The effectiveness of applied treatment in Parkinson disease based on feature selection of motion activities

被引：0
|
作者：
Switonski, Adam [1 ,3 ,4 ]
Stawarz, Magdalena [2 ,4 ]
Boczarska-Jedynak, Magdalena [7 ,8 ]
Sieron, Aleksander [5 ,6 ]
Polanski, Andrzej [1 ,3 ,4 ]
Wojciechowski, Konrad [1 ,3 ,4 ]
机构：
[1] Polish Japanese Inst Informat Technol, Fac Bytom, PL-41902 Bytom, Poland
[2] Polish Japanese Inst Informat Technol, PL-41902 Bytom, Poland
[3] Silesian Tech Univ, Fac Automat Control Elect & Comp Sci, Inst Comp Sci, PL-44100 Gliwice, Poland
[4] Silesian Tech Univ, Inst Comp Sci, PL-44100 Gliwice, Poland
[5] Med Univ Silesia, Dept Internal Dis Angiol & Phys Med, PL-40752 Katowice, Poland
[6] Med Univ Silesia, Dept & Clin Internal Dis Angiol & Phys Med, Ctr Laser Diagnost & Therapy, PL-41902 Bytom, Poland
[7] Med Univ Silesia, Dept Neurorehabil, Cent Univ Hosp, PL-40752 Katowice, Poland
[8] Med Univ Silesia, Dept Neurol, Cent Univ Hosp, PL-40752 Katowice, Poland
来源：
PRZEGLAD ELEKTROTECHNICZNY | 2012年 / 88卷 / 12B期
关键词：
Parkinson diseases; motion capture; feature selection; feature extraction; supervised machine learning; DEEP BRAIN-STIMULATION; KINEMATICAL DATA;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The analysis of effectiveness of deep brain stimulation and pharmacological treatment in Parkinson disease is presented. It is based on an examination of discriminative properties of distinctive motion features. The feature extraction and selection of kinematical motion data is carried out. The attribute ranking with entropy based attribute evaluation and greedy hill climbing search with assessment of an average inner class dissimilarity are applied. The obtained results show that deep brain stimulation has greater impact on investigated motion activities.
引用
收藏
页码：103 / 106
页数：4
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