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首页> 外文会议>International Conference on Augmented Cognition >A Wearable Multisensory, Multiagent Approach for Detection and Mitigation of Acute Cognitive Strain: Phase I - Vocalization analysis
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A Wearable Multisensory, Multiagent Approach for Detection and Mitigation of Acute Cognitive Strain: Phase I - Vocalization analysis

机译：急性认知菌株检测和减轻的可穿戴多误，多态方法：I相 - 发声分析

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While operators performing tasks with high workload can increase task performance in response to limited increases in cognitive stress, chronic or rapidly accelerating stress can exceed the operator's ability to compensate, generating acute cognitive strain (ACS). ACS represents a state wherein performance, situation awareness and cooperativity deteriorate markedly, leading to critical errors, mishaps or casualties. Nearly two decades of augmented cognition (AugCog) research has demonstrated the utility of psychophysiologic sensing and analysis for identification and tracking of changes in cognitive state and to modulate human machine interactions for improving system task performance. The proposed approach leveraged prior efforts to modulate cognitive stress using a multiagent approach to acquire and analyze multiple Psychophysiologic sensory channels, including changes in vocalizations, to create a reliable and non-intrusive Detector of Acute Cognitive Strain (DACS). The DACS system provides an integrated wearable multi-modal Research Sensor Suite (RSS) using the open-source Adaptive Multiagent Integration (AMI) architecture, that includes analysis agents for electroencephalograph (EEG), electromyography (EMG), video oculography (VOG), vocalization, and others to identify and correlate physiological signatures with cognitive stress and strain. An online AMI agent-based processing algorithm was developed and applied to audio communications to evaluate for changes in speaker vocalization fundamental frequency (F0) and cadence (utterances per minute). This paper describes initial phase results of aerospace mishap vocalization stress marker detection, a potential element of the proposed DACS system. DACS could use these markers to trigger adaptive automation agents that reduce task load and allow pilots to prevent or recover from ACS episodes.
机译：虽然具有高工作量的任务的操作员可以响应于认知应力的有限增加而增加任务性能，但慢性或快速加速的应力可能超过操作者补偿，产生急性认知应变（ACS）的能力。 AC表示一种状态，其中性能，情况意识和合作性显着恶化，导致临界错误，误会或伤亡。近二十年的增强认知（Augcog）研究已经证明了心理生理传感和分析的鉴定和追踪认知状态的变化，并调制人机相互作用来提高系​​统任务性能。所提出的方法利用事先努力使用多层方法来调节认知应力来获取和分析多种心理生理感官信道，包括发声的变化，以创造急性认知菌株（DAC）的可靠和非侵入性的检测器。 DACS系统提供了一种使用开源自适应多态集成（AMI）架构的集成可穿戴多模态研究传感器套件（RSS），包括用于脑电图（EEG），肌电学（EMG），视频身份（VOG）的分析代理，发声，以及其他与认知压力和应变的生理签名。开发了在线AMI代理的处理算法，并应用于音频通信，以评估扬声器发声基基频率（F0）和Cadence（每分钟的话语）的变化。本文介绍了航空航天Mishap发作应力标记检测的初始相位结果，该潜在元件的潜在元件的提出的DACS系统。 DAC可以使用这些标记来触发自适应自动化代理，减少任务负载并允许导频防止或从ACS剧集中恢复。

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