This paper addresses both the various EEG applications and the current EEG market ecosystem propelled by machine learning. Increasingly available open medical and health datasets using EEG encourage data-driven research with a promise of improving neurology for patient care through knowledge discovery and machine learning data science algorithm development. This effort leads to various kinds of EEG developments and currently forms a new EEG market. This paper attempts to do a comprehensive survey on the EEG market and covers the six significant applications of EEG, including diagnosis/screening, drug development, neuromarketing, daily health, metaverse, and age/disability assistance. The highlight of this survey is on the compare and contrast between the research field and the business market. Our survey points out the current limitations of EEG and indicates the future direction of research and business opportunity for every EEG application listed above. Based on our survey, more research on machine learning-based EEG applications will lead to a more robust EEG-related market. More companies will use the research technology and apply it to real-life settings. As the EEG-related market grows, the EEG-related devices will collect more EEG data, and there will be more EEG data available for researchers to use in their study, coming back as a virtuous cycle. Our market analysis indicates that research related to the use of EEG data and machine learning in the six applications listed above points toward a clear trend in the growth and development of the EEG ecosystem and machine learning world.
翻译:本文论述各种电子环境小组应用和目前由机器学习推动的当前电子环境小组市场生态系统; 越来越多的公开医疗和健康数据集利用电子环境小组鼓励数据驱动的研究,并有望通过知识发现和机器学习数据算法开发改善病人护理神经学; 这一努力导致各种电子环境小组的发展,目前形成一个新的电子环境小组市场; 本文试图对电子环境小组市场进行全面调查,并涵盖电子环境小组的六个重要应用,包括诊断/筛选、药物开发、神经营销、日常健康、逆向和年龄/残疾援助; 本调查的重点是研究领域和商业市场之间的对比和对比; 我们的调查指出了目前电子环境小组的局限性,并指明了上述每一种电子环境小组应用的未来研究方向和商业机会; 根据我们的调查,更多关于基于机器学习的电子环境小组应用的研究将导致更强有力的电子环境小组的市场。 随着与电子环境小组有关的市场的增长,与电子环境小组有关的设备将收集更多的电子环境小组数据,并在EEEE的计算机应用中进行更清晰的学习。