From Signals to Connection: Exploring Physiological Markers of Human–Nature Connectedness
Year: 2026
Type: conference-paper
Abstract: Human–nature connectedness (HNC) - the sense of belonging to the natural world - and empathy with nature are key drivers of pro-environmental attitudes and behaviors. This paper investigates whether these constructs can be inferred from non-invasive physiological, neural, and eye-tracking data. Using logistic regression models, we show that subjective self-reports consistently outperform physiological features, although multimodal signals provide complementary predictive value. We further demonstrate that domain-informed feature selection improves model relevance and interpretability. Overall, our findings emphasize the central role of subjective experience in capturing HNC and empathy with nature, while highlighting both the potential and current limitations of multimodal approaches. Future work should focus on larger, more diverse datasets and more robust feature extraction to improve generalizability.
Language: English
Topic: Urban Green Space and Health
Subfield: Urban Studies
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7216201787