普适感知与智能系统实验室(UAIS实验室)成立于2009年1月,依托兰州大学信息科学与工程学院,主要在普适计算理论与应用、心理生理信息感知、情感计算、语义网与本体论等领域展开研究工作。实验室实行学术委员会指导下的实验室主任负责制,拥有一支具有多学科交叉特点的年轻研究团队,平均年龄在40岁以下,研究人员分别具有计算机、信息处理、传感器研发、心理学、临床医学等专业背景。目前有正高级教师6人,副高级教师5人,中职人员8人,以及一批在读博士、硕士研究生人员。其中入选国家人才计划2人,甘肃省领军人才计划1人,全国先进工作者1人,具有海外留学经历教师5人。实验室承担了开源软件与实时系统教育部工程中心、西部特征人群普适情感计算国际科技合作基地、甘肃省可穿戴装备重点实验室、中国科学院半导体研究所——兰州大学认知神经传感技术联合研究中心等科研平台的建设工作。近年来承担了国家自然科学基金、国家“973”计划、国家重点研发计划、军委科技委国防科技创新特区、科技部国际合作、欧盟国际合作、企业合作以及兰州大学“985”与“211”建设等科研项目,并与瑞士苏黎世联邦理工等国内外科研单位建立联合实验室,加强国际交流,共同培养高水平的科技人才。实验室团队成员先后获得2014年中国侨界创新人才奖、2016年度教育部技术发明一等奖、2017年度甘肃省专利二等奖、2018年度国家技术发明二等奖、2019年度中国专利金奖等奖项。


研究概述

With innovative developments in Computer Science, e.g. Pervasive Computing, Affective/Cognitive Computing, and their amazing applications, the Human Computer Interaction (HCI) has been impacted by some emerging research and technologies, such as, Brain-Computer Interface (BCI), Electrocenphlogram Interface (EEGI), NHCI/NI (Neural Human-Computer Interface), and Cognitive Interaction etc. I believe that Cognitive/Neural Interface, no matter what it should be called, may perhaps be one of the most promising and life altering technologies in existence today. The implementation of these technologies could launch the world into a new era, especially, in the ways of Assisted living, Health Care, E-commerce, Security (Biometrics), Learning, like Stephen Hawking said: “We must develop as quickly as possible technologies that make possible a direct connection between brain and computer, so that artificial brains contribute to human intelligence rather than opposing it.”
My research on Cognitive/Neural Interface is evolved in three layers: Mechanisms between Human Affect/Emotion and Bio-information (Brain:fMRI/EEG, Body:ECG/EMG/Eyes-tracking…); Bio-information Pattern Analysis and Features Extraction; Multimodal information Modeling. (Fig.1)

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Fig. 1. Research on Cognitive/Neural Interface
The core layer focuses on investigating the connections and meanings between Human Affect/emotion and Bio-information through analyzing the feedbacks from EEG/ECG/EMG, fMRI etc.
The middle layer means to develop mathematical algorithms for Bio-signals de-noising, extracting Bio-data features and analyzing individual’s pattern.
The edge layer will develop multimodal data modeling and inference methodologies for combination of Bio-data features with other types of context factors, e.g. user profiles and activities, then build standard interface to variable applications.

Although there are still some challenges to research in the subject before such a solution can transcend our being, I believe that innovations in the world in the near future will unveil these ingenious emerging technologies and bring them to us.