Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

When passing this course, the student:

  • Understands the differences in practical requirements for data analysis in preventive care vs. specialised healthcare.
  • Understands and can objectively evaluate the merits of different devices for measuring behaviour during daily living.
  • Is familiar with the main methods to quantize: sleep quality, cognitive load and stress, food intake, and physical activity.
  • Can assess performance of low-cost measurements in different scenarios (risk assessment, lifestyle coaching, chronic disease management)
  • Understands the concept of adherence to interventions and is able to apply methods to assess it in practice.
  • Has basic knowledge of behaviour change technologies and motivational tools.
  • Understand the possibilities and limitations of using AI, ML and advanced data analysis methods for data-driven lifestyle change recommendations
  • Has knowledge of the technical considerations to take into account for integrating wellness/behaviour data with traditional healthcare databases.
  • The student has gained knowledge about common methods to model human behavioural patterns and to create personalised profiles.

Credits: 5

Schedule: 06.03.2023 - 30.06.2023

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Marcus van Gils

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • valid for whole curriculum period:

    See Learning outcomes

Assessment Methods and Criteria
  • valid for whole curriculum period:

    exercises, exam

Workload
  • valid for whole curriculum period:

    lectures, exercises

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Spring IV
    2023-2024 Spring IV