Stimulation-artifact characterization and removal for closed-loop BCI applications

More than two weeks ago

Enabling closed-loop brain-machine interfaces

Bi-directional brain-computer interfaces (BCIs) require simultaneous stimulation and recording to achieve closed-loop operation. Since the recorded data can be corrupted by large stimulation artifacts, there has been extensive research trying to develop techniques to detect and remove artifacts without distorting the signal of interest. However, due to the limited knowledge of the nature of the electrical artifacts and their variation caused by changes in the electrode-tissue interface, many of the proposed techniques are not effective for high-density BCI's.

The goal of this master thesis is to investigate the stimulation artifacts that are generated by high-density neural probes during micro- and macro-stimulation, and develop algorithms for automatic artifact detection and removal. The master student will be involved in lab measurements, modeling of important electrode-tissue characteristics, modelling of the analog front-end recording circuits and implementation of algorithms in FPGA.


Specific thesis objectives:

  • Study and understand the theory behind neural stimulation techniques and stimulation artifacts.
  • Create models of the electrode-tissue interface based on available devices and materials.
  • Create models of the analog front-end circuits to study the different mechanisms of channel saturation and neural-signal corruption.
  • Propose algorithms for artifact removal based on the available models.
  • Validate the proposed algorithms by designing a proof-of-concept setup with available neural probes and acquisition system (based on FPGA)



  • Interest and enthusiasm in signal processing and algorithms
  • Knowledge of Matlab
  • Knowledge of C++ and VHDL
  • Knowledge of analog IC design principles
  • Knowledge of Cadence IC design tools (Spectre, Virtuoso, etc.) is a plus

Type of project: Thesis

Duration: 9 months

Required degree: Master of Science, Master of Engineering Science, Master of Bioengineering

Required background: Electrotechnics/Electrical Engineering, Biomedical engineering

Supervising scientist(s): For further information or for application, please contact: Carolina Mora Lopez (

Imec allowance will be provided.

Share this on


This website uses cookies for analytics purposes only without any commercial intent. Find out more here. Our privacy statement can be found here. Some content (videos, iframes, forms,...) on this website will only appear when you have accepted the cookies.

Accept cookies