ETRI-Knowledge Sharing Plaform



논문 검색
구분 SCI
연도 ~ 키워드


학술지 Skin conductance responses in Major Depressive Disorder (MDD) under mental arithmetic stress
Cited 20 time in scopus Download 16 time Share share facebook twitter linkedin kakaostory
김아영, 장은혜, 최관우, 전홍진, 변상원, 심주용, 최재훈, 유한영
PLOS ONE, v.14 no.4, pp.1-13
Public Library of Science
17HS5600, 정신 질환의 모니터링 및 징후 예측을 위한 피부 부착형 센서 모듈 개발, 김승환
Depressive symptoms are related to abnormalities in the autonomic nervous system (ANS), and physiological signals that can be used to measure and evaluate such abnormalities have previously been used as indicators for diagnosing mental disorder, such as major depressive disorder (MDD). In this study, we investigate the feasibility of developing an objective measure of depressive symptoms that is based on examining physiological abnormalities in individuals when they are experiencing mental stress. To perform this, we recruited 30 patients with MDD and 31 healthy controls. Then, skin conductance (SC) was measured during five 5-min experimental phases, comprising baseline, mental stress, recovery from the stress, relaxation, and recovery from the relaxation, respectively. For each phase, the mean amplitude of the skin conductance level (MSCL), standard deviations of the SCL (SDSCL), slope of the SCL (SSCL), mean amplitude of the non-specific skin conductance responses (MSCR), number of non-specific skin conductance responses (NSCR), and power spectral density (PSD) were evaluated from the SC signals, producing 30 parameters overall (six features for each phase). These features were used as input data for a support vector machine (SVM) algorithm designed to distinguish MDD patients from healthy controls based on their physiological responses. Statistical tests showed that the main effect of task was significant in all SC features, and the main effect of group was significant in MSCL, SDSCL, SSCL, and PSD. In addition, the proposed algorithm achieved 70% accuracy, 70% sensitivity, 71% specificity, 70% positive predictive value, 71% negative predictive value in classifying MDD patients and healthy controls. These results demonstrated that it is possible to extract meaningful features that reflect changes in ANS responses to various stimuli. Using these features, detection of MDD was feasible, suggesting that SC analysis has great potential for future diagnostics and prediction of depression based on objective interpretation of depressive states.
KSP 제안 키워드
Autonomic nervous system(ANS), Depressive symptoms, Healthy controls, Main effect, Major depressive disorder(MDD), Mental Stress, Mental arithmetic, Mental disorders, Physiological responses, Physiological signals, Positive predictive value(PPV)