5th International ICST Conference on Pervasive Computing Technologies for Healthcare

Research Article

A measurement device for motion analysis of patients with Parkinson’s disease using sensor based smart clothes

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  • @INPROCEEDINGS{10.4108/icst.pervasivehealth.2011.246014,
        author={Khalil Niazmand and Karin Tonn and Anastasios Kalaras and Tim C. Lueth and  Kai Boetzel and Jan-Hinnerk Mehrkens and S. Kammermeier},
        title={A measurement device for motion analysis of patients  with Parkinson’s disease using sensor based smart  clothes},
        proceedings={5th International ICST Conference on Pervasive Computing Technologies for Healthcare},
        publisher={IEEE},
        proceedings_a={PERVASIVEHEALTH},
        year={2012},
        month={4},
        keywords={acceleration sensors Parkinson’s disease tremor smart clothes},
        doi={10.4108/icst.pervasivehealth.2011.246014}
    }
    
  • Khalil Niazmand
    Karin Tonn
    Anastasios Kalaras
    Tim C. Lueth
    Kai Boetzel
    Jan-Hinnerk Mehrkens
    S. Kammermeier
    Year: 2012
    A measurement device for motion analysis of patients with Parkinson’s disease using sensor based smart clothes
    PERVASIVEHEALTH
    ICST
    DOI: 10.4108/icst.pervasivehealth.2011.246014
Khalil Niazmand1,*, Karin Tonn1, Anastasios Kalaras1, Tim C. Lueth1, Kai Boetzel2, Jan-Hinnerk Mehrkens3, S. Kammermeier2
  • 1: The Institute of Micro Technology and Medical Device Technology (MIMED) at the Technische Universität München
  • 2: Dept. of Neurology, Ludwig-Maximilian Universität Muenchen, Klinikum Großhadern
  • 3: Dept. of Neurosurgery, Ludwig-Maximilian Universität Muenchen, Klinikum Großhadern
*Contact email: khalil.niazmand@tum.de

Abstract

Physical examination, interviews with patients and the results of rating scales for movement disturbances are the basis for the assessment of Parkinson’s disease (PD). However, subjectivity in the assessment of the symptoms and the short period of observation are disadvantageous. This paper presents the results of a study to assess the feasibility of using accelerometer data, acquired from smart clothes, to estimate the severity of tremor in patients with PD. Algorithms were implemented to estimate the severity of rest and postural tremor of hands from accelerometer data features. The system developed consists of a pullover with eight integrated accelerometers and a computer. The newly developed system for the detection and assessment of tremor was tested with PD patients. System-based estimates were compared with clinical scores derived via visual inspection of video recordings taken while patients performed a series of standardized motor tasks. A quantifiable objective data acquisition by means of a portable wireless system could evaluate the motor disorders better.