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同时利用人工感知觉识别假肢手姿势:案例研究。

Combination of Simultaneous Artificial Sensory Percepts to Identify Prosthetic Hand Postures: A Case Study.

机构信息

Rocky Mountain Regional VA Medical Center, Rehabilitation Research and Development, Denver, CO, 80220, USA.

University of Colorado Boulder, Engineering Plus Program, Boulder, CO, 80309, USA.

出版信息

Sci Rep. 2020 Apr 20;10(1):6576. doi: 10.1038/s41598-020-62970-4.

Abstract

Multiple sources of sensory information are combined to develop hand posture percepts in the intact system, but the combination of multiple artificial somatosensory percepts by human prosthesis users has not been studied. Here, we report on a case study in which a person with transradial amputation identified prosthetic hand postures using artificial somatosensory feedback. He successfully combined five artificial somatosensory percepts to achieve above-chance performance of 95.0% and 75.7% in identifying four and seven postures, respectively. We studied how artificial somatosensation and the extant hand representation are combined in the decision-making process by providing two mappings between the prosthetic sensor and the location of the sensory percept: (1) congruent, and (2) incongruent. The participant's ability to combine and engage with the sensory feedback significantly differed between the two conditions. The participant was only able to successfully generalize prior knowledge to novel postures in the congruent mapping. Further, he learned postures more accurately and quickly in the congruent mapping. Finally, he developed an understanding of the relationships between postures in the congruent mapping instead of simply memorizing each individual posture. These experimental results are corroborated by a Bayesian decision-making model which tracked the participant's learning.

摘要

多种感觉信息源被组合起来以在完整的系统中发展手姿势知觉,但人工感觉知觉的多种组合在人工假体使用者中尚未得到研究。在这里,我们报告了一项案例研究,其中一位桡骨截断的患者使用人工感觉反馈来识别假肢手的姿势。他成功地组合了五种人工感觉知觉,分别以 95.0%和 75.7%的概率成功识别了四种和七种姿势。我们通过在假肢传感器和感觉知觉的位置之间提供两种映射(1)一致,和(2)不一致,研究了在决策过程中人工感觉和现有的手表示是如何组合的。参与者在这两种情况下组合和利用感觉反馈的能力有显著差异。参与者只能在一致的映射中成功地将先前的知识推广到新的姿势。此外,他在一致的映射中更准确和快速地学习姿势。最后,他在一致的映射中发展了对姿势之间关系的理解,而不是简单地记忆每个单独的姿势。这些实验结果得到了一个贝叶斯决策模型的支持,该模型跟踪了参与者的学习过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c304/7171192/e7df1dd86e11/41598_2020_62970_Fig1_HTML.jpg

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