Proposed Bachelor and Master Theses

Improve health for everyone, one thesis at a time!

What you get

A ticket to a journey of high-quality research and development, with a successful bachelor or master thesis in computer science or a related field on the way. Potential projects we can explore:

1. Chronic disease longitudinal risk assessment

The top killers worldwide are chronic diseases, such as cardiovascular disease, lung disease, and diabetes. Existing risk assessment models can calculate the risk of such diseases, yet some of the risk factors (age, gender, smoking status, presence of diabetes, body-mass index, blood pressure, glucose, and cholesterol) are hard to obtain.

Scope: design, development, and deployment of a mobile platform that enables the data collection for these risk factors in a large population (n > 10.000).

Skills: strong programming skills, knowledge of statistics, exposure to mobile platform development (preferably iOS), and an inclination towards applying these in the health sciences.

Team: The coordinators are Katarzyna Wac and Vlad Manea, leveraging their collaboration with the R&D consortium of the H2020 WellCo project and Mads Schnoor Hansen. Teams of students welcome.

2. If you continue like this… scenarios for chronic disease

More than 40% of the risk of chronic diseases is due to unhealthy behaviors, such as physical inactivity, bad nutrition, poor sleep, or smoking status. However, there is no precise cause-effect formula that translates all these behavioral “markers” to the risk factors used in the risk assessment models from the literature.

Scope: research, development, and deployment of an interactive scenario generator based on the latest results in chronic disease risk assessment, longitudinal behavioral and health data from a large sample of the Danish population, and behavioral and health data from a participant.

Skills: For this thesis, it is important that the candidate has strong programming skills, knowledge of descriptive and inferential statistics, exposure to data visualization, and an inclination towards applying these in the health sciences.

Team: The coordinators for this thesis are Katarzyna Wac and Vlad Manea, leveraging the collaboration with the R&D consortium of the H2020 WellCo project. Teams of students welcome.

3. Say versus do – longitudinally (in)validating validated scales

For many behaviors (e.g., physical activity, sleep, nutrition) and personal states (e.g., conditions such as depression and anxiety, level of social support), over time, researchers have calibrated and validated simple questionnaires “in the office”. However, few studies have tested the validity of such questionnaires when correlated with data collected from daily life, “in the wild”.

Scope: research, design, development, deployment, analysis, and discussion of a comparative study between the outcomes obtained through the administration of a validated scale and those obtained through the collection of the analogous wearable data.

Skills: programming skills, knowledge of statistics, exposure to participatory design, and an inclination towards applying these in the health sciences.

Team: The coordinators for this thesis is Katarzyna Wac and Vlad Manea, leveraging the collaboration with validated scale experts at the University of Copenhagen. Teams of students welcome.

4. Platform MegaWars – Android vs iOS data collection to the limit!

Our living lab aims at leveraging smartphones and wearables towards collecting data from daily life, in time and context, over long periods of time. Such data does not only refer to the “usual” data an activity tracker may collect from the participant: number of steps (physical activity), hours slept (sleep), or heart rate (health state). Aspects of daily life can also be inferred from the proximity to the phone and the actual use of the phone.

Scope: development, deployment, and discussion of deep device instrumentation feature for our incoming iOS mobile platform. The lab already uses a similar feature in our Android mobile platform, which can serve as a starting point.

Skills: very strong programming skills, particularly in the Apple iOS universe, and interest in exploring iOS frameworks used in a mobile health context, such as HealthKit, ResearchKit, and ResearchKit EHR as well as external libraries and frameworks.

Team: The coordinator for this thesis is Katarzyna Wac, leveraging the collaboration within the Quality of Life technologies lab, in particular Alexandre DeMasi (University of Geneva, Android) and Vlad Manea (University of Copenhagen, iOS). Teams of students welcome.

