An approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity disorders in patients. Obtained results indicate that it is possible to interpret some selected patient’s body movements with a sufficiently high effectiveness.

中文翻译：

---

帕金森氏病患者运动活动的知识表示。

本文提出了一种从生物医学信号分析中提取有关帕金森氏病患者运动活动的知识表示的方法。这是通过使用附着在其身体上的加速度计以及利用其手部运动的视频图像来完成的。利用人工神经网络和支持向量机进行实验，以识别患者的特征性运动活动障碍。所获得的结果表明，可以以足够高的效率来解释某些选定患者的身体运动。