Static and dynamic proprioceptive recognition through vibrotactile stimulation.

Static and dynamic proprioceptive recognition through vibrotactile stimulation.
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DOI:
10.1088/1741-2552/ac0d43
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发表时间:
2021-07-02
影响因子:
4
通讯作者:
Hu X
Hu X
中科院分区:
工程技术2区
文献类型:
--
作者:
Vargas L;Huang HH;Zhu Y;Hu X

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本体感受信息为个体提供了我们肢体的静态位置和动态运动的感觉。这种反馈的受损或缺乏会降低我们使用生物肢体或辅助设备进行灵巧运动的能力。在这里,我们试图确定是否可以使用振动触觉反馈的空间和时间分量的变化来识别本体感觉的静态和动态分量。在每个受试者的前臂上放置五个振动器的阵列。每个触觉器被编码为代表五个前臂姿势之一。振动刺激引起的传达前臂的静态位置和运动。四个实验块进行测试每个主题的识别前臂的模拟静态位置,旋转幅度,旋转幅度和方向,和旋转速度。我们的研究结果表明,受试者能够进行本体感受识别的基础上提供的振动触觉信息。具体而言,旋转幅度识别的准确率最高(99.0%),而静态位置和旋转幅度方向的识别准确率最低(分别为91.7%和90.8%)。然而,所有的本体感觉属性被感知的准确度>90%,这表明所实现的振动触觉编码方案可以有效地向用户提供本体感觉信息。结果表明,本体感觉的静态和动态方面的信息可以准确地提供使用一系列的振动器。这种反馈方法可以用来潜在地评估在人机交互过程中的感觉运动整合过程,并改善临床人群的体感障碍的感觉反馈。
Proprioceptive information provides individuals with a sense of our limb’s static position and dynamic movement. Impaired or a lack of such feedback can diminish our ability to perform dexterous motions with our biological limbs or assistive devices. Here we seek to determine whether both static and dynamic components of proprioception can be recognized using variation of the spatial and temporal components of vibrotactile feedback. An array of five vibrotactors was placed on the forearm of each subject. Each tactor was encoded to represent one of the five forearm postures. Vibratory stimulus was elicited to convey the static position and movement of the forearm. Four experimental blocks were performed to test each subject’s recognition of a forearm’s simulated static position, rotational amplitude, rotational amplitude and direction, and rotational speed. Our results showed that the subjects were able to perform proprioceptive recognition based on the delivered vibrotactile information. Specifically, rotational amplitude recognition resulted in the highest level of accuracy (99.0%), while the recognition accuracy of the static position and the rotational amplitude-direction was the lowest (91.7% and 90.8%, respectively). Nevertheless, all proprioceptive properties were perceived with >90% accuracy, indicating that the implemented vibrotactile encoding scheme could effectively provide proprioceptive information to the users. The outcomes suggest that information pertaining to static and dynamic aspects of proprioception can be accurately delivered using an array of vibrotactors. This feedback approach could be used to potentially evaluate the sensorimotor integration processes during human–machine interactions, and to improve sensory feedback in clinical populations with somatosensory impairments.
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