Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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Discrimination of Parkinson's Disease from Essential Tremor using Acceleration based Tremor Analysis

가속도계를 이용한 진전현상의 분석을 통한 파킨슨병과 본태성 진전의 판별

  • Lee, Hongji (Interdisciplinary Program for Bioengineering, Seoul National University) ;
  • Lee, Woongwoo (Department of Neurology, Eulji General Hospital) ;
  • Jeon, Hyoseon (Interdisciplinary Program for Bioengineering, Seoul National University) ;
  • Kim, Sangkyong (Interdisciplinary Program for Bioengineering, Seoul National University) ;
  • Kim, Hanbyul (Interdisciplinary Program for Bioengineering, Seoul National University) ;
  • Jeon, Beom S. (Department of Neurology, Seoul National University Hospital) ;
  • Park, Kwangsuk (Department of Biomedical Engineering, College of Medicine, Seoul National University)
  • 이홍지 (서울대학교 공과대학 협동과정 바이오엔지니어링 전공) ;
  • 이웅우 (을지병원 신경과) ;
  • 전효선 (서울대학교 공과대학 협동과정 바이오엔지니어링 전공) ;
  • 김상경 (서울대학교 공과대학 협동과정 바이오엔지니어링 전공) ;
  • 김한별 (서울대학교 공과대학 협동과정 바이오엔지니어링 전공) ;
  • 전범석 (서울대학교병원 신경과) ;
  • 박광석 (서울대학교 의과대학 의공학교실)
  • Received : 2015.07.17
  • Accepted : 2015.08.25
  • Published : 2015.08.30
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Abstract

Discrimination of Parkinson's disease (PD) from Essential tremor (ET) is often misdiagnosed in clinical practice. Since tremor is time-varying signal, and dominant and harmonic frequencies are shown in tremor only with moderate or severe symptom, there are some limitations to use frequency related features. Moreover, patients with PD or ET can suffer from both resting tremor and postural tremor. In this study, 28 patients with PD and 17 patients with ET were enrolled. Tremor was measured with accelerations on the more affected hand during resting and postural conditions. The ratio of root mean square (RMS) of resting tremor to RMS of postural tremor, the mean coefficients of autocorrelation function (ACF), and the mean of differences of two adjacent coefficients of ACF at resting and postural were calculated and compared between PD and ET. The performance showed 98% accuracy with support vector machine and leave-one-out cross validation. In addition, the method accurately differentiated the patients with tremor-dominant PD from patients with ET, with 100% accuracy. Therefore, the developed algorithm can assist clinicians in diagnosing and categorizing patients with tremor, especially, patients with mild symptom or the early stage of a disease, for proper treatment.

Keywords

References

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