Advertisement

Classification of Early-Mild Subjects with Parkinson’s Disease by Using Sensor-Based Measures of Posture, Gait, and Transitions

  • Luca Palmerini
  • Sabato Mellone
  • Guido Avanzolini
  • Franco Valzania
  • Lorenzo Chiari
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7885)

Abstract

Evaluation of posture, gait, turning, and different kind of transitions, are key components of the clinical evaluation of Parkinson’s disease (PD). The aim of this study is to assess the feasibility of using accelerometers to classify early PD subjects (two evaluations over a 1-year follow-up) with respect to age-matched control subjects. Classifying PD subjects in an early stage would permit to obtain a tool able to follow the progression of the disease from the early phases till the last ones and to evaluate the efficacy of different treatments. Two functional tests were instrumented by a single accelerometer (quiet standing, Timed Up and Go test); such tests carry quantitative information about impairments in posture, gait, and transitions (i.e. Sit-to-Walk, and Walk-to-Sit, Turning). Satisfactory accuracies are obtained in the classification of PD subjects by using an ad hoc wrapper feature selection technique.

Keywords

Classification Feature Selection Parkinson’s disease Accelerometer 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Palmerini, L., Rocchi, Mellone, S., Valzania, F., Chiari, L.: Feature selection for accelerometer-based posture analysis in Parkinson’s disease. IEEE Transactions on Information Technology in Biomedicine 15(3), 481–490 (2011)CrossRefGoogle Scholar
  2. 2.
    Palmerini, L., Avanzolini, G., Mellone, S., Valzania, F., Chiari, L.: Quantification of Motor Impairment in Parkinson’s Disease Using an Instrumented Timed Up and Go Test. IEEE Transactions on Neural Systems and Rehabilitation Engineering (preprint, 2013)Google Scholar
  3. 3.
    Weiss, A., Herman, T., Plotnik, M., Brozgol, M., et al.: Can an accelerometer enhance the utility of the Timed Up & Go Test when evaluating patients with Parkinson’s disease? Med. Eng. & Phys. 32(2), 119–125 (2010)CrossRefGoogle Scholar
  4. 4.
    Zampieri, C., Salarian, A., Carlson-Kuhta, P., Aminian, K., et al.: The instrumented timed up and go test: potential outcome measure for disease modifying therapies in Parkinson’s disease. J. of Neurol., Neurosurg. & Psychiatry 81(2), 171–176 (2009)CrossRefGoogle Scholar
  5. 5.
    Kohavi, R., John, G.H.: Wrappers for Feature Subset Selection. Art. Intel. 97(1-2), 273–324 (1997)zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Luca Palmerini
    • 1
  • Sabato Mellone
    • 1
  • Guido Avanzolini
    • 1
  • Franco Valzania
    • 2
  • Lorenzo Chiari
    • 1
  1. 1.Department of Electrical, Electronic and Information Engineering, DEIUniversity of BolognaBolognaItaly
  2. 2.Department of NeuroscienceUniversity of Modena and Reggio EmiliaBaggiovaraItaly

Personalised recommendations