WJNSWorld Journal of Neuroscience2162-2000Scientific Research Publishing10.4236/wjns.2012.22016WJNS-19445ArticlesBiomedical&Life Sciences Changes in reaction time, coefficient of variance of reaction time, and autonomic nerve function in the mental fatigue state caused by long-term computerized Kraepelin test workload in healthy volunteers aisukeKuratsune1*SeikiTajima2JunichiKoizumi3KouziYamaguti4TetsuyaSasabe4KeiMizuno5MasaakiTanaka6NaokoOkawa7HidekiMito7HirokazuTsubone8YasuyoshiWatanabe5MasayasuInoue1HirohikoKuratsune6RIKEN, Center for Molecular Imaging Science, MI R&D Center, Kobe, JapanDepartment of Biochemistry and Molecular Pathology, Graduate School of Medicine, Osaka City University, Osaka, JapanDepartment of Comparative Pathophysiology, Veterinary Medical Sciences, Graduate School of Agricultural & Life Science, The University of Tokyo, Tokyo, JapanDepartment of Physiology, Graduate School of Medicine, Osaka City University, Osaka, JapanClinical Center for Fatigue Science, Graduate School of Medicine, Osaka City University, Osaka, JapanHyogo Children’s sleep and development medical research center, Kobe, JapanDivision of Materials Science and Chemical Engineering, Yokohama National University, Yokohama, JapanFaculty of Health Science for Welfare, Kansai University of Welfare Sciences, Kasiwara, Japan* E-mail:kura@fuksi-kagk-u.ac.jp(AK);29052012020211311825 November 201117 January 2012 16 February 2012© Copyright 2014 by authors and Scientific Research Publishing Inc. 2014This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/

Fatigue is a common sense caused by crushing labor, stressful social events and various illnesses. It is usually judged by their subjective symptoms, but it should be evaluated in an objective perspective. Here we show that the decrease of working efficiency and sympathetic hyperactivity are associated with mental fatigue state caused by prolonged mental workload. Recently we made a new mental fatigue model of healthy volunteers caused by long-term computerized Kraepelin test (CKT) workload. CKT is our new software for automatically checking the calculation capability, with which it is easy to determine the reaction time (RT), coefficient of variance of reaction time (CV), and accuracy of the answers (AC) during tasks. We put 24 healthy volunteers into the fatigue state by subjecting them to 120 minutes’ CKT workload, and then studied the changes in fatigue sensation, RT, CV, and AC before and after the CKT workload. The fatigue sensation, RT, and CV were clearly increased by the fatigue-inducing task and recovered during the resting period. We also studied the changes in autonomic nerve activity by using heart rate variability analysis. The low/high frequency component ratio (LF/HF) was signifi-cantly increased by the fatigue-inducing task and decreased by resting, suggesting that mental stress causes a relatively sympathetic nerve activity-dominant state. Therefore, our new fatigue model involving a long-term CKT workload is a good mental fatigue model to provide much information about the fatigue state simultane-ously, and the increase of RT, CV, and proportion of sympathetic activity (LF/HF) are associated with mental fatigue state. These might be useful objective biomarkers or evaluating a mental fatigue state.

Fatigue; Computerized Kraepelin Test; Reaction Time; Accuracy of the Answers; Autonomic Nerve Activity1. INTRODUCTION

It is well known that stressful social events frequently become the trigger for acute mental fatigue and sometimes cause problems with mental health and chronic fatigue, occasionally resulting in death in the case of overwork [1-3]. In Japan, 60% of the general adult population complaints of fatigue and one third of the population suffers from chronic fatigue [4]. Furthermore, about four hundred people have died caused by overwork every year. In 2006, the Japanese Ministry of Health, Labor, and Welfare made a new law for protecting against health problems due to overwork. According to this new law, Industrial physicians have to check the mental and physical health conditions of all laborers, if they work more than 100 hours overtime per month. However, no specific biomarkers for fatigue state have been found, and the vast majority of industrial physicians have judged their health conditions just by the subjective symptoms given in questionnaires and physiological observations. Therefore, Japanese physicians are extremely eager for evaluating worker’s fatigue state objectively by using some makers of fatigue.

In 2009, the new study group for fatigue supported by the Japanese Ministry of Health, Labor, and Welfare (Head: Kuratsune H) was set up, and the sensitivity and the specificity of several makers of fatigue state including autonomic nerve activity have been studied. Recently we demonstrated that autonomic nervous alterations are associated with daily level of fatigue [5], and that mental fatigue caused by prolonged cognitive load is associated with sympathetic hyperactivity [6].

Our co-workers K. Yamaguti and T. Sasabe devised the new software named the Computerized Kraepelin Test (CKT) for conveniently checking the calculation capability. Using this software, it is easy to determine the reaction time (RT), coefficient of variance of reaction time (CV), and accuracy of the answers (AC) during this test. Since the long-term CKT workload causes mental fatigue state, there is a possibility that a mental fatigue model of healthy volunteers would be produced by using this workload. Furthermore, as mentioned above, the CKT itself is the software for checking certain kinds of brain functions. Therefore, it also is available for checking changes in brain function during the fatigue state caused by the long-term CKT workload. In this present study we evaluated the fatigue sensation, and brain function in terms of RT, CV, AC, and autonomic nerve function during, before and after the long-term CKT workload in healthy volunteers.

