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Using deep LEARNing to predict MOOD changes in patients with depression

17 August 2020

Huge amounts of interesting data can be collected from consumer wristwatch fitness trackers such as the popular 'Fitbits'. Some evidence suggests this information can be used to detect mood changes. This could be very useful especially in patients with mood disorders such as depression. This study will look at whether we are able to detect mood changes in people with depression using information collected from wristwatch fitness trackers.

Requirements

  • Current diagnosis of major depressive disorder
  • Currently taking stable dose of Selective Serotonin Reuptake Inhibitors (SSRIs) for at least two weeks
  • Age between 18 and 65 years old
  • Own a smartphone
  • Have access to the internet
  • Have an active email address

Take part in this study

Keywords

Ethical approval

This study received ethical approval from the NHS Surrey Research Ethics Committee on the 26th June 2020.

Contact researcher

Academic study
 

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