Toomas Põld, chief medical officer at Qvalitas Medical Centre, has just defended his doctoral thesis, at Tallinn University of Technology, on how to spot signs of depression using EEG-based metrics even before perceptible symptoms arise.
That is, before the patient even realises that something is wrong.
Doctors are frequently witnesses to how a stressful job and a fast pace of life can cause mental strain. Mental strain, in turn, causes stress, and when stress become chronic, it can further develop into depression, which can have a significant effect on one’s quality of life and capacity for work and can even prove fatal. Unfortunately, workers’ mental health is still a somewhat neglected area of occupational health.
Extraordinary doctoral thesis
What made you decide to research a depression-related topic? ‘In our work, we often come into contact with people who work in positions that require high stress tolerance. This made me wonder if it would be possible to use any markers other than questionnaires to assess patients’ mental health and the condition of their brains,’ explained Dr. Toomas Põld, who has been working for a number of years as Chief Medical Officer at Qvalitas Medical Centre – one of the best-known occupational health assessment service providers in Estonia.
Dr. Põld’s doctoral thesis can be considered extraordinary, because it is the first to explore the use of EEG techniques in the area of occupational health for early detection of mental strain and depression in workers. ‘I had heard that the Centre for Biomedical Engineering at Tallinn University of Technology had been using electroencephalographic signals to study patients suffering from depression, which gave me the idea to try to find ways to make it easier for physicians to make decisions regarding patients’ mental health during medical examinations. Electroencephalography, or EEG, devices have been going down in cost, and if doctors normally use ECG to monitor heart function, then it should be possible to assess brain activity in a similar manner. All that is needed is to develop a set of assessment criteria and the appropriate algorithms,’ Põld said.
Detection before perceptible symptoms
As medical students are mainly taught how to use EEG for diagnosing epilepsy, Põld noted that in the case of his doctoral thesis, he found it both challenging and exciting how different signal processing methods can be used to extract a host of different information from brain signals.
‘For example, the spectral asymmetry index can be used to assess the balance of slower and faster rhythms in brain signals, while the fractal dimension can give insight into signal complexity,’ Põld elaborated. According to him, the information gained through signal processing enables to describe changes in the EEG signal and, thus, the functioning of the brain, which can in turn be used to identify changes that are characteristic of depression. These changes should be able to provide information about the condition of the brain before perceptible symptoms begin to manifest. If so, it would allow us to detect depression even before the patient notices changes in their mental state.’
Early detection of abnormalities in brain function is vital for the prevention and timely treatment of burnout and subsequent depression among workers. This is particularly important in occupations where depression can compromise the safety of others, such as in aircraft pilots and air traffic controllers, as well as police officers and military personnel.
When will the new method reach medical practices?
‘In order for a novel approach to be integrated into the daily practices of occupational health assessment centres, it would be necessary to recruit thousands of subjects for the appropriate trials, to carry out the trials at various research centres, and finally to establish common assessment thresholds,’ said Põld, indicating that this will take some time. ‘It would be wonderful if, in addition to various questionnaires, doctors could also base their decisions on a set of markers that would allow them to better prevent dangerous situations involving soldiers, sailors, mission workers, and other occupations characterised by high mental strain and responsibility.’
Next year, the Association of Estonian Occupational Health Doctors should be publishing a set of guidelines, commissioned by the Ministry of Social Affairs, for the treatment of psycho-emotional risk factors. ‘I hope that my research will help us reach a better understanding of mental health disorders,’ Põld said.
With current methods, depression can sometimes go undetected
Depression is one of the main causes of disease burden and incapacity for work among the working-age population. In recent decades, depression has become a prevalent mental disorder around the world, and is especially common in developed countries. Work-related stress caused by psychosocial factors in the work environment can contribute to depression among workers. The ongoing crisis caused by the COVID-19 pandemic has only exacerbated the occurrence of depression.
Currently, mental disorders are diagnosed by a family physician, occupational health doctor, or psychiatrist based on an assessment of subjective symptoms using questionnaires and interviews. Other objective indicators are not used in clinical practice today, as a result of which cases of depression where the patient exhibits no external signs can sometimes go undetected.
Toomas Põld’s doctoral thesis Application of Electroencephalographic Signal Based Measures for Early Detection of Depression Symptoms in Occupational Health can be accessed in the digital collection of Tallinn University of Technology (the thesis was supervised by Maie Bachmann, a researcher at Tallinn University of Technology).