Ngo Thang, Abeysekara Lahiru L, Pathirana Pubudu N, Horne Malcolm, Power Laura, Szmulewicz David J
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:4571-4574. doi: 10.1109/EMBC44109.2020.9175705.
Cerebellar ataxia (CA) refers to the impaired balance and coordination resulting from injury or degeneration of the cerebellum. Testing balance is one of the simplest means of assessing CA. This study compares instrumented assessment and clinical assessment scales of the balance test called Romberg's test. Inertial Measurement Unit (IMU) data were collected from a sensor attached to their chest of 53 subjects while they performed the test. The corresponding clinical scores were also tabulated. Using this data, 99 features were extracted to quantify acceleration, tremor and displacement of body sway. These features were filtered to identify the subset that better characterize the distinctive behavior of CA subjects. Elastic Net Regression model resulted a greater agreement (0.70 Pearson coefficient) with the clinical SARA scores. The overall results indicated that data from a single IMU sensor is sufficient to accurately assess balance in CA. The significance of this study is that evaluation of balance using Recurrence Quantification Analysis produces a comprehensive framework for the assessment of CA.
小脑共济失调（CA）是指因小脑损伤或退化而导致的平衡和协调能力受损。测试平衡是评估CA的最简单方法之一。本研究比较了名为罗姆伯格试验的平衡测试的仪器评估和临床评估量表。在53名受试者进行测试时，从附着在他们胸部的传感器收集惯性测量单元（IMU）数据。相应的临床评分也制成了表格。利用这些数据，提取了99个特征来量化身体摇摆的加速度、震颤和位移。对这些特征进行过滤，以识别能更好地表征CA受试者独特行为的子集。弹性网络回归模型与临床SARA评分的一致性更高（皮尔逊系数为0.70）。总体结果表明，来自单个IMU传感器的数据足以准确评估CA中的平衡。本研究的意义在于，使用递归量化分析评估平衡为CA的评估提供了一个全面的框架。
