Ambrosini Emilia, Ferrante Simona, Tibiletti Marta, Schauer Thomas, Klauer Christian, Ferrigno Giancarlo, Pedrocchi Alessandra
NeuroEngineering and Medical Robotics Laboratory, Bioengineering Department of Politecnico di Milano.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:4259-62. doi: 10.1109/IEMBS.2011.6091057.
MUNDUS is an assistive platform for recovering direct interaction capability of severely impaired people based on upper limb motor functions. Its main concept is to exploit any residual control of the end-user, thus being suitable for long term utilization in daily activities. MUNDUS integrates multimodal information (EMG, eye tracking, brain computer interface) to control different actuators, such as a passive exoskeleton for weight relief, a neuroprosthesis for arm motion and small motors for grasping. Within this project, the present work integreted a commercial passive exoskeleton with an EMG-controlled neuroprosthesis for supporting hand-to-mouth movements. Being the stimulated muscle the same from which the EMG was measured, first it was necessary to develop an appropriate digital filter to separate the volitional EMG and the stimulation response. Then, a control method aimed at exploiting as much as possible the residual motor control of the end-user was designed. The controller provided a stimulation intensity proportional to the volitional EMG. An experimental protocol was defined to validate the filter and the controller operation on one healthy volunteer. The subject was asked to perform a sequence of hand-to-mouth movements holding different loads. The movements were supported by both the exoskeleton and the neuroprosthesis. The filter was able to detect an increase of the volitional EMG as the weight held by the subject increased. Thus, a higher stimulation intensity was provided in order to support a more intense exercise. The study demonstrated the feasibility of an EMG-controlled neuroprosthesis for daily upper limb support on healthy subjects, providing a first step forward towards the development of the final MUNDUS platform.
MUNDUS是一个基于上肢运动功能，用于恢复严重受损者直接交互能力的辅助平台。其主要理念是利用终端用户的任何残余控制能力，因此适用于日常活动中的长期使用。MUNDUS集成了多模态信息（肌电图、眼动追踪、脑机接口）来控制不同的执行器，如用于减轻重量的被动式外骨骼、用于手臂运动的神经假体以及用于抓握的小型电机。在该项目中，目前的工作将商业被动式外骨骼与肌电图控制的神经假体集成在一起，以支持手到嘴的动作。由于刺激肌肉与测量肌电图的肌肉相同，首先有必要开发一种合适的数字滤波器来分离自主肌电图和刺激反应。然后，设计了一种旨在尽可能利用终端用户残余运动控制能力的控制方法。该控制器提供与自主肌电图成比例的刺激强度。定义了一个实验方案来验证滤波器和控制器在一名健康志愿者身上的操作。要求受试者在手持不同负载的情况下执行一系列手到嘴的动作。这些动作由外骨骼和神经假体共同支持。随着受试者手持重量的增加，滤波器能够检测到自主肌电图的增加。因此，提供了更高的刺激强度以支持更剧烈的运动。该研究证明了肌电图控制的神经假体用于健康受试者日常上肢支持的可行性，为最终的MUNDUS平台的开发迈出了第一步。
