The key requirements of a reliable neural signal recording system include low power to support long-term monitoring, low noise, minimum tissue damage, and wireless transmission. The neural spikes are also detected and sorted on-chip/off-chip to implement closed-loop neuromodulation in a high channel count setup. All these features together constitute an empirical neural recording system for neuroscience research. In this prospectus, we propose to develop a neural signal acquisition system with wireless transmission and feature extraction. We start by designing a prototype entirely built with commercial-off-the-shelf components, which includes recording and wireless transmission of synthetic neural data and feature extraction. We then conduct the CMOS implementation of the low-power multi-channel neural signal recording read-out circuit, which enables the in-vivo recording with a small form factor. Another direction of this thesis is to design a self-powered motion tracking read-out circuit for wearable sensors. As the wearable industry continues to advance, the need for self-powered medical devices is growing significantly. In this line of research, we propose a self-powered motion sensor based on reverse electrowetting-on-dielectric (REWOD) with low-power integrated electronics for remotely monitoring health conditions. We design the low-power read-out circuit for a wide range of input charges, which is generated from the REWOD sensor.
| Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc1944354 |
| Date | 05 1900 |
| Creators | Tasneem, Nishat Tarannum |
| Contributors | Mahbub, Ifana, Mehta, Gayatri, Namuduri, Kamesh, Kaul, Anupama, Qu, WenChao |
| Publisher | University of North Texas |
| Source Sets | University of North Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | Text |
| Rights | Public, Tasneem, Nishat Tarannum, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved. |
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