Energy-efficient DSP Solutions for Simultaneous Neural Recording and Stimulation

Speaker: Sina Basir-Kazeruni
Affiliation: Ph.D. Candidate - UCLA

Abstract:  Development of neural stimulation and signal recording systems have enabled a better understanding of underlying neurological diseases, and closed-loop neuromodulation systems provide promising therapeutic interventions for various neurological disorders.  The ability to simultaneously stimulate and record is a key capability required in enabling such systems.

One common difficulty in realizing concurrent stimulation and recording of neural signals is the presence of stimulation artifacts observed at the sensing end. Existing solutions (e.g., blanking the recording channel during stimulation or self-cancelling stimulation electrodes) have not answered all the challenges and lack the ability of continuous signal recording during the stimulation phase, thus rendering a critical portion of the data unusable. To resolve this issue, we propose an energy-efficient Adaptive Stimulation Artifact Rejection (ASAR) solution capable of adaptively removing stimulation artifact for varying stimulation characteristics at multiple sites. Additionally, a blind artifact template detection technique is introduced, which in combination with the proposed ASAR algorithm, eliminates the need for any prior knowledge of the temporal and structural characteristics of the stimulation pulse. ASAR has been implemented in 40nm CMOS and integrated in our implantable, wireless, closed-loop neuromodulation system.

Biography:  Sina Basir-Kazeruni is a PhD candidate and a Teaching Fellow in the Department of Electrical and Computer Engineering at the University of California, Los Angeles (UCLA). Sina has interned at various companies including NVIDIA, Synopsys, and Honeywell aerospace. His research interests include design and optimization of various digital integrated circuits and power/area-efficient VLSI systems. His doctoral research focuses on implementation of ultra-low-power DSP solutions for implantable, closed-loop neuromodulation systems and other biomedical applications. He is a recipient of Samueli Fellowship, UCLA Dissertation Year Fellowship (DYF) and was awarded the UCLA EE Excellence in Teaching Award in 2012 and 2017.  Sina holds a MS degree in Electrical Engineering from UCLA; prior to that, he completed his BASc in Electrical Engineering at the University of Waterloo in Canada.

For more information, contact Prof. Dejan Markovic (dejan@ee.ucla.edu)

Date/Time:
Date(s) - Aug 18, 2017
12:00 pm - 2:00 pm

Location:
E-IV Tesla Room #53-125
420 Westwood Plaza - 5th Flr., Los Angeles CA 90095