Using a Smartwatch to Predict Mood Episodes in Bipolar Disorder
Tests whether smartwatch data predicts manic or depressive episodes in adults with bipolar disorder.
Plain-language title generated from the registry record
Registry title: Prediction on the Recurrence of Manic and Depressive Episodes in Bipolar Disorder
Key facts
- Where
- Taipei, TaiwanSee the site
Could this be for you?
Answer for yourself. This is not a decision: only the study team can say whether you can take part.
- Are you between 20 and 60 years old?
Source: NCT05828056, who can take part
Where in Taiwan
- National Taiwan University HospitalTaipei, TaiwanTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- National Taiwan University Hospital
- Trial code
- NCT05828056
- Record updated
- 31 July 2026
- Original description
Mood disorders (including bipolar disorder and major depressive disorder) are chronic mental disorders with high recurrent rate. The more the number of recurrence is, the worse long-term prognosis is. This study aims to establish a prediction model of recurrence of manic and depressive episodes in mood disorders, with a hope to detect recurrence relapse as early as possible for timely clinical intervention. We will adopt wearable smart watch to collect heart rate, sleep pattern, activity level, as well as emotional status for one year long in 100 patients with bipolar disorder, and annotated their mood status (i.e., manic episode, depressive episode, and euthymic state). We expect to establish prediction models to predict the recurrence of mood episodes.Read full original descriptionShow less
Prediction on the Recurrence of Manic and Depressive Episodes in Bipolar Disorder
Mood disorders (including bipolar disorder and major depressive disorder) are chronic mental disorders with high recurrent rate. The more the number of recurrence is, the worse long-term prognosis is. This study aims to establish a prediction model of recurrence of manic and depressive episodes in mood disorders, with a hope to detect recurrence relapse as early as possible for timely clinical intervention. We will adopt wearable smart watch to collect heart rate, sleep pattern, activity level, as well as emotional status for one year long in 100 patients with bipolar disorder, and annotated their mood status (i.e., manic episode, depressive episode, and euthymic state). We expect to establish prediction models to predict the recurrence of mood episodes.
Inclusion: DSM-5 Bipolar disorder or depressive disorder; 20~60 years old; Willing to carry smartwatch and smartphone most of the time.
Exclusion: Comorbid with substance use disorder; Unable to use smartwatch and smartphone.