Assessment of Tremor Activity in the Parkinson's Disease Using a Set of Wearable Sensors
Assessment of Tremor Activity in the Parkinson's Disease Using a Set of Wearable Sensors
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DOI：
10.1109/titb.2011.2182616
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发表时间：
2012-05-01
影响因子：
--
通讯作者：
Konitsiotis, Spyridon
中科院分区：
文献类型：
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作者：
Rigas, George;Tzallas, Alexandros T.;Konitsiotis, Spyridon
震颤是帕金森病（PD）最常见的运动障碍，因此其检测在帕金森病患者的管理和治疗中起着至关重要的作用。目前的诊断程序基于受试者相关的临床评估，很难捕捉细微的震颤特征。在本文中，提出了一种使用安装在患者不同身体部位的一组加速度计来评估静息和动作/姿势震颤的自动化方法。震颤类型（静息/动作姿势）和严重程度的估计基于从获取的信号和隐马尔可夫模型中提取的特征。该方法使用从 23 名受试者（18 名 PD 患者和 5 名对照受试者）收集的数据进行评估。获得的结果验证了所提出的方法成功地：1）以 87% 的准确度量化震颤严重程度，2）区分休息时的姿势性震颤，3）区分日常活动期间的震颤和其他帕金森运动症状。
Tremor is the most common motor disorder of Parkinson's disease (PD) and consequently its detection plays a crucial role in the management and treatment of PD patients. The current diagnosis procedure is based on subject-dependent clinical assessment, which has a difficulty in capturing subtle tremor features. In this paper, an automated method for both resting and action/postural tremor assessment is proposed using a set of accelerometers mounted on different patient's body segments. The estimation of tremor type (resting/action postural) and severity is based on features extracted from the acquired signals and hidden Markov models. The method is evaluated using data collected from 23 subjects (18 PD patients and 5 control subjects). The obtained results verified that the proposed method successfully: 1) quantifies tremor severity with 87% accuracy, 2) discriminates resting from postural tremor, and 3) discriminates tremor from other Parkinsonian motor symptoms during daily activities.