Jelena Mladenovic

Univerzitet Union - Računarski Fakultet · Computer Science

Digital devices are now ubiquitous, and their capability to measure and react to our physiology is continuously improving. This is reflected in the ever-growing usage of self-monitoring technology (e.g., quantified self) as well as the increasing availability of bio- and neurofeedback applications. Yet, we argue that the use of physiological inform...

Objective. Neural self-regulation is necessary for achieving control over brain-computer interfaces (BCIs). This can be an arduous learning process especially for motor imagery BCI. Various training methods were proposed to assist users in accomplishing BCI control and increase performance. Notably the use of biased feedback, i.e. non-realistic rep...

Objective: Neural self-regulation is necessary for achieving control over brain-computer interfaces (BCIs). This can be an arduous learning process esspecially for motor imagery BCI. Various training methods were proposed to assist users in accomplishing BCI control and increase performance. Notably the use of biased feedback, i.e. non-realistic r...

While often presented as promising assistive technologies for motor-impaired users, electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) remain barely used outside laboratories due to low reliability in real-life conditions. There is thus a need to design long-term reliable BCIs that can be used outside-of-the-lab by end-users, e.g.,...

Brain-computer interfaces (BCIs) are systems that enable a person to interact with a machine using only neural activity. Such interaction can be non-intuitive for the user hence training methods are developed to increase one's understanding, confidence and motivation, which would in parallel increase system performance. To clearly address the curre...

Mental-Tasks based Brain-Computer Interfaces (MT-BCIs) allow their users to interact with an external device solely by using brain signals produced through mental tasks. While MT-BCIs are promising for many applications, they are still barely used outside laboratories due to their lack of reliability. MT-BCIs require their users to develop the abil...

Objective: Going adaptive is a major challenge for the field of Brain-Computer Interface (BCI). This entails a machine that optimally articulates inference about the user's intentions and its own actions. Adaptation can operate over several dimensions which calls for a generic and flexible framework. Approach: We appeal to one of the most compre...

Brain-Computer Interfaces (BCIs) are systems that enable a person to manipulate an external device with only brain activity, often using ElectroEncephaloGraphgy (EEG). Although there is great medical potential (communication and mobility assistance, as well as neuro-rehabilitation of those who lost motor functions), BCIs are rarely used outside of...

The clinical efficacy of neurofeedback is still a matter of debate. This paper analyzes the factors that should be taken into account in a transdisciplinary approach to evaluate the use of EEG NFB as a therapeutic tool in psychiatry. Neurofeedback is a neurocognitive therapy based on human–computer interaction that enables subjects to train volunta...

Recent research in the enteric nervous system, sometimes called the second brain, has revealed potential of the digestive system in predicting emotion. Even though people regularly experience changes in their gastrointestinal (GI) tract which influence their mood and behavior multiple times per day, robust measurements and wearable devices are not...

Adaptive Brain-Computer interfaces (BCIs) have shown to improve performance, however a general and flexible framework to implement adaptive features is still lacking. We appeal to a generic Bayesian approach, called Active Inference (AI), to infer user's intentions or states and act in a way that optimizes performance. In realistic P300-speller sim...

Designing a feedback that helps participants to achieve higher performances is an important concern in brain-computer interface (BCI) research. In a pilot study, we demonstrate how a congruent auditory feedback could improve classification in a electroencephalography (EEG) motor imagery BCI. This is a promising result for creating alternate feedbac...

We present a system that raises awareness about users' inner state. Dišimo is a multimodal ambient display that provides feedback about one's stress level, which is assessed through heart rate monitoring. Upon detecting a low heart rate variability for a prolonged period of time, Dišimo plays an audio track, setting the pace of a regular and deep b...

We present a system that raises awareness about users' inner state. Dišimo is a multimodal ambient display that provides feedback about one's stress level, which is assessed through heart rate monitoring. Upon detecting a low heart rate variability for a prolonged period of time, Dišimo plays an audio track, setting the pace of a regular and deep b...

There are numerous possibilities and motivations for an adaptive BCI, which may not be easy to clarify and organize for a newcomer to the field. To our knowledge, there has not been any work done in classifying the literature on adaptive BCI in a comprehensive and structured way. We propose a conceptual framework, a taxonomy of adaptive BCI methods...

Recent developments in computational neuroscience gave rise to an efficient generic framework to implement both optimal perceptual (Bayesian) inference and choice behaviour. This framework named Active Inference rests on minimizing free energy or surprise [3]. We suggest it could be used to implement efficient adaptive Brain-Computer Interfaces (BC...

Major issues in Brain Computer Interfaces (BCIs) include low usability and poor user performance. This paper tackles them by ensuring the users to be in a state of immersion, control and motivation, called state of flow. Indeed, in various disciplines, being in the state of flow was shown to improve performances and learning. Hence, we intended to...

Brain-Computer Interfaces (BCIs) have brought new, exciting and promising perspectives of interaction. On the one hand, active BCIs enable users to control applications (such as assistive technologies or video games) using their brain activity alone. On the other hand, passive BCIs bring the possibility of adapting an application/interface based on...

The inventory routing problem (IRP) deals with the study of the inter-relationship between two important activities in the supply chain: transportation of commodities and inventory management. In this paper, we study a variant of the multi-product IRP and we propose a general variable neighbourhood search metaheuristic for solving it. We present se...