2. MATERIALS AND METHODS2.1. Subjects

The subjects in this study were 24 students in Kansai University of Welfare Sciences (4 males and 20 females, 19 - 22 years of age). The study protocol complied with the Helsinki Declaration for Human Experimentation. The protocol was approved by the Ethics Committee of Kansai University of Welfare Science, and all subjects gave their written informed consent for the study.

2.2. Protocol of Task

We conducted a 2-day experiment. At the first and second morning without eating breakfast, all subjects assessed their subjective fatigue levels by using the visual analog scale (VAS) from 0 (minimum) to 100 (maximum). Their baseline autonomic nerve activities were determined by using heart rate variability analysis of the data from a 5-minute electrocardiogram (ECG) before the fatigue-inducing task. After this analysis, each subject performed a 2-hour fatigue-inducing task (see details in the following paragraph) without rest. After this task, they assessed their subjective fatigue levels by using VAS at 0, 20, and 60 minutes after the start of their rest period [7]. Their autonomic nerve activities were also examined again by 5-minute ECG before and after 20-, and 35-minute rest (Figure 1(a)). During the 2-hour fatigue-inducing task and 55-minute rest period, all subjects maintained the fasting state with the exception that they drank water.

2.3. Computerized Kraepelin Test (CKT)

In this study, computerized Kaepelin test was used as a fatigue-inducing task. Two digits from 0 to 9 and one “+” symbol were displayed at the top of the laptop computer screen (Figure 1(b)). Ten digits, from 0 to 9, were also displayed at the half bottom of the screen. The examinee was ordered to add these 2 digits at the top of the screen and show the answer by selecting a 1-digit number from 0 to 9 displayed at the half bottom of the screen by using a pointing device. For example, in the case of “6 + 5” on the laptop computer screen, the answer is 11; but the examinee should select the last 1-digit number of 1. When the examinee selected a 1-digit number on the screen, 2 new digits from 0 to 9 immediately appeared at the top of the screen. The examinee had to continue this procedure for 120 minutes as a fatigue-inducing task. The reaction time (RT), coefficient of variance of reaction time (CV), and accuracy of all of the answers (AC) were recorded automatically.

Since the response of most of the examinees during the first 5 minutes of this fatigue-inducing task was slow because of their inexperience, we evaluated the RT, CV, and AC at 6 - 10 minutes, 61 - 65 minutes, and 116 - 120 minutes after the beginning of the task as the change in response due to the fatigue state.

Furthermore, we also evaluated the RT, CV, and AC for 4 minutes after a 1st 20- and a 2nd 35-minute rest for evaluating the change in the response due to their recovery by resting (Figure 1(a)).

2.4. Measurement of Heart Rate Variability

ECG signals were collected on-line via 3 electrodes attached to both wrists. These ECG signals were collected at 1000 Hz and converted from analog to digital with a 12-bit resolution. R-wave peaks were detected by using an LRR-03 device (GMS Co., Tokyo, Japan). R-R wave variability was measured as an indicator of autonomic nerve activity. The system calculated instantaneously the R-R intervals as the difference between successive R-wave peaks.

2.5. Spectral Analysis

Frequency-domain analyses of HRV were performed on a collected R-R interval time series of 5 consecutive minutes by using the maximum entropy method (MemCalc; GMS Co., Tokyo, Japan) [8]. Thirty-second subsequences of R-R intervals that started at every beat were generated. The power integrals of the low-frequency component (LF, 0.04 to 0.15 Hz) and high-frequency component (HF, 0.15 to 0.40 Hz), as well as the LF/HF ratio, were calculated in all 30-second R-R interval subsequences. Finally, the mean of the LF/HF ratio in the whole time series was chosen as an autonomic index in this study.

2.6. Statistical Analysis

Differences in variables between groups were assessed by using a multivariate analysis of variance (type II MANOVA), which was performed on the fatigue VAS score, LF/HF ratio, RT, and CV of CKT. R version 2.8.0 was used to perform all multivariate analyses of variance [9].

3. RESULTS3.1. Behavioral Results

The fatigue VAS (fVAS) scores of the 24 students before and after the long-term (2-hour) CKT workload are shown in Figure 2. The fVAS scores at both 1st and 2nd days were increased by the fatigue-inducing task and recovered to the baseline level by the rest. Those increases and recovery from the fatigue sensation were statistically signifycant (type II MANOVA, p < 0.001). The fVAS score for the morning of the 2nd day (2nd day baseline) tended to be higher than that for the morning of the 1st day (type II MANOVA, p = 0.0547).

Figure 3(a) shows the change in the RT of the 24 students before and after the CKT workload. Their RT was significantly increased by the fatigue-inducing task and recovered by the rest at both 1st and 2nd days (type II MANOVA, p < 0.005). The RT of the 1st –day session during and after the CKT workload tended to be longer than that of the 2nd-day session (type II MANOVA, p = 0.093).

