IEEE Rev Biomed Eng. 2019;12:209-220. doi: 10.1109/RBME.2018.2840679. Epub 2018 May 25.
Neurodegenerative diseases, for instance Alzheimer's disease (AD) and Parkinson's disease (PD), affect the peripheral nervous system, where nerve cells send messages that control muscles in order to allow movements. Sick neurons cannot control muscles properly. Handwriting involves cognitive planning, coordination, and execution abilities. Significant changes in handwriting performance are a prominent feature of AD and PD. This paper addresses the most relevant results obtained in the field of online (dynamic) analysis of handwritten trials by AD and PD patients. The survey is made from a pattern recognition point of view, so that different phases are described. Data acquisition deals not only with the device, but also with the handwriting task. Feature extraction can deal with function and parameter features. The classification problem is also discussed along with results already obtained. This paper also highlights the most profitable research directions.
神经退行性疾病，例如阿尔茨海默病（AD）和帕金森病（PD），会影响外周神经系统，在那里神经细胞发送控制肌肉的信息，以允许运动。患病神经元不能正确地控制肌肉。手写涉及认知规划、协调和执行能力。AD 和 PD 患者的手写表现的显著变化是其突出特征。本文针对 AD 和 PD 患者在线（动态）分析手写试验所获得的最相关结果进行了综述。该综述从模式识别的角度进行，因此描述了不同的阶段。数据采集不仅涉及设备，还涉及手写任务。特征提取既可以处理功能特征，也可以处理参数特征。还讨论了分类问题以及已经获得的结果。本文还突出了最有前途的研究方向。
