Robotic technology is gradually becoming commonplace in the medical sector and in the service of patients. Medical conditions that have benefited from significant technological development include stroke, for which rehabilitation with robotic devices is administered, and surgery assisted by robots. Robotic devices have also been proposed for assistance of movement disorders. Pathological tremor, among the most common movement disorders, is such one example. In practice, the dissemination and availability of tremor suppression robotic systems has been limited. Devices in the marketplace tend to either be non-ambulatory or to target specific functions such as eating and drinking. We have developed a one degree-of-freedom (DOF) elbow orthosis that could be worn by an individual with tremor. A speed controlled voluntary driven suppression approach is implemented with the orthosis. Typically tremor suppression methods estimate the tremor component of the signal and produce a canceling counterpart signal. The suggested approach, instead estimates the voluntary component of the motion. A controller then actuates the orthosis based on the voluntary signal while simultaneously rejecting the tremorous motion. In this work, we tested the suppressive orthosis using a 1 DOF robotic system that simulates the human arm. The suggested suppression approach does not require a model of the human arm. Moreover, the human input along with the orthosis forearm gravitational forces, of nonlinear nature, are considered as part of the disturbance to the suppression system. Therefore, the suppression system can be modeled linearly. Nevertheless, the orthosis forearm gravitational forces can be compensated by the suppression system. The electromechanical design of the orthosis is presented, and data from an Essential Tremor patient is used as the human input. Velocity tracking results demonstrate an RMS error of 0.31 rad/s, and a power spectral density shows a reduction of the tremor signal by 99.8, while the intentional component power was reduced by less than 1%.
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机译：机器人技术在医疗领域和为患者提供服务方面正逐渐变得司空见惯。得益于重大技术发展的医疗条件包括中风（使用机器人设备进行康复治疗）和机器人辅助的手术。还提出了用于辅助运动障碍的机器人设备。最常见的运动障碍之一就是病理性震颤。实际上，震颤抑制机器人系统的传播和可用性受到限制。市场上的设备倾向于非移动性或针对特定功能（例如饮食）。我们已经开发出一种具有震颤的个人可以佩戴的单自由度（DOF）肘关节矫形器。矫形器采用了速度控制的自愿驱动抑制方法。典型地，震颤抑制方法估计信号的震颤分量并产生抵消的对应信号。建议的方法改为估算议案的自愿组成部分。然后，控制器根据自愿信号启动矫形器，同时拒绝震颤运动。在这项工作中，我们使用模拟人手臂的1自由度机器人系统测试了抑制性矫形器。建议的抑制方法不需要人体模型。而且，人类输入以及矫形器前臂重力具有非线性性质，被认为是对抑制系统的干扰的一部分。因此，抑制系统可以线性建模。然而，矫形器前臂的重力可以通过抑制系统来补偿。介绍了矫形器的机电设计，并将来自“原发性震颤”患者的数据用作人工输入。速度跟踪结果表明RMS误差为0.31 rad / s，功率谱密度显示震颤信号降低了99.8，而有意分量功率降低了不到1％。
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