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Review Article | Open Access

An introduction and review on innovative silicon implementations of implantable/scalp EEG chips for data acquisition, seizure/behavior detection, and brain stimulation

College of Information Engineering, Shenzhen University, Shenzhen 518000, Guangdong, China
College of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, Guangdong, China
School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518000, Guangdong, China
Peng Cheng Laboratory, Shenzhen 518055, Guangdong, China
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Abstract

Technological advances in the semiconductor industry and the increasing demand and development of wearable medical systems have enabled the development of dedicated chips for complex electroencephalogram (EEG) signal processing with smart functions and artificial intelligence-based detections/classifications. Around 10 million transistors are integrated into a 1 mm2 silicon wafer surface in the dedicated chip, making wearable EEG systems a powerful dedicated processor instead of a wireless raw data transceiver. The reduction of amplifiers and analog-digital converters on the silicon surface makes it possible to place the analog front-end circuits within a tiny packaged chip; therefore, enabling high-count EEG acquisition channels. This article introduces and reviews the state-of-the-art dedicated chip designs for EEG processing, particularly for wearable systems. Furthermore, the analog circuits and digital platforms are included, and the technical details of circuit topology and logic architecture are presented in detail.

Keywords

biomedical chipwearable EEG systemdigital system chipenergy-efficient circuitEEG signal acquisition

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Brain Science Advances
Volume 6 Issue 3,
September 2020
Pages 242-254
DOI: 10.26599/BSA.2020.9050024
Cite this article:
Shi W, Zhang J, Zhang Z, et al. An introduction and review on innovative silicon implementations of implantable/scalp EEG chips for data acquisition, seizure/behavior detection, and brain stimulation. Brain Science Advances, 2020, 6(3): 242-254. https://doi.org/10.26599/BSA.2020.9050024

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Received: 29 July 2020
Revised: 11 August 2020
Accepted: 09 September 2020
Published: 04 February 2021
© The authors 2020

This article is published with open access at journals.sagepub.com/home/BSA

Creative Commons Non Commercial CC BY- NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/ en-us/nam/open-access-at-sage).
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