Department of Electrical and Biomedical EngineeringRMIT University Melbourne VIC 3000 Australia.
SRM Institute of Science and Technology Chennai 603203 India.
IEEE J Transl Eng Health Med. 2023 Nov 1;12:194-203. doi: 10.1109/JTEHM.2023.3329344. eCollection 2024.
Several validated clinical scales measure the severity of essential tremor (ET). Their assessments are subjective and can depend on familiarity and training with scoring systems.
We propose a multi-modal sensing using a wearable inertial measurement unit for estimating scores on the Fahn-Tolosa-Marin tremor rating scale (FTM) and determine the classification accuracy within the tremor type. 17 ET participants and 18 healthy controls were recruited for the study. Two movement disorder neurologists who were blinded to prior clinical information viewed video recordings and scored the FTM. Participants drew a guided Archimedes spiral while wearing an inertial measurement unit placed at the mid-point between the lateral epicondyle of the humerus and the anatomical snuff box. Acceleration and gyroscope recordings were analyzed. The ratio of the power spectral density between frequency bands 0.5-4 Hz and 4-12 Hz, and the sum of power spectrum density over the entire spectrum of 2-74 Hz, for both accelerometer and gyroscope data, were computed. FTM was estimated using regression model and classification using SVM was validated using the leave-one-out method.
Regression analysis showed a moderate to good correlation when individual features were used, while correlation was high ([Formula: see text] = 0.818) when suitable features of the gyro and accelerometer were combined. The accuracy for two-class classification of the combined features using SVM was 91.42% while for four-class it was 68.57%.
Potential applications of this novel wearable sensing method using a wearable Inertial Measurement Unit (IMU) include monitoring of ET and clinical trials of new treatments for the disorder.
有几种经过验证的临床量表可用于衡量原发性震颤（ET）的严重程度。它们的评估是主观的，可能取决于对评分系统的熟悉程度和培训。
我们提出了一种使用可穿戴惯性测量单元的多模态传感方法，用于估计 Fahn-Tolosa-Marin 震颤评定量表（FTM）的分数，并确定震颤类型内的分类准确性。17 名 ET 参与者和 18 名健康对照者被招募参加这项研究。两名运动障碍神经科医生在不知道先前临床信息的情况下观看了视频记录并对 FTM 进行了评分。参与者在佩戴放置在肱骨外上髁和解剖鼻烟盒之间中点的惯性测量单元的同时绘制了导向阿基米德螺旋。分析了加速度计和陀螺仪的记录。计算了频带 0.5-4 Hz 和 4-12 Hz 之间的功率谱密度比，以及整个 2-74 Hz 频谱上的功率谱密度总和，同时使用加速度计和陀螺仪数据。使用回归模型估计 FTM，并使用 SVM 进行分类，使用留一法验证分类。
回归分析显示，当使用单个特征时，相关性为中等至良好，而当组合使用陀螺仪和加速度计的合适特征时，相关性很高（[公式：见文本] = 0.818）。使用 SVM 对组合特征进行两分类的准确率为 91.42%，而四分类的准确率为 68.57%。
这种使用可穿戴惯性测量单元（IMU）的新型可穿戴传感方法的潜在应用包括监测 ET 和新治疗方法的临床试验。
