Publications by Sareh Saeedi | EPFL Graph Search

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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Sareh Saeedi

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

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

Prediction of Command Delivery Time for BCI

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

Reliability and Adaptive Assistance in Brain-Computer Interfaces

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

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

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