Programa de Pós-Graduação Interunidades em Bioengenharia (EESC/FMRP/IQSC), University of São Paulo, São Carlos 13566-590, Brazil.
Department of Mechanical Engineering, Federal University of São Carlos, São Carlos 13565-905, Brazil.
Sensors (Basel). 2021 Sep 7;21(18):5991. doi: 10.3390/s21185991.
Robotic devices can be used for motor control and learning research. In this work, we present the construction, modeling and experimental validation of a bimanual robotic device. We tested some hypotheses that may help to better understand the motor learning processes involved in the interlimb coordination function. The system emulates a bicycle handlebar with rotational motion, thus requiring bilateral upper limb control and a coordinated sequence of joint sub-movements. The robotic handlebar is compact and portable and can register in a fast rate both position and forces independently from arms, including prehension forces. An impedance control system was implemented in order to promote a safer environment for human interaction and the system is able to generate force fields, suitable for implementing motor learning paradigms. The novelty of the system is the decoupling of prehension and manipulation forces of each hand, thus paving the way for the investigation of hand dominance function in a bimanual task. Experiments were conducted with ten healthy subjects, kinematic and dynamic variables were measured during a rotational set of movements. Statistical analyses showed that movement velocity decreased with practice along with an increase in reaction time. This suggests an increase of the task planning time. Prehension force decreased with practice. However, an unexpected result was that the dominant hand did not lead the bimanual task, but helped to correct the movement, suggesting different roles for each hand during a cooperative bimanual task.
机器人设备可用于运动控制和学习研究。在这项工作中，我们介绍了一种双手机器人装置的构建、建模和实验验证。我们测试了一些假设，这些假设可能有助于更好地理解涉及肢体间协调功能的运动学习过程。该系统模拟了具有旋转运动的自行车把手，因此需要双侧上肢控制和协调的关节子运动序列。机器人把手紧凑便携，能够快速独立地记录手臂的位置和力，包括抓握力。为了促进人机交互的更安全环境，实现了阻抗控制系统，并且该系统能够产生适用于实施运动学习范例的力场。该系统的新颖之处在于双手的抓握力和操纵力的解耦，从而为双手任务中的手优势功能研究铺平了道路。该实验在 10 名健康受试者中进行，在一系列旋转运动中测量了运动学和动力学变量。统计分析表明，随着练习的进行，运动速度会降低，同时反应时间会增加。这表明任务规划时间增加。抓握力随着练习而减少。然而，一个出乎意料的结果是，主导手并没有引领双手任务，而是帮助纠正运动，这表明在协作双手任务中每只手的作用不同。
