g. Parkinson’s disease). The solution is based on patient subsystems connected to a clinician subsystem through a secure cloud platform. The patient subsystem is built around a novel Human Computer Interface (HCI) based on RGBDepth camera (e.g. Kinect©), a monitor and soft gloves with color markers. Important features of the HCI are the accuracy of realtime and fine-grained three-dimensional (3D) tracking of hands and fingers, low cost, suitability for motor impaired patients and large working volume. The patient subsystem software implements both standard UPDRS motor tests and exergames, providing automatic evaluations of patients’ performances about motor and cognitive functions. The clinician subsystem interface enables at any time the neurologists and the therapists to access data about their patients, evaluate their condition and get in touch with them if needed. Data produced by the patient-side subsystem during the rehabilitation sessions are stored in the data archiving sub-system on the cloud and can be reviewed by clinicians through the clinician subsystem.