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The Scientific World Journal
Volume 2015 (2015), Article ID 125736, 9 pages
Research Article

Syndrome Differentiation Analysis on Mars500 Data of Traditional Chinese Medicine

1China Astronaut Research and Training Center, Beijing 100094, China
2Data Center of Traditional Chinese Medicine, China Academy of Chinese Medicine Science, Beijing 100700, China
3Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
4Department of Control Science and Engineering, Tongji University, Shanghai 201804, China
5Shanghai Daosheng Medical Technology Co. Ltd., Shanghai 201203, China

Received 10 October 2014; Accepted 18 December 2014

Academic Editor: Zhaohui Liang

Copyright © 2015 Yong-Zhi Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Mars500 study was a psychological and physiological isolation experiment conducted by Russia, the European Space Agency, and China, in preparation for an unspecified future manned spaceflight to the planet Mars. Its intention was to yield valuable psychological and medical data on the effects of the planned long-term deep space mission. In this paper, we present data mining methods to mine medical data collected from the crew consisting of six spaceman volunteers. The synthesis of the four diagnostic methods of TCM, inspection, listening, inquiry, and palpation, is used in our syndrome differentiation. We adopt statistics method to describe the syndrome factor regular pattern of spaceman volunteers. Hybrid optimization based multilabel (HOML) is used as feature selection method and multilabel k-nearest neighbors (ML-KNN) is applied. According to the syndrome factor statistical result, we find that qi deficiency is a base syndrome pattern throughout the entire experiment process and, at the same time, there are different associated syndromes such as liver depression, spleen deficiency, dampness stagnancy, and yin deficiency, due to differences of individual situation. With feature selection, we screen out ten key factors which are essential to syndrome differentiation in TCM. The average precision of multilabel classification model reaches 80%.