نتائج البحث - "Benoit Larras"

1

دورية أكاديمية

ECG Classification With Event-Driven Sampling

المؤلفون: Maryam Saeed, Olev Martens, Benoit Larras, Antoine Frappe, Deepu John, Barry Cardiff

المصدر: IEEE Access, Vol 12, Pp 25188-25199 (2024)

مصطلحات موضوعية: Level-crossing ADC, electrocardiograms, functional approximation, Chebyshev polynomials, artificial neural networks, arrhythmia, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/10427994/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/77708a6d4f094f3e981ee1090e21b212

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دورية أكاديمية

Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications

المؤلفون: Margus Metshein, Anar Abdullayev, Antoine Gautier, Benoit Larras, Antoine Frappe, Barry Cardiff, Paul Annus, Raul Land, Olev Märtens

المصدر: Sensors, Vol 23, Iss 16, p 7111 (2023)

مصطلحات موضوعية: cardiovascular system, convolutional neural networks, electrical bioimpedance, deep learning, photoplethysmography, non-invasive measurements, Chemical technology, TP1-1185

وصف الملف: electronic resource

Relation: https://www.mdpi.com/1424-8220/23/16/7111; https://doaj.org/toc/1424-8220

URL الوصول: https://doaj.org/article/3bec0d8f2fa14e438e0309814fe2d829

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Complexity Reduction of CNNs using Multi-Scale Group Convolution for IoT Edge Sensors

المؤلفون: Qingyuan Wang, Antoine Frappe, Benoit Larras, Barry Cardiff, Deepu John

المساهمون: University College Dublin [Dublin] (UCD), Microélectronique Silicium - IEMN (MICROELEC SI - IEMN), Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), This publication has emanated from research supported in part by 1) a grant from Science Foundation Ireland under Grant number 18/CRT/6183 and 2) CHIST-ERA grant JEDAI CHIST-ERA-18-ACAI-003., ANR-19-CHR3-0005,JEDAI,Event Driven Artificial Intelligence Hardware for Biomedical Sensors(2019)

المصدر: 2022 29th IEEE International Conference on Electronics, Circuits and Systems (ICECS)
2022 29th IEEE International Conference on Electronics, Circuits and Systems (ICECS), Oct 2022, Glasgow, United Kingdom. pp.1-4, ⟨10.1109/ICECS202256217.2022.9970790⟩

مصطلحات موضوعية: [PHYS]Physics [physics]

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0dfe655d304ae574ac68024dfdc3ec67
https://doi.org/10.1109/icecs202256217.2022.9970790

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Event-Driven ECG Classification using Functional Approximation and Chebyshev Polynomials

المؤلفون: Maryam Saeed, Olev Martens, Benoit Larras, Antoine Frappe, Deepu John, Barry Cardiff

المساهمون: University College Dublin [Dublin] (UCD), Tallinn University of Technology (TTÜ), Microélectronique Silicium - IEMN (MICROELEC SI - IEMN), Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), This work is supported by 1) JEDAI project under the Chist-Era Program, 2) Schlumberger Foundation’s Faculty for the Future Program 3) Irish ResearchCouncil under the New Foundations Scheme and 4) Microelectronic Circuit Centre Ireland., ANR-19-CHR3-0005,JEDAI,Event Driven Artificial Intelligence Hardware for Biomedical Sensors(2019)

المصدر: 2022 IEEE Biomedical Circuits and Systems Conference, BioCAS
2022 IEEE Biomedical Circuits and Systems Conference, BioCAS, Oct 2022, Taipei, Taiwan. pp.595-599, ⟨10.1109/biocas54905.2022.9948612⟩

مصطلحات موضوعية: event-driven, [SPI]Engineering Sciences [physics], level-crossing ADC, chebyshev polynomials, electrocardiograms, functional approximation, arrhythmia, artificial neural networks

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f4b822ee445846de44c1234f6fa8eb2
https://doi.org/10.1109/biocas54905.2022.9948612

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Antidictionary-Based Cardiac Arrhythmia Classification for Smart ECG Sensors

المؤلفون: Julien Duforest, Benoit Larras, Antoine Frappe, Chacko John Deepu, Olev Martens

