Výsledky vyhledávání - "Tajadura‐Jiménez, Ana"

Akademický článek

You, me, and us: Maintaining self-other distinction enhances coordination, agency, and affect

Autor: Fairhurst, Merle T., Tajadura-Jiménez, Ana, Keller, Peter E., Deroy, Ophelia

Coordinating our actions with others changes how we behave and feel. Here, we provide evidence that interacting with others rests on a balance between self-other integration and segregation. Using a group walking paradigm, participants were instructe

Externí odkaz: https://tud.qucosa.de/id/qucosa%3A94349
https://tud.qucosa.de/api/qucosa%3A94349/attachment/ATT-0/

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STAL: Spike Threshold Adaptive Learning Encoder for Classification of Pain-Related Biosignal Data

Autor: Hens, Freek, Dehshibi, Mohammad Mahdi, Bagheriye, Leila, Shahsavari, Mahyar, Tajadura-Jiménez, Ana

This paper presents the first application of spiking neural networks (SNNs) for the classification of chronic lower back pain (CLBP) using the EmoPain dataset. Our work has two main contributions. We introduce Spike Threshold Adaptive Learning (STAL)

Externí odkaz: http://arxiv.org/abs/2407.08362

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L-SFAN: Lightweight Spatially-focused Attention Network for Pain Behavior Detection

Autor: Ortigoso-Narro, Jorge, Diaz-de-Maria, Fernando, Dehshibi, Mohammad Mahdi, Tajadura-Jiménez, Ana

Chronic Low Back Pain (CLBP) afflicts millions globally, significantly impacting individuals' well-being and imposing economic burdens on healthcare systems. While artificial intelligence (AI) and deep learning offer promising avenues for analyzing p

Externí odkaz: http://arxiv.org/abs/2406.16913

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Pain level and pain-related behaviour classification using GRU-based sparsely-connected RNNs

Autor: Dehshibi, Mohammad Mahdi, Olugbade, Temitayo, Diaz-de-Maria, Fernando, Bianchi-Berthouze, Nadia, Tajadura-Jiménez, Ana

Publikováno v: IEEE Journal of Selected Topics in Signal Processing, 17 (3), 2023, 677-688

There is a growing body of studies on applying deep learning to biometrics analysis. Certain circumstances, however, could impair the objective measures and accuracy of the proposed biometric data analysis methods. For instance, people with chronic p

Externí odkaz: http://arxiv.org/abs/2212.14806

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