Markovic Marko, Dosen Strahinja, Popovic Dejan, Graimann Bernhard, Farina Dario
Department of Translational Research and Knowledge Management, Otto Bock HealthCare GmbH, D-37115 Duderstadt, Germany.
J Neural Eng. 2015 Dec;12(6):066022. doi: 10.1088/1741-2560/12/6/066022. Epub 2015 Nov 3.
Myoelectric activity volitionally generated by the user is often used for controlling hand prostheses in order to replicate the synergistic actions of muscles in healthy humans during grasping. Muscle synergies in healthy humans are based on the integration of visual perception, heuristics and proprioception. Here, we demonstrate how sensor fusion that combines artificial vision and proprioceptive information with the high-level processing characteristics of biological systems can be effectively used in transradial prosthesis control.
We developed a novel context- and user-aware prosthesis (CASP) controller integrating computer vision and inertial sensing with myoelectric activity in order to achieve semi-autonomous and reactive control of a prosthetic hand. The presented method semi-automatically provides simultaneous and proportional control of multiple degrees-of-freedom (DOFs), thus decreasing overall physical effort while retaining full user control. The system was compared against the major commercial state-of-the art myoelectric control system in ten able-bodied and one amputee subject. All subjects used transradial prosthesis with an active wrist to grasp objects typically associated with activities of daily living.
The CASP significantly outperformed the myoelectric interface when controlling all of the prosthesis DOF. However, when tested with less complex prosthetic system (smaller number of DOF), the CASP was slower but resulted with reaching motions that contained less compensatory movements. Another important finding is that the CASP system required minimal user adaptation and training.
The CASP constitutes a substantial improvement for the control of multi-DOF prostheses. The application of the CASP will have a significant impact when translated to real-life scenarious, particularly with respect to improving the usability and acceptance of highly complex systems (e.g., full prosthetic arms) by amputees.
用户自主产生的肌电活动常被用于控制手部假肢,以复制健康人抓握时肌肉的协同动作。健康人的肌肉协同作用基于视觉感知、启发法和本体感觉的整合。在此,我们展示了如何将结合人工视觉和本体感觉信息以及生物系统高级处理特性的传感器融合有效地用于经桡骨截肢假肢的控制。
我们开发了一种新型的情境和用户感知假肢(CASP)控制器,将计算机视觉、惯性传感与肌电活动相结合,以实现对假手的半自主和反应式控制。所提出的方法半自动地提供对多个自由度(DOF)的同步和比例控制,从而在保持用户完全控制的同时减少整体体力消耗。该系统在10名健全人和1名截肢者身上与主要的商业先进肌电控制系统进行了比较。所有受试者都使用带有主动手腕的经桡骨截肢假肢来抓握通常与日常生活活动相关的物体。
在控制假肢的所有自由度时,CASP明显优于肌电接口。然而,当用不太复杂的假肢系统(自由度数量较少)进行测试时,CASP速度较慢,但达到的动作包含的补偿性动作较少。另一个重要发现是,CASP系统所需的用户适应和训练极少。
CASP在多自由度假肢控制方面有了实质性改进。当应用于实际场景时,特别是在提高截肢者对高度复杂系统(如全假肢手臂)的可用性和接受度方面,CASP的应用将产生重大影响。