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Human in the Loop Cyber Physical Systems

Leader: 
Shen Feng
Member:  Filip Cuckov, Gabe Shaikh, Hang Zhang, Tianyu Xia, Xiao Zhao, Zhe Qu
Year:  2012
Agreement Nr:  1136027
Funding Agency: 
National Science Foundation
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This project develops a framework for design automation of cyber-physical systems to augment human interaction with complex systems that integrate across computational and physical environments. As a design driver, the project develops a Body/Brain Computer Interface (BBCI) for the population of functionally locked-in individuals, who are unable to interact with the physical world through movement and speech. The BBCI will enable communication with other humans through expressive language generation and interaction with the environment through robotic manipulators.

Utilizing advances in system-level design, this project develops a holistic framework for design and implementation of heterogeneous human-in-the-loop cyber-physical systems composed of physically distributed, networked components. It will advance BBCI technology by incorporating context aware inference and learning of task-specific human intent estimation in applications involving semi-autonomous robotic actuators and an efficient wireless communication framework.

One application of HLCPS is SSVEP based typing application. EEG signals are collected via passive electrodes from subject’s visual cortex.Then the EEG signals are fed into Analog Front End (AFE) which contains 3-stage amplification, low pass filter and driven right leg. The AFE, based on the OpenEEG project, is able to handle 8 channel EEG signals which are converted into digital signals by AD7606 ADC and sent to an embedded platform.

We build up the EEG signal acquisition tool chain based on the embedded platform TLL6527m. Under the control of BF527 processor, the peripheral Xilinx FPGA Spartan 3E is programmed for simultaneous data acquisition from the 8 output channels of AD7606, filtering and transferring to BF527 for further signal processing. Then the DSP plots samples on the LCD in real time and simultaneously sends them to MATLAB on a PC upon request.16 Channel EEG Cape for Beagle Bone Black (BBB)

On one hand, we prototype the heuristics and control program in MATLAB for fast implementation and validation. On the other hand, the MATLAB program can be synthesized into embedded C code running on the TLL6527m so as to have low power and portable solution.

In addition, a set of LED arrays with a centralized control board are designed for SSVEP stimulus under the control of FPGA.They can be well assembled with the embedded platform.

EEGu2:  Capstone 2015

References:
  1. Swaminathan M., Cabrera F., Pujol J., Muncuk U., Schirner G, Chowdhury K. Multi-path Model and Sensitivity Analysis for Galvanic Coupled Intra-body Communication through Layered Tissue. IEEE Transactions on Biomedical Circuits and Systems. In Press.
  2. Feng S, Quivira F, Schirner G. Framework for Rapid Development of Embedded Human-in-the-Loop Cyber-Physical Systems. International Conference on BioInformatics and BioEngineering; 2016.
  3. Feng S, Tang M, Quivira F, Dyson T, Cuckov F, Schirner G. An Embedded Device for Brain/Body Signal Acquisition and Processing. In: International Symposium on Rapid System Prototyping (RSP). Pittsburgh, PA; 2016.
  4. Swaminathan M., Schirner G, Chowdhury K. Optimization of Energy Efficient Relay Position for Galvanic Coupled Intra-body Communication. In: IEEE WCNC.; 2015.
  5. Swaminathan M, Pujol JS, Schirner G. Multi-path 2-Port Channel Characterization for Galvanic Coupled Intra-body Communication. In: BodyNets. London UK: International Conference on Body Area Networks; 2014.
  6. Schirner G, Erdogmus D, Chowdhury K, Padir T. The Future of Human-in-the-Loop Cyber-Physical Systems. IEEE Computer. 2013;46:36-45.

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