Thanks to the rapid growth in wearable technologies and recent advancement in machine learning and signal processing, monitoring complex human contexts becomes feasible, paving the way to develop human-in-the-loop IoT systems that naturally evolve to adapt to the human and environment state autonomously. Nevertheless, a central challenge in designing many of these IoT systems arises from the requirement to infer the human mental state, such as intention, stress, cognition load, or learning ability. While different human contexts can be inferred from the fusion of different sensor modalities that can correlate to a particular mental state, the human brain provides a richer sensor modality that gives us more insights into the required human context. This paper proposes ERUDITE, a human-in-the-loop IoT system for the learning environment that exploits recent wearable neurotechnology to decode brain signals. Through insights from concept learning theory, ERUDITE can infer the human state of learning and understand when human learning increases or declines. By quantifying human learning as an input sensory signal, ERUDITE can provide adequate personalized feedback to humans in a learning environment to enhance their learning experience. ERUDITE is evaluated across $15$ participants and showed that by using the brain signals as a sensor modality to infer the human learning state and providing personalized adaptation to the learning environment, the participants' learning performance increased on average by $26\%$. Furthermore, we showed that ERUDITE can be deployed on an edge-based prototype to evaluate its practicality and scalability.
翻译:由于可磨损技术的迅速增长以及最近在机器学习和信号处理方面的进步,监测复杂的人类环境变得可行,为开发自然演变以适应人类和环境状态的人类在环形IOT系统铺平了道路,然而,设计许多IOT系统的一个中心挑战来自需要推断人类的精神状态,例如意图、压力、认知负荷或学习能力等。不同的人类环境可以从不同传感器模式的融合中推断出来,这些模式可以与特定的精神状态相关,而人类大脑则提供更丰富的感官模式,使我们更深入了解所需的人类环境。本文建议EUDITE, 一种人在环形图中为学习环境的人类在环形图中,利用最近可磨损的神经技术解码大脑信号。通过从概念学习理论的洞察,ERUDITE可以推断人类学习和理解在人类学习基础上增加或下降时的人类状况。通过将人类学习作为输入感官传感器信号的量化,ERUDITE可以向人类在学习环境中提供充分的个性化反馈。通过学习学习环境来提高个人学习程度,在人类的学习模式中显示个人学习程度环境的学习,通过学习方式向个人学习方式显示其15。</s>