المساهمون: Microélectronique Silicium - IEMN (MICROELEC SI - IEMN), Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), JUNIA (JUNIA), Université catholique de Lille (UCL), University College Dublin [Dublin] (UCD), Tallinn University of Technology (TTÜ), ANR jedai (information auteur), Laboratoire commun STMicroelectronics-IEMN T2, ANR-19-CHR3-0005,JEDAI,Event Driven Artificial Intelligence Hardware for Biomedical Sensors(2019)

المصدر: 2022 IEEE International Symposium on Circuits and Systems (ISCAS)
2022 IEEE International Symposium on Circuits and Systems (ISCAS), May 2022, Austin, TX, United States. pp.414-418, ⟨10.1109/ISCAS48785.2022.9937853⟩

مصطلحات موضوعية: Antidictionary, [SPI]Engineering Sciences [physics], ComputingMethodologies_PATTERNRECOGNITION, cardiovascular system, Event-driven, Cardiac Arrhythmia Classification, Electrocardiogram

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82ffd4794adcbcdfa9b1ddc869c4023e
https://hal.science/hal-03701059

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Keyword Spotting System using Low-complexity Feature Extraction and Quantized LSTM

المؤلفون: Kevin Herisse, Benoit Larras, Antoine Frappe, Andreas Kaiser

المساهمون: Microélectronique Silicium - IEMN (MICROELEC SI - IEMN), Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), ANR leopard, Laboratoire commun STMicroelectronics-IEMN T2, ANR-18-CE24-0006,LEOPAR,Unité de pré-traitement pour systèmes intégrés à faible énergie(2018)

المصدر: 28th IEEE International Conference on Electronics Circuits and Systems, ICECS 2021
28th IEEE International Conference on Electronics Circuits and Systems, ICECS 2021, Nov 2021, Dubai, United Arab Emirates. ⟨10.1109/ICECS53924.2021.9665486⟩

مصطلحات موضوعية: Machine Learning, [SPI]Engineering Sciences [physics], ComputingMethodologies_PATTERNRECOGNITION, MFCC, Long Short-Term Memory, Keyword Spotting

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6d1fc1e5e910d7907f80c28cf55dd3c3
https://hal.science/hal-03515704

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Study of Electrode Locations for Joint Acquisition of Impedance- and Electro-cardiography Signals

المؤلفون: Margus Metshein, Antoine Gautier, Benoit Larras, Antoine Frappe, Deepu John, Barry Cardiff, Paul Annus, Raul Land, Olev Martens

المساهمون: Tallinn University of Technology (TTÜ), Microélectronique Silicium - IEMN (MICROELEC SI - IEMN), Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), University College Dublin [Dublin] (UCD), Université catholique de Lille (UCL)-Université catholique de Lille (UCL)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), This work was supported by EU Regional Development Fund (Estonian Centre of Excellence in ICT Research EXCITE TAR16013 and Mobilitas+ project Mobera20), CHIST-ERA grant JEDAI CHIST-ERA-18-ACAI-003, Irish Research Council and French Researh Agency project ANR-19-CHR3-0005-01., Laboratoire commun STMicroelectronics-IEMN T2, ANR-19-CHR3-0005,JEDAI,Event Driven Artificial Intelligence Hardware for Biomedical Sensors(2019)

المصدر: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Nov 2021, Mexico, Mexico. ⟨10.1109/EMBC46164.2021.9629504⟩

مصطلحات موضوعية: Volume measurement, Sensors, 0206 medical engineering, Stroke Volume, 02 engineering and technology, Time measurement, Thorax, Cardiography, Impedance, 020601 biomedical engineering, Electrocardiography, [SPI]Engineering Sciences [physics], Electric Impedance, Wearable computers, Cardiac Output, Electrodes, ComputingMilieux_MISCELLANEOUS

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::561fe74a32ec302e6b6938c95e4a4885
https://hal.archives-ouvertes.fr/hal-03482302/file/EMBC_Margus_CameraReady.pdf

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Slope-Based Event-Driven Feature Extraction For Cardiac Arrhythmia Classification

المؤلفون: Julien Duforest, Benoit Larras, Deepu John, Olev Martens, Antoine Frappe

المساهمون: Microélectronique Silicium - IEMN (MICROELEC SI - IEMN), Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), JUNIA (JUNIA), Université catholique de Lille (UCL), University College Dublin [Dublin] (UCD), Tallinn University of Technology (TTÜ), This work was supported by the EU Regional Development Fund (Estonian Centre of Excellence in ICT Research EXCITE TAR16013), the CHIST-ERA grant JEDAI, Mobilitas+ project Mobera20, Irish Research Council, and French Research Agency project ANR-19-CHR3-0005-01., Laboratoire commun STMicroelectronics-IEMN T2, ANR-19-CHR3-0005,JEDAI,Event Driven Artificial Intelligence Hardware for Biomedical Sensors(2019)

المصدر: 2021 IEEE Biomedical Circuits and Systems Conference (BioCAS)
2021 IEEE Biomedical Circuits and Systems Conference (BioCAS), Oct 2021, Berlin, Germany. pp.01-04, ⟨10.1109/BioCAS49922.2021.9644957⟩

مصطلحات موضوعية: Artificial neural network (ANN), event-driven, [SPI]Engineering Sciences [physics], ComputingMethodologies_PATTERNRECOGNITION, time-to-digital converter (TDC), level-crossing ADC, cardiac arrhythmia classification (CAC), ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMS, cardiovascular diseases, electrocardiogram (ECG)

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::59e88cd27bd11bc1b16b4ad499ab7232
https://doi.org/10.1109/biocas49922.2021.9644957

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Embedded ICG-based Stroke Volume Measurement System: Comparison of Discrete-Time and Continuous-Time Architectures

المؤلفون: Antoine Gautier, Benoit Larras, Olev Martens, Deepu John, Antoine Frappe

المساهمون: Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), University College Dublin [Dublin] (UCD), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), Microélectronique Silicium - IEMN (MICROELEC SI - IEMN), Université catholique de Lille (UCL)-Université catholique de Lille (UCL)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Tallinn University of Technology (TTÜ), Current work has been supported by CHIST-ERA grant JEDAI, Irish Research Council and French Research Agency project ANR-19-CHR3-0005-01 and EU Regional Development Fund (Estonian Centre of Excellence in ICT Research EXCITE TAR16013 and Mobilitas+ project Mobera20), Laboratoire commun STMicroelectronics-IEMN T2, ANR-19-CHR3-0005,JEDAI,Event Driven Artificial Intelligence Hardware for Biomedical Sensors(2019)

المصدر: 34th IEEE International System-On-Chip Conference
34th IEEE International System-On-Chip Conference, Sep 2021, Las Vegas, NV, United States
34th IEEE International System-On-Chip Conference, Socc 2021
34th IEEE International System-On-Chip Conference, Socc 2021, Sep 2021, Las Vegas, NV, United States. ⟨10.1109/SOCC52499.2021.9739386⟩

مصطلحات موضوعية: ICG, [SPI]Engineering Sciences [physics], Stroke Volume, biosignal monitoring, wearable

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f100e984336b3b1e9edad3638340f3ef
https://hal.archives-ouvertes.fr/hal-03482323

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A 43pJ per Inference CBNN-based Compute-in-sensor Associative Memory in 28nm FDSOI

المؤلفون: Antoine Frappe, Benoit Larras

المساهمون: Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Microélectronique Silicium - IEMN (MICROELEC SI - IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), Université catholique de Lille (UCL)-Université catholique de Lille (UCL)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), This work was supported in part by the French National Research Agency under Grant ANR-18-CE24-0006-01 LEOPAR. The authors would like to thank Andreia Cathelin and STMicroelectronics for access to the technology., Laboratoire commun STMicroelectronics-IEMN T2, ANR-18-CE24-0006,LEOPAR,Unité de pré-traitement pour systèmes intégrés à faible énergie(2018)

المصدر: ESSCIRC
ESSCIRC 2021-IEEE 47th European Solid State Circuits Conference (ESSCIRC)
ESSCIRC 2021-IEEE 47th European Solid State Circuits Conference (ESSCIRC), Sep 2021, Grenoble, France. pp.111-114, ⟨10.1109/ESSCIRC53450.2021.9567808⟩

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::add8bdaf4493af4d870c92946da2c67d
https://doi.org/10.1109/esscirc53450.2021.9567808

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