José Angel Miranda Calero

Publications associées (12)

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Multi-Partner Project: Sustainable Textile Electronics (STELEC)

David Atienza Alonso, José Angel Miranda Calero, Jonathan Dan

E-textiles are rapidly emerging as an important area of electronic circuit applications. It also facilitates many socially important applications such as personalized health, elderly care, and smart agriculture. However, the environmental impact and sustai ...

IEEE2025

Solving the Cold-Start Problem for the Edge: Clustering and Adaptive Deep Learning for Emotion Detection

José Angel Miranda Calero

Designing AI-based applications personalized to each user's behavior presents significant challenges due to the cold start problem and the impracticality of extensive individual data labeling. These challenges are further compounded when deploying such app ...

IEEE2025

DeepBindi: An End-to-End Fear Detection System Optimized for Extreme-Edge Deployment

José Angel Miranda Calero

Institute of Electrical and Electronics Engineers (IEEE)2025

WEMAC: Women and Emotion Multi-modal Affective Computing dataset

José Angel Miranda Calero

WEMAC is a unique open multi-modal dataset that comprises physiological, speech, and self-reported emotional data records of 100 women, targeting Gender-based Violence detection. Emotions were elicited through visualizing a validated video set using an imm ...

2024

Personalized Clustering for Emotion Recognition Improvement

José Angel Miranda Calero

Emotion recognition through artificial intelligence and smart sensing of physical and physiological signals (affective computing) is achieving very interesting results in terms of accuracy, inference times, and user-independent models. In this sense, there ...

MDPI2024

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, José Angel Miranda Calero, Jonathan Dan

The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of el ...

2024

SAT-based Exact Modulo Scheduling Mapping for Resource-Constrained CGRAs

David Atienza Alonso, Giovanni Ansaloni, José Angel Miranda Calero, Juan Pablo Sapriza Araujo, Rubén Rodríguez Álvarez, Benoît Walter Denkinger, Ruben Rodriguez

Coarse-Grain Reconfigurable Arrays (CGRAs) represent emerging low-power architectures designed to accelerate Compute-Intensive Loops (CILs). The effectiveness of CGRAs in providing acceleration relies on the quality of mapping: how efficiently the CIL is c ...

2024

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

David Atienza Alonso, Giovanni Ansaloni, José Angel Miranda Calero, Jonathan Dan, Amirhossein Shahbazinia, Flavio Ponzina

Epilepsy, a major neurological disease, requires careful diagnosis and treatment. However, the detection of epileptic seizures remains a significant challenge. Current clinical practice relies on expert analysis of EEG signals, a process that is time-consu ...

IEEE2024

Personalised and Adjustable Interval Type-2 Fuzzy-Based PPG Quality Assessment for the Edge

José Angel Miranda Calero

Most of today's wearable technology provides seamless cardiac activity monitoring. Specifically, the vast majority employ Photoplethysmography (PPG) sensors to acquire blood volume pulse information, which is further analysed to extract useful and physiolo ...

New York2023

An Open-Hardware Coarse-Grained Reconfigurable Array for Edge Computing

David Atienza Alonso, Giovanni Ansaloni, José Angel Miranda Calero, Juan Pablo Sapriza Araujo, Rubén Rodríguez Álvarez, Benoît Walter Denkinger, Ruben Rodriguez

In this work, we propose an open-hardware low-power coarse-grained reconfigurable array connected to a lightweight microcontroller and enclosed in an application mapping framework. The latter provides complete support to configure kernels in the reconfigur ...

2023

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