Tossavainen Timo, Toppila Esko, Pyykkö Ilmari, Forsman Pia M, Juhola Martti, Starck Jukka
Department of Computer Sciences, University of Tampere, Tampere FI-33014, Finland.
IEEE Trans Inf Technol Biomed. 2006 Apr;10(2):282-92. doi: 10.1109/titb.2005.859874.
Balance dysfunctions are common, especially among elderly people. Present methods for the diagnosis and evaluation of severity of dysfuntion have limited value. We present a system that makes it easy to implement different visual and mechanical perturbations for clinical investigations of balance and visual-vestibular interaction. The system combines virtual reality visual stimulation with force platform posturography on a moving platform. We evaluate our contruction's utility in a classification task between 33 healthy controls and 77 patients with Ménière's disease, using a series of tests with different visual and mechanical stimuli. Responses of patients and controls differ significantly in parameters computed from stabilograms. We also show that the series of tests achieves a classification accuracy slightly over 80% between controls and patients.
平衡功能障碍很常见,尤其是在老年人中。目前用于诊断和评估功能障碍严重程度的方法价值有限。我们提出了一种系统,该系统便于在平衡和视觉 - 前庭相互作用的临床研究中实施不同的视觉和机械扰动。该系统将虚拟现实视觉刺激与移动平台上的力平台姿势描记法相结合。我们使用一系列不同视觉和机械刺激的测试,评估我们构建的系统在33名健康对照者和77名梅尼埃病患者之间的分类任务中的效用。从稳定图计算出的参数中,患者和对照者的反应有显著差异。我们还表明,该系列测试在对照者和患者之间实现了略高于80%的分类准确率。