Python 3 toolbox for analysing FIM data:

1. Read .csv files produced by FIMTrack
2. Merge individual files into experiments
3. Add experiments into collections
4. Analyse across experiments

FIMTrack CSV files contain a large selection of primary, secondary and tertiary features (position, area, movement direction, length, etc). PyFIM adds a few high-level analyses based on MatLab scripts by Dimitri Berh.

• pause-turn frequency
• stop frequency
• bending strength
• head bend frequency
• peristalsis frequency
• peristalsis efficiency

pyFIM is on ReadTheDocs

Big thanks to Dimitri Berh, Benjamin Risse, Nils Otto and Christian Klämbt for sharing their MatLab code.

Risse B, Berh D, Otto N, Klämbt C, Jiang X. FIMTrack: An open source tracking and locomotion analysis software for small animals. PLoS Computational Biology. 2017;13(5):e1005530. doi:10.1371/journal.pcbi.1005530.

Risse B, Otto N, Berh D, Jiang X, Klämbt C. FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis. Journal of Visualized Experiments : JoVE. 2014;(94):52207. doi:10.3791/52207.

Risse B, Thomas S, Otto N, et al. FIM, a Novel FTIR-Based Imaging Method for High Throughput Locomotion Analysis. PLoS ONE. 2013;8(1):e53963. doi:10.1371/journal.pone.0053963.