自动任务负荷检测与脑电图:迈向被动脑机接口在机器人手术

T. Zander, K. Shetty, R. Lorenz, D. Leff, L. R. Krol, A. Darzi, K. Gramann, Guang-Zhong Yang
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引用次数: 27

摘要

实时自动检测手术室中外科医生的当前任务负荷可以提供有用的信息,用于支持系统。例如,此类信息可使系统在检测到关键或紧张时期时自动支持外科医生,或在外科医生从事复杂操作且不应被打扰时与他人通信。被动脑机接口(BCI)通过监测和解释脑电图记录的持续大脑活动来推断认知和情感状态的变化。由此产生的信息可用于自动调整技术系统以适应人类用户。到目前为止,被动式脑机接口主要是在实验室环境中进行研究,尽管它们的目的是在现实环境中应用。在这项研究中,被动式脑机接口被用于评估熟练外科医生执行简单和复杂手术训练任务时任务负荷的变化。结果表明,所提出的方法具有良好的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Task Load Detection with Electroencephalography: Towards Passive Brain-Computer Interfacing in Robotic Surgery
Automatic detection of the current task load of a surgeon in the theatre in real time could provide helpful information, to be used in supportive systems. For example, such information may enable the system to automatically support the surgeon when critical or stressful periods are detected, or to communicate to others when a surgeon is engaged in a complex maneuver and should not be disturbed. Passive brain–computer interfaces (BCI) infer changes in cognitive and affective state by monitoring and interpreting ongoing brain activity recorded via an electroencephalogram. The resulting information can then be used to automatically adapt a technological system to the human user. So far, passive BCI have mostly been investigated in laboratory settings, even though they are intended to be applied in real-world settings. In this study, a passive BCI was used to assess changes in task load of skilled surgeons performing both simple and complex surgical training tasks. Results indicate that the introduced methodo...
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