Amir Aminifar

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Publications associées (37)

Breaking Silos to Guarantee Control Stability with Communication over Ethernet TSN

Amir Aminifar

Editor's notes: The cross-layer approach presented in this article involves co-designing a feedback controller's parameters together with the schedule of an Ethernet network used for communicating state information and control signals.-Samarjit Chakraborty ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Personalized Real-Time Federated Learning for Epileptic Seizure Detection

David Atienza Alonso, Amir Aminifar, Tomas Teijeiro Campo, Saleh Baghersalimi

Epilepsy is one of the most prevalent paroxystic neurological disorders. It is characterized by the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant epilepsy, thus their seizures cannot be controlled by medication. Automati ...

2021

Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors

David Atienza Alonso, Amir Aminifar, Miguel Peon Quiros, Adriana Arza Valdes, Elisabetta De Giovanni

In the recent Internet-of-Things (IoT) era where biomedical applications require continuous monitoring of relevant data, edge computing keeps gaining more and more importance. These new architectures for edge computing include multi-core and parallel compu ...

2021

EpilepsyGAN: Synthetic Epileptic Brain Activities with Privacy Preservation

David Atienza Alonso, Alireza Amirshahi, Amir Aminifar, Damián Pascual Ortiz

Epilepsy is a chronic neurological disorder affecting more than 65 million people worldwide and manifested by recurrent unprovoked seizures. The unpredictability of seizures not only degrades the quality of life of the patients, but it can also be life-thr ...

2021

Robust Epileptic Seizure Detection on Wearable Systems with Reduced False-Alarm Rate

David Atienza Alonso, Amir Aminifar, Renato Zanetti

Epilepsy affects more than 50 million people and ranks among the most common neurological diseases worldwide. Despite advances in treatment, one-third of patients still suffer from refractory epilepsy. Wearable devices for real-time patient monitoring can ...

IEEE2020

Self-Aware Machine Learning for Multimodal Workload Monitoring During Manual Labor on Edge Wearable Sensors

David Atienza Alonso, Amir Aminifar, Giulio Masinelli, Adriana Arza Valdes, Farnaz Forooghifar

The design of reliable wearable technologies for real-time and long-term monitoring presents a major challenge. Self-awareness is a promising solution that enables the system to monitor itself in interaction with the environment and to manage its resources ...

2020

Security-aware Routing and Scheduling for Control Applications on Ethernet TSN Networks

Amir Aminifar

Today, it is common knowledge in the cyber-physical systems domain that the tight interaction between the cyber and physical elements provides the possibility of substantially improving the performance of these systems that is otherwise impossible. On the ...

ASSOC COMPUTING MACHINERY2020

Noise-Resilient and Interpretable Epileptic Seizure Detection

David Atienza Alonso, Amir Aminifar, Anthony Hitchcock Thomas

Deep convolutional neural networks have recently emerged as a state-of-the art tool in detection of seizures. Such models offer the ability to extract complex nonlinear representations of an electroencephalogram (EEG) signal which can improve accuracy over ...

IEEE2020

Resource-Aware Distributed Epilepsy Monitoring Using Self-Awareness From Edge to Cloud

David Atienza Alonso, Amir Aminifar, Farnaz Forooghifar

The integration of wearable devices in humans' daily lives has grown significantly in recent years and still continues to affect different aspects of high-quality life. Thus, ensuring the reliability of the decisions becomes essential in biomedical applica ...

2019

Multi-Modal Acute Stress Recognition Using Off-the-Shelf Wearable Devices

David Atienza Alonso, Amir Aminifar, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola, Victoriano Montesinos Canovas

Monitoring stress and, in general, emotions has attracted a lot of attention over the past few decades. Stress monitoring has many applications, including high-risk missions and surgical procedures as well as mental/emotional health monitoring. In this pap ...

IEEE2019

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