ReferencesUchiyama, S. Kurasawa, T. Sekizawa T. and Nakatsuka H. (2005) Job strain and risk of cardiovascular events in treated hypertensive Japanese workers: Hypertension follow-up group study. Journal of Occupational Health, 47, 102-111. doi:10.1539/joh.47.102Mizuno-Lewis S. and McAllister, M. ,et al. (2008)Taking leave from work: The impact of culture on Japanese female nurses Journal of Clinical Nursing 17, 274-281.Iwasaki, K., Takahashi, M. and Nakata. A. (2006) Health problems due to long working hours in Japan: working hours, workers’ compensation (Karoshi), and preventive measures. Industrial Health, 44, 537-540. doi:10.2486/indhealth.44.537Watanabe, Y. (2008) Preface and mini-review: Fatigue science for human health. In: Watanabe, Y., Evengard, B., Natelson, B.H., Jason, L.A. and Kuratsune, H., Eds., Fatigue Science for Human Health, Springer, New York, 5-11.Tanaka, M., Mizuno, K., Yamaguti, K., Kuratsune, H., Fujii, A., Baba, H., Matsuda, K., Nishimae, A., Takesaka, T. and Watanabe, Y. (2011) Autonomic nervous alterations associated with daily level of fatigue. Behavioral and Brain Functions, 7, 46. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3214128/pdf/1744-9081-7-46.pdfMizuno, K., Tanaka, M., Yamaguti, K., Kajimoto, O., Kuratsune, H. and Watanabe, Y. (2011) Mental fatigue caused by prolonged cognitive load associated with sympathetic hyperactivity. Behavioral and Brain Functions, 7, 17. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3113724/pdf/1744-9081-7-17.pdfLee, K.A., Hicks, G. and Nino-Murcia, G. (1991) Validity and reliability of a scale to assess fatigue. Psychiatry Research, 36, 291-298. doi:10.1016/0165-1781(91)90027-MShinba, T., Kariya, N., Matsui, Y., Ozawa, N., Matsuda, Y. and Yamamoto, K. (2008) Decrease in heart rate variability response to task is related to anxiety and depressiveness in normal subjects. Psychiatry and Clinical Neurosciences, 62, 603-609. doi:10.1111/j.1440-1819.2008.01855.xIhaka R. and Gentleman, R. ,et al. (1996)A language for data analysis and graphics Journal of Computational and Graphical Statistics 5, 299-314.Ataka, S., Tanaka, M., Nozaki, S., Mizuma, H., Mizuno, K., Tahara, T., Sugino, T., Shirai, T., Kajimoto, Y., Kuratsune, H., Kajimoto, O. and Watanabe, Y. (2008) Effects of oral administration of caffeine and D-ribose on mental fatigue. Nutrition, 24, 233-238. doi:10.1016/j.nut.2007.12.002Stefank, K. (1923) Reaction time and fatigue. Science, 57, 204-205. doi:10.1126/science.57.1468.204-aAkselrod, S., Gordon, D., Ubel, F.A., Shannon, D.C., Berger, A.C. and Cohen, R.J. (1981) Power spectrum analysis of heart rate fluctuation: A quantitative probe of beat-to-beat cardiovascular control. Science, 213, 220-222. doi:10.1126/science.6166045Pagani, M., Furlan, R., Pizzinelli, P., Crivellaro, W., Cerutti, S. and Malliani, A. (1989) Spectral analysis of R-R and arterial pressure variabilities to assess sympathovagal interaction during mental stress in humans. Journal of Hypertension, 6S, 14-15.Lucini, D., Di Fede, G., Parati, G. and Pagani, M. (2005) Impact of chronic psychosocial stress on autonomic cardiovascular regulation in otherwise healthy subjects. Hypertension, 46, 1201-1206. doi:10.1161/01.HYP.0000185147.32385.4bFilaire, E., Portier, H., Massart, A., Ramat, L. and Teixeira, A. (2010) Effect of lecturing to 200 students on heart rate variability and alpha-amylase activity. European Journal of Applied Physiology, 108, 1035-1043. doi:10.1007/s00421-009-1310-4Kuratsune, H., Yamaguti, K., Lindh, G., Eveng?rd, B., Hagberg, G., Matsumura, K., Iwase, M., Onoe, H., Takahashi, M., Machii, T., Kanakura, Y., Kitani, T., L?ngstr?m, B. and Watanabe, Y. (2002) Brain regions involved in fatigue sensation: Reduced acetylcarnitine uptake into the brain. Neuroimage, 17, 1256-1265. doi:10.1006/nimg.2002.1260Tajima, S., Yamamoto, S., Tanaka, M., Kataoka, Y., Iwase, M., Yoshikawa, E., Okada, H., Onoe, H., Tsukada, H., Kuratsune, H., Ouchi, Y. and Watanabe, Y. (2010) Medial orbitofrontal cortex is associated with fatigue sensation. Neurology Research International, 2010, Article ID 671421. doi:10.1155/2010/671421 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3003967/pdf/NRI2010-671421.pdf