Respiration is of interest for many diseases like chronic obstructive pulmonary disease or congestive heart failure. Interesting is to access if and to what extend respiration is limiting for daily living activities of these patients.
Within this project the aim is to develop algorithms for reliable monitoring of respiration during light exercise for wearable sensors. However, during exercise the signal can be distorted. The first step in this project would include signal processing and motion artifact reduction approaches. If needed for algorithm development in-house data collection studies should be performed. Secondly, features would be extracted that allow follow up of respiration over time. The ultimate goal is to assess these features in clinical data from patients in cardiac and/or pulmonary revalidation programs.
- Signal processing.
- Feature extraction.
- Data analysis.
- Literature study.
- Msc Biomedical or Electrical Engineering or Computer Science.
- Available for 9 to 12 months.
- Experience with matlab and/or python.
- Interest in human physiology.
- Knowledge of data analysis approaches.
- Motivated student eager to work independently and expand knowledge in the field.
- Good written and verbal English skills
For all inquiries, please contact:
Ms Najat Loiazizi, HR specialist.
Telephone number: +31 (0)40 40 20 675