BACKGROUND A lack of communication with people suffering from acquired brain injuries may lead to drawing erroneous conclusions regarding the diagnosis or therapy of patients. Information technology and neuroscience make it possible to enhance the diagnostic and rehabilitation process of patients with traumatic brain injury or post-hypoxia. In this paper, we present a new method for evaluation possibility of communication and the assessment of such patients' state employing future generation computers extended with advanced human-machine interfaces. METHODS First, the hearing abilities of 33 participants in the state of coma were evaluated using auditory brainstem response measurements (ABR). Next, a series of interactive computer-based exercise sessions were performed with the therapist's assistance. Participants' actions were monitored with an eye-gaze tracking (EGT) device and with an electroencephalogram EEG monitoring headset. The data gathered were processed with the use of data clustering techniques. RESULTS Analysis showed that the data gathered and the computer-based methods developed for their processing are suitable for evaluating the participants' responses to stimuli. Parameters obtained from EEG signals and eye-tracker data were correlated with Glasgow Coma Scale (GCS) scores and enabled separation between GCS-related classes. The results show that in the EEG and eye-tracker signals, there are specific consciousness-related states discoverable. We observe them as outliers in diagrams on the decision space generated by the autoencoder. For this reason, the numerical variable that separates particular groups of people with the same GCS is the variance of the distance of points from the cluster center that the autoencoder generates. The higher the GCS score, the greater the variance in most cases. The results proved to be statistically significant in this context. CONCLUSIONS The results indicate that the method proposed may help to assess the consciousness state of participants in an objective manner.

中文翻译：

---

使用人机界面对获得性脑损伤的参与者进行多因素意识水平评估。

背景技术与患有获得性脑损伤的人缺乏沟通可能导致得出关于患者的诊断或治疗的错误结论。信息技术和神经科学使增强脑外伤或缺氧后患者的诊断和康复过程成为可能。在本文中，我们提出了一种新的方法来评估交流的可能性，并使用扩展了高级人机界面的下一代计算机来评估此类患者的状态。方法首先，使用听觉脑干反应测量（ABR）评估昏迷状态下33位参与者的听力。接下来，在治疗师的协助下，进行了一系列基于计算机的交互式练习。参加者 使用眼睛注视跟踪（EGT）设备和脑电图EEG监视耳机监视动作。使用数据聚类技术处理收集的数据。结果分析表明，收集的数据和开发的基于计算机的处理方法适合评估参与者对刺激的反应。从EEG信号和眼动仪数据获得的参数与格拉斯哥昏迷量表（GCS）评分相关，并可以在GCS相关类别之间进行分离。结果表明，在脑电图和眼动仪信号中，发现了与意识有关的特定状态。在自动编码器生成的决策空间上，我们将它们视为离群值。为此原因，将具有相同GCS的特定人群分开的数值变量是自动编码器生成的距群集中心的点的距离的方差。在大多数情况下，GCS分数越高，差异越大。在这种情况下，结果证明具有统计学意义。结论结果表明，所提出的方法可能有助于客观地评估参与者的意识状态。