Gait Analysis Graphical User Interface Files

hsGUI Package:

Software Platform: 
Matlab 2014a with image processing package

Software Authorship: 
This code was developed by BA Ellison and A Worley under supervision of V VanderHorst and compiled by A Kirby (4/2023).

Role in Research: 
This code was employed to extract gait metrics which were then used to validate analytical approaches to quantify changes in gait style through gait signatures. These analytical approaches can be found in:
1. Broom L, Ellison BA, Worley A, Wagenaar L, Sorberg E, Ashton C, et al. A translational approach to capture gait signatures of neurological disorders in mice and humans. Sci Rep. 2017;7(1):3225.
2. Broom L, Worley A, Gao F, Hernandez LD, Ashton CE, Shih LC, et al. Translational methods to detect asymmetries in temporal and spatial walking metrics in parkinsonian mouse models and human subjects with Parkinson’s disease. Sci Rep. 2019;9(2437).

Raw Data: 
This custom software package was written to display movies taken of mice walking on a plexiglass runway with a mirror at a 45 degree angle underneath. The video is captured with the animal walking horizontally on the plexiglass surface so that both the lateral view and the view from underneath the animal are captured simultaneously. The videos are captured at 120 frames per second and stored in .AVI format.

Software Description:
The program hs initiates a graphical interface to score bouts of gait that are pre-identified in the video. After starting the program, the user selects a video and then is prompted to enter time ranges that contain bouts of gait to be scored. The video load and initial frame displays for the purpose of spatial calibration. The user then manually indicates the long axis of the walkway, and locates points on the apparatus that are a fixed 5 cm distance apart. Once this preparation is complete, scoring begins. First, a subset of video frames corresponding to the first time range identified by the program is then loaded. The interface allows navigating forward and backwards through the loaded frames to identify the frames in which a paw contacts the plexiglass surface and those in which the paw lifts from the surface and the swing phase of gait begins. After identifying a relevant frame, the user clicks on the paw and the time corresponding to this frame and the spatial location of the paw are saved. The entire bout of gait (animal walking from one side to the other) is captured; then another paw is selected and the process is repeated until all four paws have been captured for the entire bout of gait. The user can enter whether a particular bout of gait was cued and how, as well as subjective information about the characteristics of the gait. Once all four paws are scored, the program will advance to the next bout of gait until all pre-selected bouts have been completed. When the program exits this information is saved in a file.

hs.m
- ChooseVid.m
- hsFramelist2.m/hsFramelist2.fig
- hsGUI.m/hsGUI.fig
--- activateCallbacks.m
--- uicomponent.m
--- deleteLastStep.m
--- plotLimbLines.m
--- plotSwings.m
--- recordSwing.m
--- saveTrial.m
--- dateLookup2.m
--- mat2csv.m

The program write2gp takes the raw scoring data produced by hs and extracts commonly used gait parameters, which are exported in the form of a matlab variable.

write2gp.m
- arrangeGP.m
---getgait.m

The program newPawsAnalyze takes input arguments to selecting data (including animal, date of behavior, and information about an individual bout of gait such as environmental cues) and extracts spatial and temporal parameters into a Matlab structure.

newPawsAnalyze.m