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人类能够在对机器人手的感觉运动控制中整合离散事件的反馈。

Humans can integrate feedback of discrete events in their sensorimotor control of a robotic hand.

作者信息

Cipriani Christian, Segil Jacob L, Clemente Francesco, ff Weir Richard F, Edin Benoni

机构信息

The BioRobotics Institute, Scuola Superiore Sant'Anna, V.le Piaggio 34, 56025, Pontedera (PI), Italy,

出版信息

Exp Brain Res. 2014 Nov;232(11):3421-9. doi: 10.1007/s00221-014-4024-8. Epub 2014 Jul 4.

Abstract

Providing functionally effective sensory feedback to users of prosthetics is a largely unsolved challenge. Traditional solutions require high band-widths for providing feedback for the control of manipulation and yet have been largely unsuccessful. In this study, we have explored a strategy that relies on temporally discrete sensory feedback that is technically simple to provide. According to the Discrete Event-driven Sensory feedback Control (DESC) policy, motor tasks in humans are organized in phases delimited by means of sensory encoded discrete mechanical events. To explore the applicability of DESC for control, we designed a paradigm in which healthy humans operated an artificial robot hand to lift and replace an instrumented object, a task that can readily be learned and mastered under visual control. Assuming that the central nervous system of humans naturally organizes motor tasks based on a strategy akin to DESC, we delivered short-lasting vibrotactile feedback related to events that are known to forcefully affect progression of the grasp-lift-and-hold task. After training, we determined whether the artificial feedback had been integrated with the sensorimotor control by introducing short delays and we indeed observed that the participants significantly delayed subsequent phases of the task. This study thus gives support to the DESC policy hypothesis. Moreover, it demonstrates that humans can integrate temporally discrete sensory feedback while controlling an artificial hand and invites further studies in which inexpensive, noninvasive technology could be used in clever ways to provide physiologically appropriate sensory feedback in upper limb prosthetics with much lower band-width requirements than with traditional solutions.

摘要

为假肢使用者提供功能有效的感觉反馈在很大程度上仍是一个未解决的挑战。传统的解决方案需要高带宽来提供用于控制操作的反馈,但在很大程度上并不成功。在本研究中,我们探索了一种依赖于时间上离散的感觉反馈的策略,这种反馈在技术上易于提供。根据离散事件驱动的感觉反馈控制(DESC)策略,人类的运动任务是以由感觉编码的离散机械事件界定的阶段来组织的。为了探索DESC在控制方面的适用性,我们设计了一种范式,让健康人操作一个人造机器人手来提起并替换一个装有仪器的物体,这是一个在视觉控制下很容易学习和掌握的任务。假设人类的中枢神经系统自然地基于一种类似于DESC的策略来组织运动任务,我们提供了与已知会有力影响抓握-提起-握持任务进展的事件相关的短暂振动触觉反馈。训练后,我们通过引入短暂延迟来确定人工反馈是否已与感觉运动控制整合,我们确实观察到参与者显著延迟了任务的后续阶段。因此,本研究支持了DESC策略假说。此外,它表明人类在控制人造手时可以整合时间上离散的感觉反馈,并促使进一步开展研究,在这些研究中,可以巧妙地使用廉价的非侵入性技术,以比传统解决方案低得多的带宽要求,在上肢假肢中提供生理上合适的感觉反馈。

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