A Low-Power Oscillatory Feature Extraction Unit for Implantable Neural Interfaces

Conference Paper (2023)
Authors

H. Yassin (TU Delft - Bio-Electronics, Aswan University)

A. Akhoundi (TU Delft - Bio-Electronics)

El Sayed Hasaneen (Aswan University)

Dante G Muratore (TU Delft - Bio-Electronics)

Research Group
Bio-Electronics
Copyright
© 2023 H. Yassin, A. Akhoundi, El Sayed Hasaneen, D.G. Muratore
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Publication Year
2023
Language
English
Copyright
© 2023 H. Yassin, A. Akhoundi, El Sayed Hasaneen, D.G. Muratore
Research Group
Bio-Electronics
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. @en
ISBN (electronic)
9781665451093
DOI:
https://doi.org/10.1109/ISCAS46773.2023.10181914
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Abstract

Power and area efficient on-chip feature extraction is needed for future closed-loop neural interfaces. This paper presents a feature extraction unit for neural oscillatory synchrony that bypasses the phase extraction step to reduce hardware complexity. Instead, the sine and cosine of the phase are directly approximated from the real and imaginary components of the signal to calculate the phase-amplitude coupling (PAC) and phase locking value (PLV). The synthesized design achieves state-of-the-art performances at 43 nW/channel and 0.006 mm2, while maintaining sufficient accuracy for seizure detection in epileptic patients.

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