A Micro-Power EEG Acquisition SoC With Integrated Feature Extraction Processor for a Chronic Seizure Detection System
By Naveen Verma, Ali H. Shoeb, Jose L. Bohorquez, Joel L. Dawson, John V. Guttag, Anantha P. Chandrakasan. IEEE Journal of Solid-State Circuits, 2010
536 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Cellular and Molecular Neuroscience, Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/d57f04ddfd995868f10fdf9a9d98acd0501e9239
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- Omid Salehi-Abari
- Vladimir Marko Stojanovic
- Fred Chen
- Fabian Lim
- Jan M. Rabaey
- Anantha P. Chandrakasan
- Alper Erturk
- Daniel J. Inman
In Cellular and Molecular Neuroscience
In Cognitive Neuroscience
Citations in the corpus
- Design and Analysis of a Hardware-Efficient Compressed Sensing Architecture for Data Compression in Wireless Sensors (2012, background): “Meanwhile, feature extraction approaches require training, are usually signal specific and typically provide only macro level decisions based on the original signals [6], [7].”
- A Batteryless 19 $\mu$W MICS/ISM-Band Energy Harvesting Body Sensor Node SoC for ExG Applications (2013, unknown): “An SoC for EEG seizure detection integrates a COTS radio and does not include voltage regulation or power management [6].”
- Energy-Aware Design of Compressed Sensing Systems for Wireless Sensors Under Performance and Reliability Constraints (2013, background): “Common functional blocks within a wireless sensor node and their associated energy costs from state-of-the-art publications [3]–[13]. of transmitted data.”
- A Minimally Invasive 64-Channel Wireless μECoG Implant (2015, background): “low-noise EEG/ECoG amplifiers have been reported in recent literature [22]–[25].”