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Estimating Subjective Assessments Using a Simple Biosignal Sensor

机译:使用简单的生物信号传感器估算主观评估

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Given a remarkable recent progress in robotics research, we can envision the day when robots and humans coexist and robots become closely integrated into our daily lives. This means endowing robots with the ability to communicate so they perceive human emotion, adapt their behavior to humans, and sense situations even without explicit instructions. Meanwhile, affective computing, that interprets emotion or other affective phenomena from human biosignals, has emerged as an area of great interest. In addition to biosignals-brain waves, heart rate, pulse, electrical activity, and the like-affective computing is concerned with facial expressions, gestures, and a wide range of other indicators of emotion. Here we explore the latest insights of affective computing in relation to human-robot interaction (HRI). There is good reason to believe robots will soon have the ability to read human emotions, so here we investigate the feasibility of inferring human psychological states from biosensor signals. Obviously, non-invasive biosensors that don't interfere with normal everyday activities would be preferable. A number of inexpensive user-friendly brain-wave sensors have been brought to market recently, and we employ one of these devices, the Neuro Sky Mindset EEG neuroheadset, in assessment trials to explore the feasibility of inferring subjective assessments. Using our experimental setup, we find that it is indeed possible to infer subjective assessments from biosignals, and this capability could prove immensely useful for future HRI applications.
机译:鉴于近期机器人技术研究取得显着进展,我们可以预见机器人与人类共存,机器人与日常生活紧密结合的一天。这意味着赋予机器人进行交流的能力,以便他们即使没有明确的指示也可以感知人类的情感,适应人类的行为并感知情况。同时,从人类生物信号中解释情感或其他情感现象的情感计算已经成为人们关注的领域。除了生物信号外,脑电波,心率,脉搏,电活动和类似情感的计算还涉及面部表情,手势和各种其他情绪指标。在这里,我们探索与人机交互(HRI)相关的情感计算的最新见解。有充分的理由相信机器人将很快具有读取人类情绪的能力,因此在此我们研究从生物传感器信号推断人类心理状态的可行性。显然,不干扰正常日常活动的非侵入性生物传感器将是更好的选择。最近,许多廉价的用户友好型脑波传感器已经投放市场,我们在评估试验中采用了其中一种设备NeuroSky Mindset EEG神经耳机,以探索推断主观评估的可行性。使用我们的实验设置,我们发现确实有可能从生物信号中推断出主观评估,并且这种能力可能被证明对未来的HRI应用非常有用。

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