Stress Response Index for Adverse Childhood Experience Based on Fusion of Biomarkers

Citation

Aimie-Salleh N, Malarvili M & Whitttaker AC (2018) Stress Response Index for Adverse Childhood Experience Based on Fusion of Biomarkers. In: Proceedings of 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES). 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), Sarawak, Malaysia, 03.12.2018-06.12.2018. Piscataway, NJ, USA: IEEE, pp. 140-145. https://doi.org/10.1109/iecbes.2018.8626657

Abstract
Adverse childhood experiences has been suggested to cause change in physiological processes and can determine the magnitude of stress response which might have significant impact on health later in life. For this reason, detection of this altered stress response can be used as an indicator for future health. To detect the altered stress response, biomarkers that represent both autonomic nervous system (ANS) and hypothalamic-pituitary-adrenocorticol (HPA) is proposed. This study fuses the biomarker that represents both ANS and HPA as a single measure to classify the stress response based on adverse childhood experience and propose a stress response index as an future health indicator. Electrocardiograph (ECG), blood pressure, pulse rate and salivary cortisol (SCort) were collected from 12 participants who had adverse childhood experience while the remaining 11 acted as the control group. The recording session was done during a Paced Auditory Serial Addition Test (PASAT). HRV was then computed from the ECG and the HRV features were extracted. Next, the selected HRV features were combined with other biomarkers and the performance of the fused features were compared. From the result, fused feature by the parallel fusion; known as Euclidean distance (ed) demonstrated the highest performance with 80.0% accuracy, 83.3% sensitivity and 78.3% specificity. This performance was achieved using Support Vector Machine. Finally, the fused feature was fed into SVM in order to model the stress response index as an indicator for future health.

Keywords
Heart Rate Variability; Salivary Cortisol; Stress; Biomarkers; Fusion