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 Criteria:

• DSM-5 Bipolar disorder or depressive disorder
• 20~60 years old
• Willing to carry smartwatch and smartphone most of the time

Exclusion Criteria:

• Comorbid with substance use disorder
• Unable to use smartwatch and smartphone

We will recruit 100 patients with mood disorders from the psychiatric ward and outpatient services of the Department of Psychiatry, National Taiwan University Hospital. All the participants will be followed for one year to collect the daily activity level, sleep patterns, heart rate through actigraphy, as well as location, mood report, drug compliance and face photo through smartphone app that will be developed by Co-PI Lai.

All the data in this study will be appropriately maintained with protection of privacy and confidentiality. Any personal identifiable data will be replaced by research ID number.