A Multimodal Human-Robot Interface to Drive a Neuroprosthesis for Tremor Management
A Multimodal Human-Robot Interface to Drive a Neuroprosthesis for Tremor Management
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DOI：
10.1109/tsmcc.2012.2200101
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发表时间：
2012-11-01
期刊：
影响因子：
--
通讯作者：
Rocon, Eduardo
中科院分区：
文献类型：
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作者：
Alvaro Gallego, Juan;Ibanez, Jaime;Rocon, Eduardo
震颤是最常见的运动障碍，其发病率随年龄增长而增加。尽管有许多可用的治疗方案，但65%的上肢震颤患者报告在日常生活中存在严重困难。这引起了对不同治疗方案的研究，其中应用选择性机械负载的可穿戴机器人构成了一种有吸引力的方法。在这种情况下，目前的工作提出了一种多模式的人机界面，以驱动神经假体震颤管理。我们的方法依赖于对震颤的精确表征来调节功能性电刺激系统，以补偿震颤。神经假体通过检测来自脑电图活动分析的移动意图来触发，这为用户提供了一个自然的界面。当预测被传递时，表面肌电图用于检测在存在意志活动的情况下震颤的实际发作。这些信息反过来触发刺激，刺激依赖于震颤参数振幅和频率，这些参数来自一对记录受影响关节运动学的惯性传感器。表面肌电图还产生震颤的第一特征，以及关于优选刺激部位的精确信息。除了允许系统的优化性能外，我们的多模式方法还允许实施冗余方法，以提高系统的可靠性并适应不同用户的特定需求。具有代表性的一组患者的结果说明了这里提出的接口的性能，并证明其可行性。
Tremor is the most prevalentmovement disorder, and its incidence is increasing with aging. In spite of the numerous therapeutic solutions available, 65% of those suffering from upper limb tremor report serious difficulties during their daily living. This gives rise to research on different treatment alternatives, amongst which wearable robots that apply selective mechanical loads constitute an appealing approach. In this context, the current work presents a multimodal human-robot interface to drive a neuroprosthesis for tremor management. Our approach relies on the precise characterization of the tremor to modulate a functional electrical stimulation system that compensates for it. The neuroprosthesis is triggered by the detection of the intention to move derived from the analysis of electroencephalographic activity, which provides a natural interface with the user. When a prediction is delivered, surface electromyography serves to detect the actual onset of the tremor in the presence of volitional activity. This information in turn triggers the stimulation, which relies on tremor parameters-amplitude and frequency-derived from a pair of inertial sensors that record the kinematics of the affected joint. Surface electromyography also yields a first characterization of the tremor, together with precise information on the preferred stimulation site. Apart from allowing for an optimized performance of the system, our multimodal approach permits the implementation of redundant methods to both enhance the reliability of the system and adapt to the specific needs of different users. Results with a representative group of patients illustrate the performance of the interface presented here and demonstrate its feasibility.