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Publicação
Psychophysiological effects of guided imagery based intervention on elementary school children
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Orientador(es)
Resumo(s)
The MindRegulation-Socioemotional Learning (MR-SEL) project aimed to study the benefits of a relaxation and Guided Imagery (GI) based intervention on children in an elementary school context. To assess potential differences, one of the key physiological indicators of emotional regulation, well-being, and stress is Heart Rate Variability (HRV). HRV analysis is a widely utilized non-invasive method for assessing autonomic nervous system function and cardiovascular health. Software tools like Kubios HRV are the gold standard for HRV analysis; however, they require manual intervention for each recording. This approach becomes increasingly impractical with the growing volume of physiological data from wearable devices and large-scale studies. This dissertation is going to present an automated HRV analysis pipeline called HRVautomator that streamlines the entire workflow, including pre-processing, Electrocardiogram (ECG) signal filtering, quality evaluation, segment selection, and extraction of key autonomic nervous system metrics. The main goal of this study was to use this tool to evaluate HRV changes in school-aged children before, during, and after interventions from the MindRegulation project, which aimed to study the effects of a relaxation and GI intervention on the psychophysiological well-being of children in school. Results demonstrate a very close agreement between the pipeline and Kubios in metrics like Root Mean Square of Successive Differences (RMSSD), High-Frequency power (HF), Low-Frequency power (LF) and Poincaré plot standard deviation perpendicular the line of identity (SD1). Furthermore, improvements in HRV indices related to stress regulation were observed, with the Guided Imagery intervention showing particularly strong effects—relative to relaxation-only and control conditions—by increasing vagal dominance, reducing sympathetic activation, and supporting adaptive autonomic functioning.
Descrição
Tese de Mestrado, Engenharia Biomédica e Biofísica, 2026, Universidade de Lisboa, Faculdade de Ciências
Palavras-chave
Heart Rate Variability (HRV) Guided Imagery (GI) Autonomic Nervous System (ANS) Automated HRV Analysis School-based Intervention