Publications de Ping-Keng Jao | EPFL Graph Search

EEG-Based Online Regulation of Difficulty in Simulated Flying

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Ping-Keng Jao

Adaptively increasing the difficulty level in learning was shown to be beneficial than increasing the level after some fixed time intervals. To efficiently adapt the level, we aimed at decoding the subjective difficulty level based on Electroencephalograph ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Machine-Learning Based Monitoring of Cognitive Workload in Rescue Missions with Drones

Dario Floreano, Ricardo Andres Chavarriaga Lozano, David Atienza Alonso, Fabio Isidoro Tiberio Dell'Agnola, Ping-Keng Jao, Adriana Arza Valdes

In search and rescue missions, drone operations are challenging and cognitively demanding. High levels of cognitive workload can affect rescuers’ performance, leading to failure with catastrophic outcomes. To face this problem, we propose a machine learnin ...

2022

Decoding Cognitive States under Varying Difficulty Levels

Ping-Keng Jao

Understanding cognitive states of human under different difficulty levels is useful in improving human-human and human-machine interactions. For example, a crucial factor in designing games is maintaining the engagement of players. An ideal scenario would ...

EPFL2020

EEG Correlates of Difficulty Levels in Dynamical Transitions of Simulated Flying and Mapping Tasks

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, David Atienza Alonso, Fabio Isidoro Tiberio Dell'Agnola, Ping-Keng Jao, Adriana Arza Valdes

Decoding the subjective perception of task difficulty may help improve operator performance, i.e., automatically optimize the task difficulty level. Here, we aim to decode a compound of cognitive states that covaries with the task difficulty level. We desi ...

2020

Using Robust Principal Component Analysis to Reduce EEG Intra-Trial Variability

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Ping-Keng Jao

Practical brain-computer interfaces need to overcome several challenges, including tolerance to signal variability within- and across sessions. We introduce Robust Principal Component Analysis (RPCA) as a potential approach to tackle intra-trial variabilit ...

2018

Analysis of EEG Correlates of Perceived Difficulty in Dynamically Changing Flying Tasks

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Ping-Keng Jao

Real-time workload estimation can be an important tool to improve human-machine interaction. Despite multiple efforts in this sense, most studies focused on tasks designed to have extreme conditions of workload (high vs low), and these levels remain rather ...

IEEE2018