Prediction Potential of Different Handwriting Tasks for Diagnosis of Parkinson's

被引：42

作者：

Drotar, Peter ^{[1
]}

Mekyska, Jiri ^{[1
]}

Smekal, Zdenek ^{[1
]}

Rektorova, Irena ^{[3
]}

Masarova, Lucia ^{[3
]}

Faundez-Zanuy, Marcos ^{[2
]}

机构：

[1] Brno Univ Technol, Dept Telecommun, CS-61090 Brno, Czech Republic

[2] Escola Univ Politec Mataro, Mataro, Spain

[3] St Anns Univ Hosp, Fac Med, First Dept Neurol, Brno, Czech Republic

来源：

2013 E-HEALTH AND BIOENGINEERING CONFERENCE (EHB) | 2013年

关键词：

handwriting; Parkinson's disease; decision support systems; micrographia; SVM; DISEASE; MOVEMENTS;

D O I：

10.1109/EHB.2013.6707378

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

One of the most frequent clinical hallmarks of Parkinson's disease (PD) is micrographia. Micrographia in PD is characterized by the decreased letter size and by changes in the kinematic aspects including increased movement time, decreased velocities and accelerations, and increased number of changes in velocity and acceleration. Based on the literature survey we proposed template to acquire handwriting during different tasks. In addition to well established tasks for PD diagnosis such as Archimedean spiral, we designed new tasks to acquire all aspects of micrographia. The database consists of eight different handwriting samples from seventy-five subjects. The presented results shows almost 80% overall classification accuracy

引用

页数：4

共 16 条

[11] Validity of spiral analysis in early Parkinson's disease [J].