Dysphonic Analysis of Parkinson′s Disease Based on Partially Ordered Topological Graph
Zhang Tao1*, Jiang Peipei1, Li Lin1, Zhang Xiaojuan2
1School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, Hebei, China; 2Kailuan Mental Health Center, Tangshan 063001, Hebei, China
Abstract：In this paper, we proposed a novel dysphonic analysis method on Parkinson′s disease based on partially ordered topological graph from the view of formal concept analysis. Firstly, we constructed a representation (method) named partially ordered topological graph (POT graph) from attribute topology and attribute partially ordered graph, which gained the ability of concept searching and hierarchical concept tree structure representation. Coloring and briefing the concept tree could obtain the brief concept tree. The concept classification structure of the analysis object could be obtained according to the partial order relation of the brief concept tree. Applying the method to concept searching in Parkinson′s disease dataset, results showed that the POT graph could not only analyze the relationship between Parkinson′s disease and speech feature in the view of formal concept, but also be used as a diagnostic basis for data analysis. Results obtained from several Parkinson′s disease datasets(the numbers of sample are 197, 5875, 1040 and 220)showed that the average precision was 76.64% by POT graph. Compared with the classical classifier such as LDA (67.36%), QDA (70.83%), kNN (71.83%), Parzen window (70.24%), and SVM (74.61%), our result was higher than SVM 2.72%. In conclusion, the proposed method could be beneficial to the dysphonic analysis of Parkinson′s disease.
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