Publications by Ricardo Andres Chavarriaga Lozano

Customizing the human-avatar mapping based on EEG error related potentials during avatar-based interaction

Olaf Blanke, José del Rocio Millán Ruiz, Ronan Boulic, Bruno Herbelin, Ricardo Andres Chavarriaga Lozano, Fumiaki Iwane, Thibault Serge Mario Porssut

Objective. A key challenge of virtual reality (VR) applications is to maintain a reliable human-avatar mapping. Users may lose the sense of controlling (sense of agency), owning (sense of body ownership), or being located (sense of self-location) inside th ...

2024

EEG-Based Online Regulation of Difficulty in Simulated Flying

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, 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

EEG error-related potentials encode magnitude of errors and individual perceptual thresholds

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Aleksander Sobolewski, Fumiaki Iwane

Error-related potentials (ErrPs) are a prominent electroencephalogram (EEG) correlate of performance monitoring, and so crucial for learning and adapting our behavior. It is poorly understood whether ErrPs encode further information beyond error awareness. ...

Cell Press2023

EEG signature of breaks in embodiment in VR

Olaf Blanke, José del Rocio Millán Ruiz, Ronan Boulic, Bruno Herbelin, Ricardo Andres Chavarriaga Lozano, Fumiaki Iwane, Thibault Serge Mario Porssut

The brain mechanism of embodiment in a virtual body has grown a scientific interest recently, with a particular focus on providing optimal virtual reality (VR) experiences. Disruptions from an embodied state to a less- or non-embodied state, denominated Br ...

2023

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

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

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

User Adaptation to Closed-Loop Decoding of Motor Imagery Termination

José del Rocio Millán Ruiz, Kyuhwa Lee, Ricardo Andres Chavarriaga Lozano, Bastien Orset

One of the most popular methods in non-invasive brain machine interfaces (BMI) relies on the decoding of sensorimotor rhythms associated to sustained motor imagery. Although motor imagery has been intensively studied, its termination is mostly neglected. O ...

2021

Mobile brain/body imaging of landmark-based navigation with high-density EEG

Ricardo Andres Chavarriaga Lozano

Coupling behavioral measures and brain imaging in naturalistic, ecological conditions is key to comprehend the neural bases of spatial navigation. This highly integrative function encompasses sensorimotor, cognitive, and executive processes that jointly me ...

WILEY2021

Invariability of EEG error-related potentials during continuous feedback protocols elicited by erroneous actions at predicted or unpredicted states

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Inaki Asier Iturrate Gil, Fumiaki Iwane

Objective. When humans perceive an erroneous action, an EEG error-related potential (ErrP) is elicited as a neural response. ErrPs have been largely investigated in discrete feedback protocols, where actions are executed at discrete steps, to enable seamle ...

2021

Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials

Aude Billard, José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Iason Batzianoulis, Fumiaki Iwane

Robotic assistance via motorized robotic arm manipulators can be of valuable assistance to individuals with upper-limb motor disabilities. Brain-computer interfaces (BCI) offer an intuitive means to control such assistive robotic manipulators. However, BCI ...

NATURE PORTFOLIO2021

Closed-loop EEG study on visual recognition during driving

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Ruslan Aydarkhanov

Objective. In contrast to the classical visual brain-computer interface (BCI) paradigms, which adhere to a rigid trial structure and restricted user behavior, electroencephalogram (EEG)-based visual recognition decoding during our daily activities remains ...

2021