Rasku Jyrki
Department of Computer Sciences, 33014 University of Tampere, Tampere, Finland.
Comput Biol Med. 2009 Oct;39(10):940-5. doi: 10.1016/j.compbiomed.2009.07.010. Epub 2009 Aug 7.
Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge. Deficits in the postural control system may also originate from a working environment where noise and solvents are present. Some diseases, for instance Menière's disease, can cause instability in walking and standing. Regardless of the origin of the problem in the balance system, it has to be detected in a meaningful, easily interpretable way. When detected, a suitable rehabilitation method can be proposed. In this paper we present a method which extracts a scalar feature from a stabilogram signal, which well describes the differences between young and elderly people's swaying processes. When our feature is applied to the K nearest neighbour algorithm the correct recognition accuracy is over 70% in cases where the purpose is to predict whether an unknown test feature is measured from a young or an elderly subject.
在年轻健康人群中，维持姿势稳定性方面的困难并不常见。然而，随着年龄的增长，问题开始出现。姿势控制系统的缺陷也可能源于存在噪音和溶剂的工作环境。一些疾病，例如梅尼埃病，会导致行走和站立不稳。无论平衡系统问题的根源是什么，都必须以有意义、易于解释的方式进行检测。检测到问题后，就可以提出合适的康复方法。在本文中，我们提出了一种从稳定图信号中提取标量特征的方法，该特征能很好地描述年轻人和老年人摇摆过程的差异。当将我们的特征应用于K近邻算法时，在旨在预测未知测试特征是来自年轻人还是老年人的情况下，正确识别准确率超过70%。
