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An Adaptive Arm-Weight Support Platform for 3D Upper Limb Robot-Aided Neuro-Rehabilitation

机译:用于3D上肢机器人辅助神经康复的自适应手臂重量支持平台

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Arm-weight support has proved to be a key component in robot-aided neuro-rehabilitation in order to permit a wide range of motion for patients with severe disabilities. In this work, a novel motorized platform for sustaining the upper limb of patients during 3D robot-aided rehabilitation and its control architecture are presented. The proposed system is able to support patient's limb in the 3D space through upper limb kinematic reconstruction during the execution of reaching movements. The platform and the adopted control strategy have been tested on 8 healthy subjects performing point-to-point 3D movements. The trajectory executed by the forearm support has been monitored to assess the performance of the chosen control approach. Moreover, a questionnaire based on the Likert rating scale has been submitted to the subjects to evaluate the overall platform. Preliminary results showed that the proposed control algorithm allowed to follow the arm movement in pmb3D space with a reduced position error (0.002±0.012 rad ), Moreover the subjects felt their arm completely supported, free to move in any direction of the space and judged the platform easy to use.
机译:事实证明,手臂重量支撑是机器人辅助神经康复的关键组成部分,以使严重残疾的患者能够进行广泛的运动。在这项工作中,提出了在3D机器人辅助康复过程中维持患者上肢的新型电动平台及其控制架构。所提出的系统能够在上肢运动执行期间通过上肢运动学重建在3D空间中支撑患者的肢体。该平台和采用的控制策略已经在执行点对点3D运动的8位健康受试者上进行了测试。前臂支撑所执行的轨迹已受到监控,以评估所选控制方法的性能。此外,基于李克特评定量表的问卷已提交给受试者,以评估整体平台。初步结果表明,所提出的控制算法可以跟踪手臂在pmb3D空间中的运动,从而减少了位置误差(0.002±0.012 rad)。此外,受试者感到手臂完全支撑,可以在空间的任何方向上自由移动,并判断平台易于使用。

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