Method for Detection of a Relapse Into a Depression or Mania State Based on Activity Data and/or Data Obtained by Questioning the Patient

Abstract

The invention relates to a method for detection of a relapse into a depression or mania state of a patient from a remission state wherein motor activity data is recorded using a wearable device worn by the patient and is received as input data by an evaluating unit and/or mood data is acquired by obtaining a questionnaire which has been completed by the patient, the questions of the questionnaire relating to the mania state, to the depression state and the questionnaire including at least one control question for checking the awareness and/or the ability to focus of the patient, the questions being designed such that they can be answered by multiple choice, and wherein the answers of the patient are input as input data into the evaluating unit, the input data is analyzed by the evaluating unit, wherein the condition of the patient is classified as remission, mania or depression by means of machine learning, and wherein a relapse is detected if the patient is classified as mania or depression. Further aspects of the invention relate to an evaluating system for detection of a relapse into a depression or mania state of a patient in a remission state based on motor activity data and/or mood data.

Dependencies are inferred from the claim text.