Sivylla E. Paraskevopoulou

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—This paper presents a novel front-end circuit for detecting action potentials in extracellular neural recordings. By implementing a real-time, adaptive algorithm to determine an effective threshold for robustly detecting a spike, the need for calibration and/or external monitoring is eliminated. The input signal is first pre-processed by utilising a(More)
This paper presents an AC-coupled instrumentation amplifier for electroneurogram (ENG) activity recording. For this design, we evaluate gain and noise requirements based on interference sources (electrodes, power line, EMG). The circuit has been implemented in a commercially-available 0.35μm CMOS technology with total power consumption 460μW. The amplifier(More)
—This paper presents a dynamic front-end towards achieving unsupervised single-neuron activity monitoring. By implementing at the front-end, an automatic gain control that is optimized for neural signal dynamics, subsequent processing can be achieved without the need for calibration. The system uses three amplification stages (low-noise first stage,(More)
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