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、心理生理技术、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35岁以下,研究人员分别具有计算机、医学、信息处理等专业背景,目前有教授1人,副教授5人,讲师3人,以及一批在读博士、硕士研究生人员。实验室近年来承担了国家自然科学基金、国家“973”计划、科技部国际合作、欧盟国际合作、企业合作、兰州大学“985”与“211”建设等科研项目,并与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。


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.