EEG Correlates of Well-Being Using a Low-Cost Wearable System

February 2, 2022
Science Team

Can well-being be monitored, predicted, and improved in an affordable way using wearable EEG technologies?

What Is Well-being?

While well-being used to be considered as either a function of positive/negative emotions or as a function of fulfilling one’s purpose, it is now commonly considered a multidimensional construct comprising the emotional, physical, psychological, and social dimensions. It is modulated by many different factors (that vary across cultures) such as age, life purpose, self-acceptance, autonomy, coping strategies when facing stressful events, income level, social relationships, spirituality engagement, personality traits, family and parenting roles, work-life balance, mental health and disabilities, and more.

Individuals with high well-being can bounce back from stressful or adverse events and live happier and more fulfilled lives. However, measuring the subjective experience of well-being is not easy, since it encompasses so many variables.

Well-being and the Brain

Why it’s important: long-term changes in well-being (e.g., depression) changes the structure of the brain, which in turn, further affects well-being levels. Furthermore, being aware of one’s depression is the first step to healing, and might be altered in depressed patients. It is therefore crucial to detect signs of low mental health early, to prevent long-term changes that are harder to heal. Medications can have side effects and be very costly.

While much is still unknown about the exact relationship between the brain and well-being, we know that the main brain systems involved in executive function, emotion regulation, motivation, or neuropathology (e.g., reward, stress, limbic systems) are crucial for long-term well-being and mental health.

Electroencephalography (EEG) is a non-invasive (harmless) method that measures the brain’s electric fields through electrodes attached to the head. It has been used for decades by researchers and clinicians. It is much more affordable than other technologies like fMRI for example, and better captures the fast brain dynamics (millisecond accuracy vs 0.5 s for fMRI).

EEG activity picked up over the frontal regions reflects crucial brain mechanisms involved in well-being. Alpha oscillations (populations of neurons “firing” together between 8-13 Hz) typically reflect inhibition (deactivation) of the brain activity in the same region. Frontal alpha asymmetry (FAA) is simply the difference in alpha power between the left and the right frontal regions. Relatively lower alpha in the left frontal area therefore reflects greater cortical activation in that area, and is linked to approach motivation behaviors (e.g., happiness, enthusiasm, positive emotions, addiction or risk-taking when extreme etc.), whereas relatively lower alpha in the right frontal region reflects avoidance motivation behaviors (e.g., withdrawal, lack of motivation, depression, anxiety, etc.). Similar alpha asymmetries that have been observed in the posterior regions of the brain can go in the opposite direction, and have been linked to depression and anxiety.

What Is Novel About Our Study?

Alpha asymmetry has not been used to directly study well-being to our knowledge, and therefore seems like a great candidate to study well-being. Furthermore, most studies are conducted in small and undiversified groups of participants, leading to some difficulties in replicating the robustness of this measure for clinical applications, and identifying the role of covariables or individual differences on the effects. For example, how does age affect the alpha asymmetry? This is mainly because EEG is still a costly and time-consuming technology for researchers.

Recently, technological advances have led to the development of affordable wearable EEG systems that can allow researchers to record EEG much faster (minutes instead of hours of preparation), at lower costs (hundreds of dollars instead of tens of thousands), and on larger and more diverse populations (hundreds of participants instead of a few dozen). However, their capacity to collect high signal quality has been debated.

Study Setup and Aims

We validated a low-cost wearable system to make sure it could reliably record alpha oscillations. Then, we used this system to record EEG on 230 people (22-80 years old, 64.3% female) that came to the IONS Discovery Lab (IDL) and filled out our online survey. We looked at:

  1. How alpha asymmetry may be linked to well-being levels (in frontal and posterior regions).
  2. How some covariables (age and gender) could be linked to alpha asymmetry and well-being.
  3. Whether EEG asymmetries in the other main frequency bands (delta 1-3 Hz, theta 3-7 Hz, beta 14-30 Hz) could also be linked to well-being.

Our Findings

Contrary to our main hypothesis, no association was found between well-being and frontal alpha asymmetry (FAA). However, well-being was linked to alpha asymmetry in the posterior region, in the opposite direction compared to the literature on FAA. That is, well-being was higher when alpha power was higher in the left posterior area relative to the right one.

Gender was not linked to either well-being or alpha asymmetry but age was significantly linked to both well-being and posterior alpha asymmetry, suggesting that it might be a mediator variable. In other words, the brain mechanisms associated with well-being are influenced by aging.

Asymmetries in the other frequency bands did show any relationship with well-being.


We showed that it is possible to measure brain activity to study and monitor well-being using low-cost wearable technologies (although some limitations/challenges are discussed in the manuscript and careful methods should be used).

We revealed that well-being might rely on brain processes different from the traditional ones underlying motivation and emotions, and potentially a more cognitive dimension (what we do with our emotions as opposed to which emotions emerge). These mechanisms may rely on deeper and more posterior systems or the brain (e.g., neuromodulators), as opposed to surface and prefrontal ones (e.g., cortex).

Where Do We Go From Here?

This study and the tools employed will help more researchers and clinicians to measure well-being levels, predict, and prevent negative outcomes (e.g., depression relapse, treatment response, etc.). Furthermore, the more we can understand the brain mechanisms underlying well-being, the better we can help enhance these processes and intervene when necessary to increase well-being for all.

These wearable technologies and findings can be used to develop neurofeedback training protocols, which can help people self-regulate and train their emotions and thoughts patterns, with the technology helping bring awareness to the ongoing mental states. Neuromodulation techniques (e.g., magnetic stimulation of the brain) can be used (clinically) to target these networks. If done carefully by professionals, it is possible to modulate these systems to reduce depression, addictions, or any negative tendency.

In the long term, when the remaining technical challenges are overcome, clinicians will be able to monitor patients and to conduct these EEG-based therapies remotely while patients are in the comfort of their home.

Read more about this study and the results in the paper “Electroencephalography Correlates of Well-Being Using a Low-Cost Wearable System” published in Frontiers in Human Neuroscience.

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