Computational Analysis of the Effect of Islamic Spirituality on Heart Rate Response to Stress

Background and Objectives: Stress is a significant contributor to various diseases, necessitating effective management strategies. This study aimed to investigate the potential role of Islamic spirituality, conceptualized as both long-term disposition (“being spiritual”) and short-term practice (“engaging in spiritual acts”), in modulating heart rate (HR) responses to stress.  Methods: In this observational study, ۲۴ female students (mean age = ۲۸ years) were categorized using the Golzari religious belief commitment questionnaire. HR was recorded using a digital pulse oximeter during exposure to five standardized stress scenarios. For the short-term spirituality assessment, the experimental group performed Dhikr during recovery periods. HR signals were processed, and ۲۰ features were extracted using a Daubechies-۴ wavelet transform. Analysis of variance (ANOVA) was used for feature selection, and an extreme learning machine (ELM) classifier with a five-neuron hidden layer was employed for classification. Results: ELM classifier achieved ۹۴.۴% accuracy in distinguishing between high and low long-term spirituality groups based on HR responses. For short-term spirituality, it differentiated the Dhikr group from controls with ۸۸.۸% accuracy during recovery phases. Conclusion: Findings indicate that both facets of Islamic spirituality are associated with attenuated HR responses to stress, suggesting their potential role in mitigating physiological stress reactivity.

کلیدواژه ها:

Spirituality ، Stress ، Heart rate ، Extreme learning machine classification ، Computational analysis ، معنویت اسلامی ، استرس ، نوسانات ضربان قلب ، طبقه بندی ELM ، تحلیل محاسباتی