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评估帕金森病患者手部震颤的计算机模型。

Computer models evaluating hand tremors in Parkinson's disease patients.

作者信息

Legaria-Santiago Valeria Karina, Sánchez-Fernández Luis Pastor, Sánchez-Pérez Luis Alejandro, Garza-Rodríguez Alejandro

机构信息

Instituto Politécnico Nacional, Centro de Investigación en Computación, Juan de Dios Bátiz, 07738 México City, Mexico.

Instituto Politécnico Nacional, Centro de Investigación en Computación, Juan de Dios Bátiz, 07738 México City, Mexico.

出版信息

Comput Biol Med. 2022 Jan;140:105059. doi: 10.1016/j.compbiomed.2021.105059. Epub 2021 Nov 24.

Abstract

One of the most characteristic signs of Parkinson's disease (PD) is hand tremor. The MDS-UPDRS scale evaluates different aspects of the disease. The tremor score is a part of the MDS-UPDRS scale, which provides instructions for rating it, by observation, with an integer from 0 to 4. Nevertheless, this form of assessment is subjective and dependent on visual acuity, clinical judgment, and even the mood of the individual examiner. On the other hand, in many cases, existing computational models proposed to resolve the disadvantages of the MDS-UPDRS scale may have uncertainty in differentiating a category of a slight Parkinson tremor from voluntary movements. In this study, 554 measurements from Parkinson's patients, and 60 measurements from healthy subjects, were recorded with inertial sensors placed on the back of each hand. Five biomechanical indicators characterised the hand tremor. With these indicators, the three fuzzy inference models proposed can differentiate, in the first instance, the presence of postural or resting tremor from a normal movement of the hand, and if detected, to determine its severity. The fuzzy inference models allowed following the criteria of the MDS-UPDRS scale, providing an evaluation with an accuracy of two decimal digits and which, due to its simplicity, can be implemented in clinical environments. The assessments of three experts validated the computer model.

摘要

帕金森病(PD)最典型的症状之一是手部震颤。MDS-UPDRS量表评估该疾病的不同方面。震颤评分是MDS-UPDRS量表的一部分,它提供了通过观察将其评为0至4的整数的指导。然而,这种评估形式是主观的,并且依赖于视力、临床判断,甚至个别检查者的情绪。另一方面,在许多情况下,为解决MDS-UPDRS量表的缺点而提出的现有计算模型在区分轻微帕金森震颤类别与自主运动时可能存在不确定性。在本研究中,使用放置在每只手背部的惯性传感器记录了554名帕金森病患者的测量数据和60名健康受试者的测量数据。五个生物力学指标表征了手部震颤。利用这些指标,所提出的三个模糊推理模型首先可以区分姿势性或静止性震颤与手部正常运动的存在,如果检测到震颤,则确定其严重程度。模糊推理模型允许遵循MDS-UPDRS量表的标准,提供精确到两位小数的评估,并且由于其简单性,可以在临床环境中实施。三位专家的评估验证了该计算机模型。

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