Method and Algorithms to Improve Depression Care Using Wearable Device

Background: Depression leads to heavy cost within many developed countries. We introduce such a procedure to collect objective biometrics data and detect depression in a real-time manner. Purpose: This research aims to aid doctors increasing the accuracy of depression diagnosis while improving care outcomes and shorten the duration of treatment. Methods: We apply wearable devices to collect objective biometrics from patients and synchronize to a cloud-based database. Several algorithms are utilized to perform depression detection, supporting self-care method among patients and notify medical professions in severe cases. The analytics of the data is further utilized by medical professions to support the medical decision. Results: Comparing to traditional 4-9 months of treatment, our procedure was proven to improve depression care outcome significantly starting at 4th week while physicians, nurses, and patients all provide positive feedback to the questionnaire. Conclusion/ Implication for Practice: This research successfully lowers the side effect of depression drugs by 3 months while improving the relationship between caregivers and patients. If implemented in the future, will increase efficiency to depression care and reduce inefficient waste.