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You searched for id:"oai:etd.ohiolink.edu:akron1533124706225894". One record found.

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University of Akron

1. Hoseini, Seied Zaniar, Hoseini. MULTI-CHANNEL EEG SENSOR FRONTEND FOR PORTABLEHEALTH CONDITION MONITORING APPLICATIONS.

Degree: PhD, Electrical Engineering, 2018, University of Akron

This work presents two neuro signal amplifiers and a time-mode successive approximation register (SAR) analog to digital converter (ADC) for Electroencephalography (EEG) sensor frontend. The first amplifier is a low power capacitive-coupled instrumentation amplifier (CCIA) which achieves a power consumption of 540nW. This amplifier is capable of cancelling a rail to rail electrode offset, where a high input impedance is obtained by adding voltage buffers at the input node. The second amplifier is a current feedback instrumentation amplifier (CFIA), that has a very high input impedance, high CMRR and high PSRR which makes it robust against the motion artifacts. A DC offset cancellation loop is added to the conventional CFIA to effectively cancel ±300mV of electrode offset without sacrificing its other benefits. In the ADC side, reducing the area was the main focus of the design, so the ADC can be used in multi-channel EEG sensor frontends. An 8-bit 364.9kS/s SAR ADC that replaces the conventional capacitive DAC with a single-capacitor single-current source time-mode DAC is realized. The proposed ADC shows significant area reduction compared to state of the art ADCs with similar resolution and conversion speed.Overall, the contributions of this work are realizing a power efficient CCIA through design optimization, developing a new CFIA architecture to improve DC electrode offset cancelation range, and implementing a very small size ADC that can improve the performance of EEG sensor frontends, while reducing the power consumption and area. Advisors/Committee Members: Lee, Kye-Shin (Advisor).

Subjects/Keywords: Biomedical Engineering; Electrical Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hoseini, Seied Zaniar, H. (2018). MULTI-CHANNEL EEG SENSOR FRONTEND FOR PORTABLEHEALTH CONDITION MONITORING APPLICATIONS. (Doctoral Dissertation). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1533124706225894

Chicago Manual of Style (16th Edition):

Hoseini, Seied Zaniar, Hoseini. “MULTI-CHANNEL EEG SENSOR FRONTEND FOR PORTABLEHEALTH CONDITION MONITORING APPLICATIONS.” 2018. Doctoral Dissertation, University of Akron. Accessed December 18, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=akron1533124706225894.

MLA Handbook (7th Edition):

Hoseini, Seied Zaniar, Hoseini. “MULTI-CHANNEL EEG SENSOR FRONTEND FOR PORTABLEHEALTH CONDITION MONITORING APPLICATIONS.” 2018. Web. 18 Dec 2018.

Vancouver:

Hoseini, Seied Zaniar H. MULTI-CHANNEL EEG SENSOR FRONTEND FOR PORTABLEHEALTH CONDITION MONITORING APPLICATIONS. [Internet] [Doctoral dissertation]. University of Akron; 2018. [cited 2018 Dec 18]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1533124706225894.

Council of Science Editors:

Hoseini, Seied Zaniar H. MULTI-CHANNEL EEG SENSOR FRONTEND FOR PORTABLEHEALTH CONDITION MONITORING APPLICATIONS. [Doctoral Dissertation]. University of Akron; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1533124706225894

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