Mathôt Sebastiaan, Melmi Jean-Baptiste, van der Linden Lotje, Van der Stigchel Stefan
Aix-Marseille University, CNRS, LPC UMR 7290, Marseille, France.
Dept. of Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands.
PLoS One. 2016 Feb 5;11(2):e0148805. doi: 10.1371/journal.pone.0148805. eCollection 2016.
We present a new human-computer interface that is based on decoding of attention through pupillometry. Our method builds on the recent finding that covert visual attention affects the pupillary light response: Your pupil constricts when you covertly (without looking at it) attend to a bright, compared to a dark, stimulus. In our method, participants covertly attend to one of several letters with oscillating brightness. Pupil size reflects the brightness of the selected letter, which allows us-with high accuracy and in real time-to determine which letter the participant intends to select. The performance of our method is comparable to the best covert-attention brain-computer interfaces to date, and has several advantages: no movement other than pupil-size change is required; no physical contact is required (i.e. no electrodes); it is easy to use; and it is reliable. Potential applications include: communication with totally locked-in patients, training of sustained attention, and ultra-secure password input.
我们展示了一种基于通过瞳孔测量法解码注意力的新型人机界面。我们的方法建立在最近的一项发现之上，即隐蔽的视觉注意力会影响瞳孔对光的反应：当你隐蔽地（不看它）关注一个明亮的刺激物而非黑暗的刺激物时，你的瞳孔会收缩。在我们的方法中，参与者隐蔽地关注几个亮度不断变化的字母中的一个。瞳孔大小反映了所选字母的亮度，这使我们能够高精度且实时地确定参与者想要选择的是哪个字母。我们方法的性能与迄今为止最好的隐蔽注意力脑机接口相当，并且有几个优点：除了瞳孔大小变化外无需其他动作；无需身体接触（即无需电极）；易于使用；且可靠。潜在应用包括：与完全闭锁综合征患者进行通信、持续注意力训练以及超安全密码输入。
