Heart rate variability analysis for mental stress measurement in mobile settings

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Stress affects our body often detrimentally. It is essential to monitor stress levels frequently and continuously, which may be possible in the mobile settings. Heart rate variability (HRV) analysis is commonly used as a quantitative marker depicting the activity of autonomous nervous system (ANS) that may be related to mental stress. HRV features can be extracted by detecting QRS complexes from electrocardiogram (ECG) signals. In the present study, we developed ECG analysis software that enables to detect 99.3% of the QRS complexes correctly for the signal generated from the mobile sensor. To provide reliable assessment of HRV in mobile settings, we validated ultra short term HRV features since the conventional five min measurement might be inadequately long in mobile settings. The results suggested that we could assess cardiac activity and mental stress of individuals accurately and conveniently by ultra short term ECG recordings from mobile sensors. We also showed a feasibility of using a mobile ECG sensor to detect subtle changes in HRV features during the acute stress. We investigated the relationships of physiological measures and HRV features on stress factors of Stress Response Inventory (SRI) and age. Our results showed that stress levels were associated with ages, physiological measures, HRV features, and stress factors. We also found that depressed patients showed lower SDNN and CV whereas higher stress index (SI) during mental stress compared to normal group. Based on these findings we sought to devise and validate a stress formula that tells whether a subject belongs to low or high stress group. The results indicated that the stress formula devised from mean RR interval, SDNN, CV, PNN50, SI, HF, and anger scores predicted the stress levels within 75.6% accuracy. In conclusion, the results of these studies suggested that quantitative stress measurement may be possible in mobile settings. The stress formula together with the ultra short term ECG samp...
Advisors
Kim, De-Sokresearcher김대석researcher
Description
한국정보통신대학교 : 공학부,
Publisher
한국정보통신대학교
Issue Date
2007
Identifier
392863/225023 / 020058016
Language
eng
Description

학위논문(석사) - 한국정보통신대학교 : 공학부, 2007.8, [ x, 117 p. ]

Keywords

mobile; stress; ANS; autonomous nervous sytem; electrocardiogram; HRV; Heart rate variability; ECG

URI
http://hdl.handle.net/10203/54883
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=392863&flag=dissertation
Appears in Collection
School of Engineering-Theses_Master(공학부 석사논문)
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