EUNIL research role: Jan 2016 – Oct 2019.
Biomedical sensing
Non-Invasive Neural Recording Hardware
EUNIL research across low-noise neural recording, 4D acoustoelectric current-density imaging, analog front-end optimization, EMI control, DSP/wavelets, and experimental phantoms.
Part of Research Technician · EUNIL / University of Arizona · Jan 2016 – Oct 2019
completed2016–2019SensingLow-noise hardwareDSPNeural recording
Typeresearch hardware
SkillsLow-noise acquisition, DSP, Acoustoelectric imaging, Experimental phantoms
Selected facts
Quantitative details and source-backed proof points.
Work covered non-invasive neural recording, current-density simulation, low-noise amplifiers, amplifier optimization, EMI control, DSP, wavelets, and experimental phantoms.
Built and optimized front-end hardware and experimental workflows for 4D acoustoelectric current-density imaging.
Presented the work at BMES 2017 and IEEE IUS 2018.
Project summary
Why it exists, what I built, and what I learned.
Why I built it
Non-invasive current-density imaging required detecting weak acoustoelectric signals through low-noise hardware, controlled phantoms, and synchronized signal processing.
What I built
Low-noise amplifiers and interconnects, 4D acoustoelectric imaging instrumentation, tissue-equivalent phantoms, current-density simulations, and MATLAB/DSP analysis workflows.
What worked
Signal fidelity improved when circuit optimization, grounding, shielding, EMI control, phantom design, and processing were treated as one measurement system.
What failed
Weak acoustoelectric signals were sensitive to electrical noise, coupling, interconnects, phantom setup, and processing assumptions, so hardware and analysis had to be debugged together.
What I learned
Reliable neural sensing starts with low-noise acquisition and controlled experimental setups before advanced signal interpretation.
Stack
Tools, systems, and technical areas involved.
Analog sensingLow-noise amplifiersEMI controlDSPWaveletsPhantomsMATLABAcoustoelectric imaging
Links and direction
Public links and next steps.
Use this page as supporting evidence for non-invasive neural recording, low-noise instrumentation, and signal-quality depth.
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