CHS: Small: Collaborative Research: EEG-Guided Electrical Stimulation for Immersive Virtual Reality

CHS：小型：合作研究：脑电图引导的沉浸式虚拟现实电刺激

• 批准号: 1715858
• 负责人: Deniz Erdogmus
• 金额: $ 14.2万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1715858&HistoricalAwards=false
• 关键词: CHS; Small; Collaborative; Research; EEG

Spatial presence, in Virtual Reality (VR) terminology, refers to the perception (or illusion) of being physically present in a simulated environment. VR strives to create interactive environments that provide experiences of spatial presence through accurate delivery and perception of multimodal sensory stimuli. Research in VR spans fields ranging from neuroscience and medicine to gaming. While the computing and gaming industries have generated tremendous advances in hardware and software for graphics processing and 3D display technologies, VR systems still lack capabilities for providing users with haptic feedback (a sense of touch), which is crucial for generating truly immersive, real-world experiences. It is known that an increase in the feeling of spatial presence manifests itself in the form of increased brain activity. This research aims to achieve the control of haptic sensory stimulation adaptively, based on the changes in brain activity associated with perceptual responses elicited by sensory stimulation in VR environments. Project outcomes will include novel scientific discoveries and engineering enhancements that will make significant contributions to other areas of interest, such as prosthetic limbs, augmented reality, and telepresence applications. The project will help train a new generation of engineers skilled in addressing multidisciplinary challenges, while through outreach activities STEM careers will be promoted at the K-12 level.The research objective is to identify and analyze brain activity associated with the increased feeling of haptic spatial presence elicited by electro-tactile stimulation and measured through EEG, and to investigate closed-loop techniques to control electro-tactile stimulation for enhanced haptic presence in VR environments. Specifically, the project will: (1) develop an electrical haptic stimulation framework; (2) design analysis techniques to identify markers of haptic inputs in EEG; (3) establish control policies for adaptive electrical stimulation; and (4) evaluate and refine EEG-guided adaptive stimuli control framework in VR environments. In particular, the proposition to actuate haptic feedback through electrical stimulation is novel, while formulating design principles for model-based optimal EEG-guided closed-loop haptic feedback for immersive spatial presence is transformative. Additional innovative propositions to advance adaptive control under uncertainty and psychophysical investigations are unique; these present a potentially game-changing opportunity for VR system development and perhaps for general human-computer interaction.

在虚拟现实（VR）术语中，空间存在是指在模拟环境中物理存在的感知（或错觉）。VR致力于创造互动环境，通过准确传递和感知多模态感官刺激来提供空间存在的体验。VR的研究涵盖了从神经科学、医学到游戏等多个领域。虽然计算机和游戏行业在图形处理和3D显示技术的硬件和软件方面取得了巨大进步，但VR系统仍然缺乏为用户提供触觉反馈（一种触觉）的能力，而触觉反馈对于产生真正沉浸式的真实体验至关重要。众所周知，空间感的增强表现为大脑活动的增加。本研究旨在基于VR环境中感官刺激引发的与感知反应相关的大脑活动变化，实现对触觉感官刺激的自适应控制。项目成果将包括新的科学发现和工程改进，这将对其他感兴趣的领域做出重大贡献，如假肢、增强现实和远程呈现应用。该项目将帮助培养能够应对多学科挑战的新一代工程师，同时通过外展活动，STEM职业将在K-12阶段得到提升。研究目的是识别和分析与电触觉刺激引起的触觉空间存在感增加相关的大脑活动，并通过脑电图测量，并研究控制电触觉刺激增强VR环境中触觉存在感的闭环技术。具体而言，该项目将：(1)开发电触觉刺激框架；(2)设计分析技术识别EEG触觉输入标记；(3)建立自适应电刺激控制政策；(4)评估和完善VR环境下脑电图引导的自适应刺激控制框架。特别是，通过电刺激驱动触觉反馈的提议是新颖的，而为沉浸式空间存在制定基于模型的最佳eeg引导闭环触觉反馈的设计原则是变革性的。在不确定性和心理物理研究下推进自适应控制的其他创新主张是独一无二的；这些都为VR系统的开发以及一般的人机交互提供了一个潜在的改变游戏规则的机会。

项目成果

EEG-based trial-by-trial texture classification during active touch.

• DOI: 10.1038/s41598-020-77439-7
• 发表时间: 2020-11-27
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Eldeeb S;Weber D;Ting J;Demir A;Erdogmus D;Akcakaya M
• 通讯作者: Akcakaya M

A History-based Stopping Criterion in Recursive Bayesian State Estimation

递归贝叶斯状态估计中基于历史的停止准则

• DOI: 10.1109/icassp.2019.8683726
• 发表时间: 2019
• 期刊: Speech and Signal Processing (ICASSP
• 作者: Marghi, Yeganeh M.;Kocanaogullari, Aziz;Akcakaya, Murat;Erdogmus, Deniz
• 通讯作者: Erdogmus, Deniz

Optimal Modality Selection Using Information Transfer Rate for Event Related Potential Driven Brain Computer Interfaces

使用事件相关电位驱动脑机接口的信息传输率进行最佳模态选择

• 发表时间: 2020
• 期刊: ACM PETRA
• 作者: A. Kocanaogullari, M. Akcakaya

On Analysis of Active Querying for Recursive State Estimation

递归状态估计的主动查询分析

• DOI: 10.1109/lsp.2018.2823271
• 发表时间: 2018
• 期刊: IEEE Signal Processing Letters
• 影响因子: 3.9
• 作者: Kocanaogullari, Aziz;Erdogmus, Deniz;Akcakaya, Murat
• 通讯作者: Akcakaya, Murat

An Event-Driven AR-Process Model for EEG-Based BCIs With Rapid Trial Sequences

• DOI: 10.1109/tnsre.2019.2903840
• 发表时间: 2019-03
• 期刊: IEEE Transactions on Neural Systems and Rehabilitation Engineering
• 影响因子: 4.9
• 作者: P. Gonzalez-Navarro;Yeganeh M. Marghi;Bahar Azari;Murat Akçakaya;Deniz Erdoğmuş
• 通讯作者: P. Gonzalez-Navarro;Yeganeh M. Marghi;Bahar Azari;Murat Akçakaya;Deniz Erdoğmu&#x015F