Copyright © 2019 American College of Occupational and Environmental Medicine. Unauthorized reproduction of this article is prohibited Assessment of Objective Symptoms of Depression in Occupational Health Examination Toomas Po ˜ld, MD, Laura Pa ¨eske, MS, Maie Bachmann, PhD, Jaanus Lass, PhD, and Hiie Hinrikus, DSc Objective: The aim of the study was to assess early symptoms of depression in regular occupational health examination using the objective measures based on electroencephalographic (EEG) signal analysis. Methods: The study was performed on 125 volunteer participants. The resting-state EEG signal was recorded for 7 minutes. The spectral asymmetry index (SASI) and Higuchi fractal dimension (HFD) were calculated in EEG channel P z . Parallel, the participants were subjected to two psychological tests, observer-rated HAM-D and self-rated EST-Q-D. Results: The SASI revealed depressive symptoms for 64.8%, HFD for 55.2%, HAM-D for 44.8%, and EST-Q-D for 28.8% of participants. Combination of two different measures indicated depression symptoms up to 78.4% of partic- ipants. Conclusion: The results of this study confirm the feasibility of indication of early symptoms of depression applying EEG-based objective measures. Keywords: depression symptoms, early detection, electroencephalography, Higuchi fractal dimension, occupational stress, psychological tests, spectral asymmetry index M ental disorders contribute to 56.7% of disability-adjusted life-years, peaking in early adulthood for mental and sub- stance use disorders and including remarkable part of working age population. 1 Depression has become a common mental disorder during last decades with a prevalence rate of 7% in developed countries. 1–3 The development of depression has been suggested to be related to work stress, caused by psychosocial factors in the work environment. 4–8 The work stress due to high demand and low control may precipitate clinical depression among employees. Mental disorders of workers and specialists may increase the risk of accidents especially in the cases of high personal responsibility (pilots, policemen, military specialists, etc). Therefore, early detec- tion of depression symptoms is expected to be beneficial to prevent further and more serious mental disorder and possible related accidents. Despite that, regular examination of depression symp- toms has still not become common in occupational health exami- nation. Clinical interview and psychological tests have been used in monitoring of depression symptoms in clinical practice, as well as in studies in work environment. 4–8 Tests and interviews as subjective measures, based on self-feeling, enable revealing only symptoms evident in the developed stage of depression. The detection of possible alterations in underlying physiology, foremost in brain behavior, can provide objective information about depression symp- toms and provide early detection of disorders. Alterations in human brain bioelectric activity are expected to be able to detect specific to mental disorders changes in brain bioelectric processes before the subjective symptoms become evident. Electroencephalography (EEG) is a tool suitable for nonin- vasive cost-effective monitoring the state of the brain including depression. 9–12 Many special studies on depression EEG have demonstrated that depression causes significant alterations in vari- ous EEG parameters between preselected groups of depressive and healthy subjects. 10–14 To the best of our knowledge, no EEG analysis based evaluation of depression has been performed for individual persons. The aim of the current study is to assess early symptoms of depression of employees in occupational health examination. For this purpose, objective measures, based on EEG signal analysis, have been used and subjective measures, based on psychological tests, explored for comparison. To assess objective depression symptom for individuals, two measures based on EEG analysis, the linear spectral asymmetry index (SASI) and the nonlinear Higuchi fractal dimension (HFD), were calculated. 10,15 For comparison, two psychological tests were used for evaluation of subjective symptoms: the Hamilton Depres- sive Rating Scale HAM-D, assessed by a medical doctor, and the Emotional State Questionnaire for depression EST-Q-D, based on self-rated symptoms. 16,17 METHODS Participants In the current study, the volunteers from different institutions passing occupational health examination were invited to participate. As a result, 125 volunteers without declared depression episodes nor other mental disorders were selected for the study. According to the results of performed medical and biochemical examinations, the selected participants were healthy. The participants were asked to fulfill the questionnaire and declare their habits and health condi- tion. Average age of the group was 41.04 (median 41.00 years) with standard deviation of 8.66 years. Selected participants had a higher or secondary level of education and were employed as managers, specialists, engineers, etc. Unfortunately, none from the group of pilots accepted the invitation to participate in the study. The demographic factors of the selected group of participants are presented in Table 1. The participants were asked to abstain from alcohol for 24 hours and from coffee for 2 hours before the EEG recordings. All participants have been informed about the aim and procedures of the study and have signed written informed consent. The study was conducted in accordance with the Declaration of Helsinki and formally approved by the Tallinn Medical Research Ethics Committee. Procedures, Methods, and Equipment All participants underwent a clinical test by the medical doctor based on the 17-item Hamilton Depression Rating Scale From the Centre of Biomedical Engineering, Department of Health Technologies, Tallinn University of Technology, Tallinn, Estonia (Dr Po ˜ld, Dr Pa ¨eske, Dr Bachmann, Dr Lass, Hinrikus); and Qvalitas Medical Centre, Tallinn, Estonia (Dr Po ˜ld). This study was financially supported by the Estonian Ministry of Education and Research under institutional research financing IUT 19-2 and by the Estonian Centre of Excellence in IT (EXCITE) 2014-2020.4.01.15-0018 funded by the European Regional Development Fund. The authors declare no conflict of interest. Supplemental digital contents are available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal’s Web site (www.joem.org). Address correspondence to: Maie Bachmann, PhD, Centre of Biomedical Engi- neering, Department of Health Technologies, Tallinn University of Technol- ogy, Ehitajate tee 5, 19086 Tallinn, Estonia (maie@cb.ttu.ee) Copyright ß 2019 American College of Occupational and Environmental Medicine DOI: 10.1097/JOM.0000000000001622 JOEM  Volume 61, Number 7, July 2019 605 ORIGINAL ARTICLE