IEEE Solid-States Circuits Magazine - Fall 2023 - 49

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sub-μW/channel consumption and closedloop
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channel consumption for epileptic iEEG
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detection of Parkinsonian resting
tremor with feature engineering and Kalman
filtering, " Clin. Neurophysiol., vol.
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[26] B. Zhu, G. Coppola, and M. Shoaran, " Migraine
classification
using somatosensory
evoked potentials, " Cephalalgia, vol.
39, no. 9, pp. 1143-1155, Aug. 2019, doi:
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[27] L. Yao, J. L. Baker, N. D. Schiff, K. P. Purpura,
and M. Shoaran, " Predicting task
performance from biomarkers of mental
fatigue in global brain activity, " J. Neural
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036001, doi: 10.1088/1741-2552/abc529.
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tremor detection in Parkinson's disease
with machine learning and Kalman filtering, "
in Proc. IEEE Biomed. Circuits Syst.
Conf. (BioCAS), Oct. 2018, pp. 1-4, doi:
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[29] J. Yoo, L. Yan, D. El-Damak, M. A. B. Altaf,
A. H. Shoeb, and A. P. Chandrakasan,
" An 8-channel scalable EEG acquisition
SoC with patient-specific seizure classification
and recording processor, "
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pp. 214-228, Jan. 2013, doi: 10.1109/JSSC.
2012.2221220.
[30] M. Shoaran, B. A. Haghi, M. Taghavi, M.
Farivar, and A. Emami-Neyestanak, " Energy-efficient
classification for resourceconstrained
biomedical applications, "
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N. Verma, and R. Genov, " NURIP: Neural
interface processor for brain-state classification
and programmable-waveform
neurostimulation, " IEEE J. Solid-State Circuits,
vol. 53, no. 11, pp. 3150-3162, Nov.
2018, doi: 10.1109/JSSC.2018.2869579.
[32] A. Chua, M. I. Jordan, and R. Muller,
" SOUL: An energy-efficient unsupervised
online learning seizure detection classifier, "
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J. M. Henderson, and K. V. Shenoy,
" High-performance brain-to-text communication
via handwriting, " Nature, vol.
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10.1038/s41586-021-03506-2.
[34] L. Yao, B. Zhu, and M. Shoaran, " Fast and
accurate decoding of finger movements
from ECoG through Riemannian features
and modern machine learning techniques, "
J Neural Eng., vol. 19, no. 1, Feb.
2022, Art. no. 016037, doi: 10.1088/17412552/ac4ed1.
[35]
B. Zhu, M. Farivar, and M. Shoaran, " ResOT:
Resource-efficient oblique trees for neural
signal classification, " IEEE Trans.
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704, Aug. 2020, doi: 10.1109/TBCAS.2020.
3004544.
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8-channel, patient-specific epileptic
seizure classification SoC using a
non-linear support vector machine, " IEEE
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versatile brain activity classification and
closed-loop neuromodulation SoC with
0.004 mm2-1.51 µW/channel fast-settling
highly multiplexed mixed-signal
[40] M. Shoaran, M. H. Kamal, C. Pollo, P. Vandergheynst,
and A. Schmid, " Compact
low-power cortical
recording architecture
for compressive multichannel data
acquisition, " IEEE Trans. Biomed. Circuits
Syst., vol. 8, no. 6, pp. 857-870, Dec. 2014,
doi: 10.1109/TBCAS.2014.2304582.
[41] B. Zhu, M. Taghavi, and M. Shoaran, " Costefficient
classification for neurological
disease detection, " in Proc. IEEE Biomed.
Circuits Syst. Conf. (BioCAS), Oct. 2019, pp.
1-4, doi: 10.1109/BIOCAS.2019.8918702.
[42] U. Shin, C. Ding, V. Woods, A. S. Widge,
and M. Shoaran, " A 16-channel low-power
neural connectivity extraction and phaselocked
deep brain stimulation SoC, " IEEE
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Jan. 2023, doi: 10.1109/LSSC.2023.3238797.
[43] U. Shin, C. Ding, L. Somappa, V. Woods,
A. S. Widge, and M. Shoaran, " A 16-channel
60 µW neural synchrony processor for
multi-mode phase-locked neurostimulation, "
in Proc. IEEE Custom Integr. Circuits
Conf. (CICC), Apr. 2022, pp. 1-2, doi:
10.1109/CICC53496.2022.9772806.
[44] M. Sharifshazileh, K. Burelo, J. Sarnthein,
and G. Indiveri, " An electronic neuromorphic
system for real-time detection of high frequency
oscillations (HFO)
in
intracranial
EEG, " Nature Commun., vol. 12, no. 1, May
2021, Art. no. 3095, doi: 10.1038/s41467-02123342-2.
[45]
M. Ronchini, Y. Rezaeiyan, M. Zamani,
G. Panuccio, and F. Moradi, " NET-TEN: A
silicon neuromorphic network for lowlatency
detection of seizures in local field
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Jun. 2023, Art. no. 036002, doi: 10.1088/
1741-2552/acd029.
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Farkhani, and F. Moradi, " In the realm of
hybrid Brain: Human brain and AI, " Oct.
2022, arXiv:2210.01461.
[47] C. Fang, C. Wang, S. Zhao, F. Tian, J. Yang,
and M. Sawan,
" A 510 μW 0.738-mm2
6.2-pJ/SOP online learning multi-topology
SNN processor with unified computation
engine in 40-nm CMOS, " IEEE Trans.
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[48] J. Yoo and M. Shoaran, " Neural interface
systems with on-device computing: Machine
learning and neuromorphic architectures, "
Current Opinion Biotechnol., vol.
72, pp. 95-101, Dec. 2021, doi: 10.1016/
j.copbio.2021.10.012.
frontend, "
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Conf. (ISSCC), Feb. 2022, pp. 338-340, doi:
10.1109/ISSCC42614.2022.9731776.
[38] U. Shin et al., " NeuralTree: A 256-channel
0.227-μJ/class versatile neural activity
classification and closed-loop neuromodulation
SoC, " IEEE J. Solid-State Circuits,
vol. 57, no. 11, pp. 3243-3257, Nov. 2022,
doi: 10.1109/JSSC.2022.3204508.
[39] J. D. Simeral et al., " Home use of a percutaneous
wireless intracortical braincomputer
interface by individuals with
tetraplegia, " IEEE Trans. Biomed. Eng., vol.
68, no. 7, pp. 2313-2325, Jul. 2021, doi:
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About the Author
Mahsa Shoaran (mahsa.shoaran@
epfl.ch) is an assistant professor in
electrical engineering and Neuro-X
and director of the Integrated Neurotechnologies
Laboratory at the Swiss
Federal Institute of Technology Lausanne,
1015 Lausanne, Switzerland.
She is a Senior Member of IEEE.
IEEE SOLID-STATE CIRCUITS MAGAZINE
FALL 2023
49
IEEE Solid-States Circuits Magazine - Fall 2023

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