Publications by Sareh Saeedi | EPFL Graph Search

Decoding Neural Correlates of Cognitive States to Enhance Driving Experience

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Marija Uscumlic, Zahra Khaliliardali, Sareh Saeedi, Lucian Andrei Gheorghe, Huaijian Zhang, Ruslan Aydarkhanov

Modern cars can support their drivers by assessing and autonomously performing different driving maneuvers based on information gathered by in-car sensors. We propose that brain–machine interfaces (BMIs) can provide complementary information that can ease ...

2018

The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users

José del Rocio Millán Ruiz, Luca Tonin, Serafeim Perdikis, Sareh Saeedi, Christoph Schneider

This work aims at corroborating the importance and efficacy of mutual learning in motor imagery (MI) brain–computer interface (BCI) by leveraging the insights obtained through our participation in the BCI race of the Cybathlon event. We hypothesized that, ...

2018

Long-Term Stable Control of Motor-Imagery BCI by a Locked-in User Through Adaptive Assistance

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Sareh Saeedi

Performance variation is one of the main challenges that BCIs are confronted with, when being used over extended periods of time. Shared control techniques could partially cope with such a problem. In this paper, we propose a taxonomy of shared control app ...

Institute of Electrical and Electronics Engineers2017

Adaptive Assistance for Brain-Computer Interfaces by Online Prediction of Command Reliability

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Robert Leeb, Sareh Saeedi

One of the challenges of using brain-computer interfaces (BCIs) over extended periods of time is the variation of the users' performance across different experimental days. The goal of the current study is to propose a performance estimator for an electroe ...

Institute of Electrical and Electronics Engineers2016

Adaptive assistance for BCI: a locked-in syndrome end-user case study

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Robert Leeb, Sareh Saeedi

2016

Reliability and Adaptive Assistance in Brain-Computer Interfaces

Sareh Saeedi

Brain-computer interfaces (BCIs) aim at offering an interaction modality for people with severe motor disabilities. Despite promising advances, BCIs are still confronted with multiple challenges in determining user's intentions reliably, mainly due to high ...

EPFL2016

Prediction of Command Delivery Time for BCI

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Sareh Saeedi, Tom Edward Carlson, Inaki Asier Iturrate Gil

One of the challenges in using brain computer interfaces over extended periods of time is the uncertainty in the system. This uncertainty can be due to the user's internal states, the non stationarity of the brain signals, or the variation of the class dis ...

2014

Making the most of context-awareness in brain-computer interfaces

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Sareh Saeedi, Tom Edward Carlson

In order for brain-computer interfaces (BCIs) to be used reliably for extended periods of time, they must be able to adapt to the users evolving needs. This adaptation should not only be a function of the environmental (external) context, but should also c ...

2013

On the Need for Both Internal and External Context Awareness for Reliable BCIs

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Sareh Saeedi, Tom Edward Carlson

In this paper we argue that for brain-computer interfaces (BCIs) to be used reliably for extended periods of time, they must be able to adapt to the user’s evolving needs. This adaptation should not only be a function of the environmental (external) contex ...

2013

Real-time Prediction of Fast and Slow Delivery of Mental Commands in a Motor Imagery BCI: An Entropy-based Approach

Michael Christoph Gastpar, Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Sareh Saeedi

Providing adaptive shared control for Brain- Computer Interfaces (BCIs) can result in better performance while reducing the user’s mental workload. In this respect, online estimation of accuracy and speed of command delivery are important factors. This stu ...

2012