Federal Institute of Paraná, Assis Chateaubriand Campus, Assis Chateaubriand 85935-000, Brazil.
Department of Electrical Engineering, State University of Londrina, Londrina 86057-970, Brazil.
Sensors (Basel). 2023 Nov 7;23(22):9020. doi: 10.3390/s23229020.
Wearable technologies have aided in reducing pathological tremor symptoms through non-intrusive solutions that aim to identify patterns in involuntary movements and suppress them using actuators positioned at specific joints. However, during the development of these devices, tests were primarily conducted on patients due to the difficulty of faithfully simulating tremors using simulation equipment. Based on studies characterizing tremors in Parkinson's disease, the development of a robotic manipulator based on the Stewart platform was initiated, with the goal of satisfactorily simulating resting tremor movements in the hands. In this work, a simulator was implemented in a computational environment using the multibody dynamics method. The platform structure was designed in a virtual environment using SOLIDWORKS v2017 software and later exported to Matlab R17a software using the Simulink environment and Simscape multibody library. The workspace was evaluated, and the Kalman filter was used to merge acceleration and angular velocity data and convert them into data related to the inclination and rotation of real patients' wrists, which were subsequently executed in the simulator. The results show a high correlation and low dispersion between real and simulated signals, demonstrating that the simulated mechanism has the capacity to represent Parkinson's disease resting tremors in all wrist movements. The system could contribute to conducting tremor tests in suppression devices without the need for the presence of the patient and aid in comparing suppression techniques, benefiting the development of new wearable devices.
可穿戴技术通过非侵入性解决方案辅助减少病理性震颤症状，这些方案旨在识别非自主运动模式，并通过位于特定关节的致动器来抑制它们。然而，在这些设备的开发过程中，由于难以使用模拟设备忠实地模拟震颤，因此主要在患者身上进行测试。基于帕金森病震颤特征的研究，基于 Stewart 平台的机器人操纵器的开发已经启动，目标是在手部满意地模拟静止震颤运动。在这项工作中，使用多体动力学方法在计算环境中实现了模拟器。平台结构使用 SOLIDWORKS v2017 软件在虚拟环境中设计，然后使用 Simulink 环境和 Simscape 多体库将其导出到 Matlab R17a 软件中。评估了工作空间，并使用卡尔曼滤波器合并加速度和角速度数据，并将其转换为与真实患者手腕倾斜和旋转相关的数据，然后在模拟器中执行这些数据。结果表明，真实和模拟信号之间具有高度相关性和低分散性，表明模拟机制具有代表所有手腕运动中帕金森病静止震颤的能力。该系统可以有助于在无需患者在场的情况下进行抑制装置的震颤测试，并有助于比较抑制技术，从而有益于新型可穿戴设备的开发。
