our team gives thanks to God for our paper publication. we acknowledge this opportunity comes only through His grace.
our most recent publication is in AI, Brain and Child and is titled Investigating effects of microclimate on stress and affect using low-cost wearables in quasi-formal academic contexts.
its abstract reads:
The influence of microclimate on the affective state of learners is of interest in the context of anthropogenic climate change. In prior work, these impacts have been documented using electrodermal activity (EDA). This paper extends that approach with a multimodal analysis of neuro-physiological data in the context of scholastic activity with the inclusion of electroencephalography (EEG), facial action units (FAU), EDA, and photoplethysmography (PPG). Our methodology represents a citizen science, neuroergonomic and multi-pronged approach to investigate the relationships between human neuro-physiologic health and mental well-being. In the present study, low-cost, bespoke wearables were assembled, including EEG headsets, and physiological wristbands. EEG was chosen for its potential to offer neuro-physiological insights. EDA was incorporated as a non-invasive method to detect stress and emotional arousal. PPG was utilised as another indicator, being influenced by vascular, cardiac, and autonomic nervous systems. Finally, FAUs were analysed to prove the feasibility of FAUs as a stand-alone source of data which can support other analysis methods. Statistical tests and machine learning models were used to investigate relationships between neuro-physiological data, subjective data and the surrounding environment. Results suggest that features of the multimodal data were significant as they are correlated with environmental factors, and emotional arousal. The specific extent of the influence was also confirmed using Shapley values. With a deeper understanding of the feasibility of a robust multimodal approach, more complex relationships can be investigated with the upscaling of experiments for different age groups, especially children. This pipeline of data analysis could also be improved and enhanced by the usage of AI. Subsequently, there is potential for policy makers, and individuals to improve environments to maximise well-being.