共济失调
接收机工作特性
惯性测量装置
物理医学与康复
逻辑回归
加速度计
计算机科学
人工智能
医学
听力学
心理学
机器学习
神经科学
操作系统
作者
Lahiru L. Abeysekara,Chandima Kolambahewage,Pubudu N. Pathirana,Malcolm Horne,David J. Szmulewicz,Louise A. Corben
标识
DOI:10.1109/embc40787.2023.10340519
摘要
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.
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