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A pediatric near-infrared spectroscopy brain-computer interface based on the detection of emotional valence
Erica D Floreani1,2, Silvia Orlandi1,3, Tom Chau1,2
1Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada.
Insights
This study developed a pediatric brain-computer interface (BCI) using emotional states to aid communication for children. The affective BCI shows feasibility for school-aged children, paving the way for future assistive technologies.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Human-Computer Interaction
Background:
- Brain-computer interfaces (BCIs) offer communication pathways for individuals with physical disabilities by bypassing motor control.
- Research on BCIs for children is limited, and traditional methods may not suit their developmental needs.
- Emotional state detection presents a novel, alternative access method for pediatric BCIs.
Purpose of the Study:
- To develop and evaluate a pediatric BCI system for identifying emotional states (positive/negative) in children.
- To explore the feasibility of using functional near-infrared spectroscopy (fNIRS) to detect hemodynamic changes in the prefrontal cortex (PFC) associated with emotions.
- To assess the effectiveness of neurofeedback in helping children regulate emotional states and modulate brain activity.
Main Methods:
- Developed a pediatric BCI using fNIRS to measure prefrontal cortex hemodynamic activity.
- Recruited 10 neurotypical children (aged 8-14) for four experimental sessions (one offline, three online).
- Employed emotion-induction trials, visual neurofeedback, and adaptive, child-specific linear discriminant classifiers.
Main Results:
- Online valence classification accuracy exceeded chance for most participants by the final two sessions.
- A positive correlation was observed between age and BCI performance, indicating older children performed better.
- Offline analysis showed accuracies comparable to adult affective BCI studies using fNIRS.
Conclusions:
- Affective fNIRS-BCIs are feasible for school-aged children.
- Further research with more sessions, larger samples, and individuals with disabilities is needed to confirm practical potential.
- Emotional state detection offers a promising avenue for pediatric BCI development.
Abstract:
Brain-computer interfaces (BCIs) are being investigated as an access pathway to communication for individuals with physical disabilities, as the technology obviates the need for voluntary motor control. However, to date, minimal research has investigated the use of BCIs for children. Traditional BCI communication paradigms may be suboptimal given that children with physical disabilities may face delays in cognitive development and acquisition of literacy skills. Instead, in this study we explored emotional state as an alternative access pathway to communication. We developed a pediatric BCI to identify positive and negative emotional states from changes in hemodynamic activity of the prefrontal cortex (PFC). To train and test the BCI, 10 neurotypical children aged 8-14 underwent a series of emotion-induction trials over four experimental sessions (one offline, three online) while their brain activity was measured with functional near-infrared spectroscopy (fNIRS). Visual neurofeedback was used to assist participants in regulating their emotional states and modulating their hemodynamic activity in response to the affective stimuli. Child-specific linear discriminant classifiers were trained on cumulatively available data from previous sessions and adaptively updated throughout each session. Average online valence classification exceeded chance across participants by the last two online sessions (with 7 and 8 of the 10 participants performing better than chance, respectively, in Sessions 3 and 4). There was a small significant positive correlation with online BCI performance and age, suggesting older participants were more successful at regulating their emotional state and/or brain activity. Variability was seen across participants in regards to BCI performance, hemodynamic response, and discriminatory features and channels. Retrospective offline analyses yielded accuracies comparable to those reported in adult affective BCI studies using fNIRS. Affective fNIRS-BCIs appear to be feasible for school-aged children, but to further gauge the practical potential of this type of BCI, replication with more training sessions, larger sample sizes, and end-users with disabilities is necessary.
