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Evaluation of mental stress by physiological indices derived from finger plethysmography

Emiko Minakuchi1*, Eriko Ohnishi25, Junji Ohnishi26, Shigeko Sakamoto2, Miyo Hori2, Miwa Motomura3, Junichi Hoshino4, Kazuo Murakami2 and Takayasu Kawaguchi5

Author Affiliations

1 Graduate School of Comprehensive Human Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan

2 Bio-Laboratory, Foundation for Advancement of International Science, 3-24-16 Kasuga, Tsukuba, Ibaraki 305-0821, Japan

3 Department of Nursing, Ibaraki Prefectural University of Health Sciences, 4669-2 Ami, Inashiki, Ibaraki 300-0394, Japan

4 Department of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan

5 Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan

6 Department of Food and Nutrition, Faculty of Home Economics, Tokyo Kasei University, 1-18-1 Kaga, Itabashi, Tokyo 173-0003, Japan

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Journal of Physiological Anthropology 2013, 32:17  doi:10.1186/1880-6805-32-17

Published: 12 October 2013



Quantitative evaluation of mental stress is important to prevent stress-related disorders. Finger plethysmography (FPG) is a simple noninvasive method to monitor peripheral circulation, and provides many physiological indices. Our purpose is to investigate how FPG-derived indices reflect on mental stress, and to clarify any association between these physiological indices and subjective indices of mental stress.


Thirty-one healthy women (mean age, 22 years ± 2) participated. The participants rested by sitting on a chair for 10 min. They then performed a computerized version of the Stroop color-word conflict test (CWT) for 10 min. Finally, they rested for 10 min. FPG was recorded throughout the experiment. The participants completed a brief form of the Profile of Mood States (POMS) questionnaire before and after the test. Using the FPG data, we conducted chaos analysis and fast Fourier transform analysis, and calculated chaotic attractors, the largest Lyapunov exponent, a high-frequency (HF) component, a low-to-high-frequency (LF/HF) ratio, finger pulse rate and finger pulse wave amplitude.


The HF component decreased and the LF/HF ratio increased significantly during the test (P < 0.01), while the confusion subscale of POMS increased after the test (P < 0.05). During testing, finger pulse rate significantly increased (P < 0.001), and the finger pulse wave amplitude decreased (P < 0.001). The attractor size reduced during testing and returned to a baseline level afterwards. Although the largest Lyapunov exponent showed no significant change during testing, significant negative correlation with the tension-anxiety subscale of POMS was observed at the beginning (P < 0.01). A significant negative correlation between the LF/HF ratio and two subscales was also observed in the beginning and middle of the test (P < 0.05). There were no correlations during the rest periods.


The physiological indices derived from FPG were changed by mental stress. Our findings indicate that FPG is one of the easiest methods to evaluate mental stress quantitatively. In particular, the largest Lyapunov exponent and the LF/HF ratio might be associated with acute mental stress. Farther examination is needed to find any association between the physiological indices and various types of mental stress.

Chaos analysis; Color-word conflict test; Finger plethysmography; Mental stress; Peripheral circulation