Publications by Jonathan Dan | EPFL Graph Search

Deep learning–based detection of generalized convulsive seizures using a wrist‐worn accelerometer

David Atienza Alonso, Antoine Jérôme Spahr, Jonathan Dan

Objective To develop and validate a wrist‐worn accelerometer‐based, deep‐learning tunable algorithm for the automated detection of generalized or bilateral convulsive seizures (CSs) to be integrated with off‐the‐shelf smartwatches. Methods We conducted a ...

Wiley2025

Cough-E: A multimodal, privacy-preserving cough detection algorithm for the edge

David Atienza Alonso, Lara Orlandic, Tomas Teijeiro Campo, Jérôme Paul Rémy Thevenot, Stefano Albini, Jonathan Dan

Continuous cough monitors can greatly benefit doctors in home monitoring and treatment of respiratory diseases. Although many works propose algorithms to automate this task, they suffer of poor data privacy and short-term monitoring. Edge-AI is a promising ...

2025

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

Longitudinal high-density cortical auditory event-related potentials and speech-sound discrimination in the first two years of life in extremely and very preterm infants without developmental disorders

Jonathan Dan

Maturation of the auditory system in early childhood significantly influences the development of language-related perceptual and cognitive abilities. This study aims to provide insights into the neurophysiological changes underlying auditory processing and ...

2025

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

How to Count Coughs: An Event-Based Framework for Evaluating Automatic Cough Detection Algorithm Performance

David Atienza Alonso, Lara Orlandic, Tomas Teijeiro Campo, Jérôme Paul Rémy Thevenot, Jonathan Dan

Chronic cough disorders are widespread and challenging to assess because they rely on subjective patient questionnaires about cough frequency. Wearable devices running Machine Learning (ML) algorithms are promising for quantifying daily coughs, providing c ...

IEEE2024

SzCORE: Seizure Community Open-Source Research Evaluation framework for the validation of electroencephalography-based automated seizure detection algorithms

David Atienza Alonso, William Cappelletti, Una Pale, Alireza Amirshahi, Jonathan Dan

The need for high-quality automated seizure detection algorithms based on electroencephalography (EEG) becomes ever more pressing with the increasing use of ambulatory and long-term EEG monitoring. Heterogeneity in validation methods of these algorithms in ...

2024

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

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

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

Ambulatory seizure detection

Adriano Bernini, Jonathan Dan

Purpose of review: To review recent advances in the field of seizure detection in ambulatory patients with epilepsy. Recent findings: Recent studies have shown that wrist or arm wearable sensors, using 3D-accelerometry, electrodermal activity or photopleth ...

2024