IMU Movement Pattern Data Analysis

If have raw time–series output from a few Inertial Measurement Unit, could you turne into clear insights about how an object (or person) is moving. The goal is straightforward: monitor and characterise movement patterns so I can spot changes over time and build a baseline for future comparisons. You will decide on the most appropriate combination of acceleration, gyroscopic and, if useful, magnetic-field signals; I’m open to any proven approach that highlights trends, periodicity or relevant statistics in the data. Feel free to work in Python (pandas, NumPy, SciPy, scikit-learn) or MATLAB—whichever you are fastest with—as long as the analysis can be rerun easily on new datasets. Deliverables • A well-commented script or notebook that loads my CSV/JSON log, processes it, and outputs key movement metrics. • Visualisations (plots or dashboards) that make the patterns easy to read at a glance. • A concise write-up explaining your methods and how to interpret the results. Clean, reproducible work is the priority, so please keep intermediate steps transparent and share any assumptions you make. If you have experience with gait, posture, activity recognition or similar IMU projects, that will be a plus—let me know in your proposal.

Projekt-ID: 40069097