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A new quantitative evaluation method of spiral drawing for patients with Parkinson’s disease based on a polar coordinate system with varying origin

Author

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  • Wang, Min
  • Wang, Bei
  • Zou, Junzhong
  • Nakamura, Masatoshi

Abstract

Parkinson’s disease (PD) is a common disease of the central nervous system among the elderly, and its complex symptoms bring up challenges for the clinical diagnosis. In this paper, a new method based on a polar coordinate system with varying origin was proposed in order to quantitatively evaluate the performance in spiral drawing tasks for patients with Parkinson’s disease, since this method can assess the movement ability of spiral drawing before and after deep brain stimulation (DBS) among the patients. In this paper, three normal subjects and twelve PD patients participated in spiral drawing experiment. The hand movements of patients, before and after DBS, were recorded by a digitized tablet respectively in this experiment. And the variation of origin, radius, degree and other characteristics of hand movements were evaluated by introducing a set of parameters for feature extraction. The result showed that the proposed polar coordinate system embraced good performance in the quantitative evaluation of spiral drawing. Therefore, the proposed method overcame the limitation of data processes with fixed origin for diagnosis and evaluation, and by combining with extraction and analysis of characteristic parameters it had clinical significance in measuring the effectiveness of operation or treatment for the PD patients.

Suggested Citation

  • Wang, Min & Wang, Bei & Zou, Junzhong & Nakamura, Masatoshi, 2012. "A new quantitative evaluation method of spiral drawing for patients with Parkinson’s disease based on a polar coordinate system with varying origin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4377-4388.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:18:p:4377-4388
    DOI: 10.1016/j.physa.2012.03.029
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    Cited by:

    1. Lahmiri, Salim, 2017. "Parkinson’s disease detection based on dysphonia measurements," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 98-105.

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