5. Peer-ceived stress in situ

Are you stressed? Besides being a relevant question to ask nowadays, this is a recent study in our lab. The study explores the relationships between the state of the art stress assessment by using validated scale-based questionnaires that are self-administered by the participant, and the stress assessment by using exploratory questionnaires that are administered to the participant’s peers (friends, family, co-workers) in situ.

Scope: design and development of a mobile platform for peer stress assessment on the iOS platform, consisting of two applications: one for the individual and one for the peers.

Skills: good programming skills, particularly in the Apple iOS universe, and an interest in exploring iOS frameworks used in a mobile health context, such as HealthKit and ResearchKit.

Team: The coordinator for this thesis is Katarzyna Wac, leveraging the collaboration within the Quality of Life technologies lab, in particular Allan Berrocal (stress study researcher, University of Geneva, Android) and Vlad Manea (University of Copenhagen, iOS). Teams of students welcome.

Your turn

Write a mail to our lab leader Katarzyna Wac at wac@di.ku.dk and katarzyna.wac@unige.ch. We encourage theses in teams, so if you have a friend or two who are interested, you can write a thesis together and join forces to improve health for everyone!

Mobile Quality of Life Lab on the iOS platform

Department of Computer Science, Faculty of Science, University of Copenhagen, Denmark

Expeer – Implementing Trust In A Digital Car-Sharing Service

Department of Media, Cognition and Communication, University of Copenhagen, Denmark

Lifestyle-Based Chronic Disease Risk Assessment

Department of Computer Science, Faculty of Science, University of Copenhagen, Denmark

Exploring Data From Wearable Trackers (Fitbit) In Prediction Models For Implantable Cardioverter-Defibrillator (ICD) Patients – A Mixed Method Approach

Department of Health Informatics, University of Copenhagen, Denmark

GiFTER – Experiencing Giving and Receiving Gifts ‘On the Go’

Department of Media, Cognition and Communication, University of Copenhagen, Denmark

Diabetes Risk Assessment Based on Physical Activity and Sleep Duration Using Wearable Trackers

Department of Bioinformatics, Faculty of Science, University of Copenhagen, Denmark

Understanding Factors Influencing Loneliness And Corresponding Quality Of Life via Interviews, Smartphone Sensing And Data Modeling

Department of Computer Science, Faculty of Science, University of Copenhagen, Denmark

Supportive Learning During Lectures Using Mobile Services

Department of Computer Science, Faculty of Science, University of Copenhagen, Denmark | The Mobile App: Student Version Teacher Version

Factors Influencing Individual’s Sleep Quality and Quantity

Faculty of Humanities and Faculty of Science, University of Copenhagen, Denmark

Automated Ambulatory Detection and Prediction of Condition Worsening in Chronic Care

Department of Computer Science, Faculty of Science, University of Copenhagen, Denmark

Pervasive Services for Elderly with Mild Cognitive Impairments: Requirements and Design Implications

University of Geneva, Switzerland

Activity Level Estimator

University of Geneva, Switzerland

Capturing and interpreting Human Emotional States with an emo-BAN – A Feasibility Study

University of Twente, the Netherlands

Location-time Based TCP Delays Measurements for PocketPC

University of Geneva, Switzerland

Mobile User’s Location Prediction Study

University of Geneva, Switzerland

Performance Measurements, Designing a Generic Measure and Performance Indicator Model

University of Geneva, Switzerland

Equivalent Queue Model Capturing End-to-End Performance in Mobile Networks

Vrije University, the Netherlands (stay at the Blekinge Institute of Technology, Sweden)

Monitoring of End-to-End delay and Throughput in a UMTS Network

Vrije University, the Netherlands (stay at the Blekinge Institute of Technology, Sweden)

Development of the Location- and Time-Specific Context-Information Source

University of Geneva, Switzerland (stay at the University of Twente)

MobiVTag – A First Development

University of Geneva, Switzerland

Where is European’s Wireless Going?

University of Geneva, Switzerland