Visualization of complex high dimensional biomechanical data

Sarcopenia is a disease characterized by the decline of skeletal muscle mass, muscle strength, and physical performance. To gain a better understanding of this disease and to assess both functional and anatomical effects of sarcopenia, experimental and modeling data have been collected.
The neuromuscular models developed in our team and the studies built on them generate more and more high dimensional data (time series and parameters). We need new ways to visualize them to both analyze the data and better communicate the results. To design an effective and efficient visualization tool, Melissa will conduct a survey of the various ways to visualize complex data and how to implement these methods/tools based on the rich ecosystem of plotting libraries in Python. Based on our research team needs, Melissa will then select and implement the most suited tool. Melissa will also develop a user-friendly interface that allows the access to model parameter visualization and also experimental descriptor visualization (heat maps) from an available library after pre-processing (filtering and segmentation).

Faculty Supervisor:

Ning Jiang

Student:

Partner:

Université de Technologie de Compiègne

Discipline:

Engineering

Sector:

Education

University:

University of Waterloo

Program: