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Tomas Teijeiro

tomas.teijeiro@epfl.ch

EPFL › STI › IEM › ESL

Website: https://esl.epfl.ch

I received my PhD from the Centro Singular de Investigación en Tecnoloxías Intelixentes (CITIUS), University of Santiago de Compostela, Spain, in 2017. During my doctoral studies I developed a novel knowledge-based framework for time series interpretation based on abductive reasoning that has been successfully applied to automatic ECG interpretation and classification. Now I am currently working as a research associate at the Embedded Systems Laboratory (ESL), with Prof. David Atienza. My research interests include knowledge representation, non-monotonic temporal reasoning, event-based sensing, and their application to biosignal abstraction and interpretation in energy-efficient setups.

Selected publications

Abductive reasoning as the basis to reproduce expert criteria in ECG Atrial Fibrillation identification

T. Teijeiro, C.A. García, D. Castro, and P. Félix
Published in Physiological Measurement in

On the adoption of abductive reasoning for time series interpretation

T. Teijeiro and P. Félix
Published in Artificial Intelligence in

Heartbeat classification using abstract features from the abductive interpretation of the ECG

T. Teijeiro, P. Félix, J. Presedo, and D. Castro
Published in IEEE Journal of Biomedical and Health Informatics in

M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems

S. Baghersalimi; A. Amirshahi; F. Forooghifar; T. Teijeiro; AMIR AMINIFAR  et al.

ACM Transactions on Intelligent Systems and Technology. 2024-05-29.

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Acoustical Features as Knee Health Biomarkers: A Critical Analysis

C. Kechris; J. P. R. Thevenot; T. Teijeiro; V. Stadelmann; N. Maffiuletti  et al.

2024-05-23.

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Combining general and personal models for epilepsy detection with hyperdimensional computing

U. Pale; T. Teijeiro; S. Rheims; P. Ryvlin; D. Atienza

Artificial Intelligence In Medicine. 2024-01-09. DOI : 10.1016/j.artmed.2023.102754.

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Decentralized Federated Learning for Epileptic Seizures Detection in Low-Power Wearable Systems

S. Baghersalimi; T. Teijeiro; A. Aminifar; D. Atienza Alonso

IEEE Transactions on Mobile Computing. 2023. DOI : 10.1109/TMC.2023.3320862.

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Event-based sampled ECG morphology reconstruction through self-similarity

S. Zanoli; G. Ansaloni; T. Teijeiro; D. Atienza

Computer Methods And Programs In Biomedicine. 2023-10-01. DOI : 10.1016/j.cmpb.2023.107712.

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Layer-Wise Learning Framework for Efficient DNN Deployment in Biomedical Wearable Systems

S. Baghersalimi; A. Amirshahi; T. Teijeiro; A. Aminifar; D. Atienza Alonso

2023-10-09. IEEE-EMBS International Conference on Body Sensor Networks: Sensors and Systems for Digital Health (IEEE BSN) 2023, Cambridge, MA, US, October 9-11, 2023. DOI : 10.1109/BSN58485.2023.10331334.

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A semi-supervised algorithm for improving the consistency of crowdsourced datasets: The COVID-19 case study on respiratory disorder classification

L. Orlandic; T. Teijeiro; D. Atienza

Computer Methods and Programs in Biomedicine. 2023. DOI : 10.1016/j.cmpb.2023.107743.

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A Multimodal Dataset for Automatic Edge-AI Cough Detection

L. Orlandic; J. P. R. Thevenot; T. Teijeiro; D. Atienza Alonso

2023-07-24. 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Sydney Australia, July 24-27, 2023. DOI : 10.1109/EMBC40787.2023.10340413.

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An Error-Based Approximation Sensing Circuit for Event-Triggered Low-Power Wearable Sensors

S. Zanoli; F. Ponzina; T. Teijeiro; A. S. J. Levisse; D. Atienza Alonso

IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 2023. DOI : 10.1109/JETCAS.2023.3269623.

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Importance of methodological choices in data manipulation for validating epileptic seizure detection models

U. Pale; T. Teijeiro; D. Atienza Alonso

2023. 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Sydney, Australia, July 24-27, 2023. DOI : 10.1109/EMBC40787.2023.10340493.

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ExG Signal Feature Selection Using Hyperdimensional Computing Encoding

U. Pale; T. Teijeiro; D. Atienza

2022-12-08. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Las Vegas, NV, USA, 06-08 December 2022. p. 1688-1693. DOI : 10.1109/BIBM55620.2022.9995107.

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HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration

W. A. Simon; U. Pale; T. Teijeiro; D. Atienza

2022-06-09. ICCAD 2022 - 41st IEEE/ACM International Conference on Computer-Aided Design, San Diego, USA, 30 October 2022- 3 November 2022. p. 1-8. DOI : 10.1145/3508352.3549475.

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Adaptive R-Peak Detection on Wearable ECG Sensors for High-Intensity Exercise

E. De Giovanni; T. Teijeiro; G. P. Millet; D. Atienza Alonso

IEEE Transactions on Biomedical Engineering. 2022-09-09. DOI : 10.1109/TBME.2022.3205304.

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Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure Detection

U. Pale; T. Teijeiro; D. Atienza

Frontiers in Neurology. 2022-03-31. DOI : 10.3389/fneur.2022.816294.

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Exploration of Hyperdimensional Computing Strategies for Enhanced Learning on Epileptic Seizure Detection

U. Pale; T. Teijeiro; D. Atienza Alonso

2022. 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC 2022), Glasgow, Scotland, July 11-15, 2022. p. 4076-4082. DOI : 10.1109/EMBC48229.2022.9870919.

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Personalized seizure signature: An interpretable approach to false alarm reduction for long‐term epileptic seizure detection

D. Sopic; T. Teijeiro; D. Atienza; A. Aminifar; P. Ryvlin

Epilepsia. 2022-02-03. DOI : 10.1111/epi.17176.

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INCLASS: Incremental Classification Strategy for Self-Aware Epileptic Seizure Detection

L. Ferretti; G. Ansaloni; R. Marquis; T. Teijeiro; P. Ryvlin  et al.

2022-03-23. Design Automation and Test in Europe Conference (DATE2022), Grenoble, France, March 16-23, 2022. p. 1449-1454. DOI : 10.23919/DATE54114.2022.9774713.

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Systematic Assessment of Hyperdimensional Computing for Epileptic Seizure Detection

U. Pale; T. Teijeiro; D. Atienza Alonso

2021. 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, Virtual, October 31 – November 4, 2021. DOI : 10.1109/EMBC46164.2021.9629648.

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Personalized Real-Time Federated Learning for Epileptic Seizure Detection

S. Baghersalimi; T. Teijeiro; D. Atienza; A. Aminifar

IEEE Journal of Biomedical and Health Informatics. 2021-07-09. DOI : 10.1109/JBHI.2021.3096127.

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The COUGHVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms

L. Orlandic; T. Teijeiro; D. Atienza Alonso

Scientific Data. 2021-06-23. DOI : 10.1038/s41597-021-00937-4.

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Interpreting deep learning models for epileptic seizure detection on EEG signals

V. Gabeff; T. Teijeiro; M. Zapater; L. Cammoun; S. Rheims  et al.

Artificial Intelligence in Medicine. 2021-05-01. DOI : 10.1016/j.artmed.2021.102084.

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Self-Aware Anomaly-Detection for Epilepsy Monitoring on Low-Power Wearable Electrocardiographic Devices

F. Forooghifar; A. Aminifar; T. Teijeiro; A. Aminifar; J. Jeppesen  et al.

2021-04-12. 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, Online, May 3-7, 2021. DOI : 10.1109/AICAS51828.2021.9458555.

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Knowledge, Machine Learning and Atrial Fibrillation: More Ingredients for a Tastier Cocktail

T. Teijeiro

2020. 2020 Computing in Cardiology Conference (CinC), Rimini, Italy, September 13th-16th, 2020. DOI : 10.22489/CinC.2020.476.

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An Event-Based System for Low-Power ECG QRS Complex Detection

S. Zanoli; T. Teijeiro; F. Montagna; D. Atienza Alonso

2020. DATE 2020 - Design, Automation & Test In Europe Conference & Exhibition, Grenoble, France, March 9-13, 2020. p. 258-263. DOI : 10.23919/DATE48585.2020.9116498.

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Event-Triggered Sensing for High-Quality and Low-Power Cardiovascular Monitoring Systems

G. Surrel; T. Teijeiro; M. Chevrier; A. Aminifar; D. Atienza Alonso

IEEE Design & Test. 2019-11-04. DOI : 10.1109/MDAT.2019.2951126.

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Teaching & PhD

PhD Students

Wensi Zhang

Past EPFL PhD Students as codirector

Silvio Zanoli