Annu Int Conf IEEE Eng Med Biol Soc. 2023 Jul;2023:1-4. doi: 10.1109/EMBC40787.2023.10340519.
Friedreich Ataxia (FRDA) is an inherited disorder that affects the cerebellum and other regions of the human nervous system. It causes impaired movement that affects quality and reduces lifespan. Clinical assessment of movement is a key part of diagnosis and assessment of severity. Recent studies have examined instrumented measurement of movement to support clinical assessments. This paper presents a frequency domain approach based on Average Band Power (ABP) estimation for clinical assessment using Inertial Measurement Unit (IMU) signals. The IMUs were attached to a 3D printed spoon and a cup. Participants used them to mimic eating and drinking activities during data collection. For both activities, the ABP of frequency components from individuals with FRDA clustered in 0 to 0.2Hz band. This suggests that the ABP of this frequency is affected by FRDA irrespective of the device or activity. The ABP in this frequency band was used to distinguish between FRDA and non-ataxic participants using the Area Under the Receiver-Operating-Characteristic Curve (AUC) which produced peak values greater than 0.8. The machine learning models (logistic regression and neural networks) produced accuracy greater than 80% with these features common to both devices.
弗里德赖希共济失调(FRDA)是一种遗传性疾病,影响小脑和人体神经系统的其他区域。它会导致运动受损,影响生活质量并缩短寿命。运动的临床评估是诊断和严重程度评估的关键部分。最近的研究已经检查了运动的仪器测量,以支持临床评估。本文提出了一种基于平均频带功率(ABP)估计的频域方法,用于使用惯性测量单元(IMU)信号进行临床评估。IMU 附着在 3D 打印勺和杯子上。参与者在数据收集期间使用它们来模拟进食和饮水活动。对于这两种活动,来自 FRDA 个体的频率成分的 ABP 在 0 到 0.2Hz 频段内聚集。这表明,无论设备或活动如何,该频率的 ABP 都会受到 FRDA 的影响。使用接收器操作特性曲线(AUC)下的面积来区分 FRDA 和非共济失调参与者,该面积产生的峰值大于 0.8。这些特征对于两种设备都是通用的,使用这些特征的机器学习模型(逻辑回归和神经网络)产生了大于 80%的准确性。