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A multi-channel EEG system featuring single-wire data aggregation via FM-FDM techniques | IEEE Conference Publication | IEEE Xplore

A multi-channel EEG system featuring single-wire data aggregation via FM-FDM techniques


Abstract:

Conventional EEG systems are extremely power hungry due to a reliance on high resolution analog-to-digital converters (ADCs) to cover their required dynamic range. This p...Show More

Abstract:

Conventional EEG systems are extremely power hungry due to a reliance on high resolution analog-to-digital converters (ADCs) to cover their required dynamic range. This paper presents a novel architecture for acquiring multi-channel high-resolution EEG using low power techniques. Instead of digitizing the output of each analog front-end (AFE) amplifier with an individual ADC, a voltage-controlled oscillator is used to generate an up-converted frequency-modulated (FM) signal at a unique carrier frequency. All channels then share a single wire via frequency-domain multiplexing (FDM), enabling a rugged mechanical design. The composite FM signal is then digitized with a single ADC optimized for time-domain resolution (1 MHz, 12 bits) rather than employing multiple ADCs optimized for voltage-domain resolution (1 kHz, 16–24 bits), thereby enabling a low-power implementation. To validate this approach, a discrete prototype is developed and achieves 75 dB of dynamic range per channel.
Date of Conference: 22-25 May 2016
Date Added to IEEE Xplore: 11 August 2016
ISBN Information:
Electronic ISSN: 2379-447X
Conference Location: Montreal, QC, Canada
Citations are not available for this document.

I. Introduction

Electroencephalogram (EEG) monitoring has wide range of applications — from the diagnosis and treatment of a number of brain-related diseases and disorders to brain-computer interactive technologies for every-day application. Ideally, patients suffering from a number of neurological conditions such as epilepsy, post-traumatic brain injury, Alzheimer's disease, and more would benefit from continuous, noninvasive, and high-resolution measurement of EEG during activities of daily living (ADL) [1]. Interactive systems that maximize the flexibility of the human brain with the efficiency of computer technology such as search target recognition, drowsiness detection, and human-robot interaction will require minimal intrusion upon and maintenance from the user [2], [3].

Traditional multi-channel EEG acquisition approach

Cites in Papers - |

Cites in Papers - IEEE (3)

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1.
Julian Warchall, Paul Theilmann, Yuxuan Ouyang, Harinath Garudadri, Patrick P. Mercier, "Robust Biopotential Acquisition via a Distributed Multi-Channel FM-ADC", IEEE Transactions on Biomedical Circuits and Systems, vol.13, no.6, pp.1229-1242, 2019.
2.
Julian Warchall, Paul Theilmann, Yuxuan Ouyang, Harinath Garudadri, Patrick P. Mercier, "22.2 A Rugged Wearable Modular ExG Platform Employing a Distributed Scalable Multi-Channel FM-ADC Achieving 101dB Input Dynamic Range and Motion-Artifact Resilience", 2019 IEEE International Solid- State Circuits Conference - (ISSCC), pp.362-364, 2019.
3.
Julian Warchall, Shiva Kaleru, Nidhi Jayapalan, Bijoor Nayak, Harinath Garudadri, Patrick P. Mercier, "A 678- \mu W Frequency-Modulation-Based ADC With 104-dB Dynamic Range in 44-kHz Bandwidth", IEEE Transactions on Circuits and Systems II: Express Briefs, vol.65, no.10, pp.1370-1374, 2018.

Cites in Papers - Other Publishers (1)

1.
Andrew Melnik, Petr Legkov, Krzysztof Izdebski, Silke M. Kärcher, W. David Hairston, Daniel P. Ferris, Peter König, "Systems, Subjects, Sessions: To What Extent Do These Factors Influence EEG Data?", Frontiers in Human Neuroscience, vol.11, 2017.
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References

References is not available for this document.