Preliminary findings from studies employing wearable technology to assess skin electrical impulses and other physiological indicators that could be linked to mood swings in bipolar disorder have been released. The research is still in its early stages, but the goal is to use these patterns to identify mood swings in bipolar disorder patients, which will aid in diagnosis and possibly lead to more effective, quicker treatments.
Illustration: Researcher wearing the Empatica E4 bracelet. Image Credit: Diego Hidalgo-Mazzei
Bipolar disorder is a mental condition that produces variations in a person's mood, energy, activity level, and focus. The execution of routine duties and interpersonal relationships may be challenging during these transitions.
Mood swings can range from feeling euphoric (very “up”) to despondent, depending on the individual. Currently, the majority of diagnoses for these mood fluctuations are made subjectively during medical interviews or through questionnaires. It takes time, and medical assistance is needed right away.
Now, a team of Barcelona-based psychiatrists has worked with data scientists in Edinburgh to continually gather several physiological indicators during the various phases and episodes of bipolar disorder using a research-grade wearable device.
Electrodermal activity, which uses variations in the skin’s electrical conductivity to reflect the degree of stress through the nervous system’s responsiveness, is one of the physiological biomarkers that have been gathered. This can act as a quick sign of whether someone is manic, depressed, or experiencing a typical emotional state.
They selected 19 healthy volunteers and 38 bipolar disorder patients from the Barcelona region.
Each participant was fitted with a commercially available Empatica E4 bracelet, which they were asked to wear for around 48 hours. This can measure a variety of physiological changes, but we were most interested in measuring small electrophysiological changes in the skin of the wearer. We found that bipolar disorder patients in their depressed phase had on average a significantly lower skin electrical activity than the rest of the bipolar group or the healthy control group. We also found that as an individual moved from manic to depressive state (or vice versa), this was detectable by a change in skin surface electrical activity.
Diego Hidalgo-Mazzei, Postdoctoral Researcher, Hospital Clínic of Barcelona
“It is important for the patient and doctor to know how and when these mood fluctuations take place. It is important also to highlight that the treatment is different for manic or depressive states. This can help with a prompt diagnosis and early personalized treatment, but it can also help in preventing adverse outcomes, for example in alerting to an increased risk of suicide, or of mood swings which may lead to dangers with activities such as driving. It is also easier to treat patients if we know if they are in a manic phase or a depressed phase,” Hidalgo-Mazzei added.
He further stated, “Until now, these mood swings have mostly been diagnosed subjectively, through interview with doctors or by questionnaires, and this had led to real difficulties. Arriving at the correct drug is difficult, with only around 30 to 40% of treated individuals having the expected response. We hope that the additional information these systems can provide will give us greater certainty in treating patients. We are still some ways from that though.”
Hidalgo-Mazzei concluded, “This is an exploratory observational study, so we need to look at a larger sample and use machine learning to analyze all the biomarkers collected by the wearers to confirm the findings to determine patterns which might indicate a specific episode. This may not be ideal for every bipolar disorder sufferer, in every circumstance, but a potential pattern may help in the future the people hardest hit by the mood changes which affect their lives.”
A 2019 study estimates that around 700,000 people in Europe suffer from bipolar disorder, which affects between 1% and 2% of the population (precise figures are hard to come by). That is comparable to a city the size of Glasgow, Washington, DC, or Frankfurt.
In this seminal study, Dr Hidalgo and collaborators have laid the foundation for a new approach to diagnosing and treating bipolar disorders. Bipolar disorder is defined by the occurrence of episodes (either manic or depressive) interspersed with periods of wellbeing known as euthymia. To date, the course of the illness is entirely unpredictable, and the occurrence of new episodes relies solely on their early recognition at a subjective level through early-warning symptoms.
Paolo Ossola, Professor, University of Parma
Ossola stated, “Having a physiological biomarker that extends beyond the subjective level would enable more timely intervention. More importantly, the fact that it originates from a wearable device could assist individuals who, due to geographical reasons, lack easy access to clinical facilities. The shift from the subjective to the biological level could also promote understanding of the underlying mechanistic dynamics of mood swings. Previous attempts, based on the study of motor behavior using wearable devices, failed to differentiate, for example, the restlessness caused by anxiety in a depressive episode from the initial hyperactivation associated with a manic switch. A more finely tuned biomarker, such as conductance, could capture these subtle changes and thus determine whether a treatment is effective and the reasons behind it.”
“As the authors note, this is just a preliminary exploratory study, but their encouraging results could pave the way for future research aimed at unravelling clinical puzzles in the diagnosis and treatment of bipolar disorder. The exciting collaboration between doctors and data scientists is significantly accelerating the development of this new branch of precision psychiatry. I eagerly anticipate the much-needed transition from ‘bench to bedside’ with these technologies becoming available in community-based mental health settings,” Ossola concluded.
This study will be presented at the 36th ECNP Congress, which will be held online and in Barcelona from October 7–10, 2023. The ECNP Congress, with more than 6,000 attendees, is Europe’s premier venue for the most recent findings in disease-related neuroscience.
The Baszucki Brain Research Fund grant from the Milken Institute, the ISCIII (FIS PI21/00340, TIMEBASE Study), and the European Union all contributed to the funding of this study.