BraiNet: Pervasive Brain Monitoring Framework

Department of Computer Science and Engineering, Arizona State University

Faculty Advisor

Sandeep K.S. Gupta
Professor
Department of Computer Science and Engineering
Arizona State University
sandeep.gupta@asu.edu

Research Faculty

Present Students

Sponsers


Vision

BraiNet is a network of individual Brain-Computer Interface (BCI) systems. BraiNet is a pervasive brain monitoring system to develop BCI apps in societal level.

We envision the following set of goals:

  • Pervasive Brain Monitoring
  • Recognizing Mental States On-the-Go
  • Providing On-line Feedback to the User

There are four main challenges:

  • Setup Procedure and Usability
  • Accurate Recognition of Mental States
  • Real-time Feedback to the User
  • Energy Efficiency on Mobile Platform

Brain-Computer Interface Systems:

Brain-Computer Interface (BCI) systems provide a direct connection between neural activies and computing devices.

BCI System Model


Signal Acquisition:

To enhance usability of our apps, we use commercially available sensors. These sensors are connected to mobile phone via Bluetooth.


Signal Processing:

To satisfy accuracy, real-timing, and energy efficiency of BCI apps, computational intensive signal processing is implemented in multi-tier architecture including fog and cloud servers.

BraiNet Infrastructure


Applications:

Based on the BraiNet framework, we have developed following mobile apps:

  • SafeDrive: An Intelligent Driver Safety Application: According to mental states of drivers, appropriate warning message will be provided to avoid accidents
  • SafeDrive App

  • E-BIAS: A Pervasive EEG-Based Identification and Authentication System: Each person has unique brain signal patterns. These patterns can be considered as signatures for identification and authentication in security systems
  • EBIAS App

  • nMovie: BCI-based Interactive Movie Experience: According to mental state of the viewer, the movie scene may change
  • nMovie App

  • AyLA: An Intelligent Learning Assistant Based on Mental States: According to students attention level, the lecture materials may change [ongoing project
  • AyLA App


Publications

  • K. Sadeghi, A. Banerjee, and S. K. S. Gupta, Neuro Movie Theatre: A Real-Time Internet-of-People Based Mobile Application, The 16th ACM International Workshop on Mobile Computing Systems and Applications, Santa Fe, NM, 2015. [ PDF ]

  • M. Pore, K. Sadeghi, V. Chakati, A. Banerjee, and S. K. S. Gupta, Enabling Real-Time Collaborative Brain-Mobile Interactive Applications on Volunteer Mobile Devices, The 2nd ACM Workshop on Hot Topics in Wireless, Paris, France, 2015. [ PDF ]

  • J. Sohankar, K. Sadeghi, A. Banerjee, and S. K. S. Gupta, E-BIAS: A Pervasive EEG-Based Identification and Authentication System, The 11th ACM International Symposium on QoS and Security for Wireless and Mobile Networks, Cancun, Mexico, 2015. [ PDF ]

  • K. Sadeghi, A. Banerjee, J. Sohankar, and S. K. S. Gupta, SafeDrive: An Autonomous Driver Safety Application in Aware Cities, The First International Workshop on Context-Aware Smart Cities and Intelligent Transport Systems, AwareCities (PerCom 2016 Workshop), Sydney Australia, 14-18 March 2016. [ PDF ]


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Last Updated: 12th May 2008