title: Automated Gait Analysis Through Hues and Areas (AGATHA): A Method to Characterize the Spatiotemporal Pattern of Rat Gait.
abstract: While rodent gait analysis can quantify the behavioral consequences of disease, significant methodological differences exist between analysis platforms and little validation has been performed to understand or mitigate these sources of variance. By providing the algorithms used to quantify gait, open-source gait analysis software can be validated and used to explore methodological differences. Our group is introducing, for the first time, a fully-automated, open-source method for the characterization of rodent spatiotemporal gait patterns, termed Automated Gait Analysis Through Hues and Areas (AGATHA). This study describes how AGATHA identifies gait events, validates AGATHA relative to manual digitization methods, and utilizes AGATHA to detect gait compensations in orthopaedic and spinal cord injury models. To validate AGATHA against manual digitization, results from videos of rodent gait, recorded at 1000 frames per second (fps), were compared. To assess one common source of variance (the effects of video frame rate), these 1000 fps videos were re-sampled to mimic several lower fps and compared again. While spatial variables were indistinguishable between AGATHA and manual digitization, low video frame rates resulted in temporal errors for both methods. At frame rates over 125 fps, AGATHA achieved a comparable accuracy and precision to manual digitization for all gait variables. Moreover, AGATHA detected unique gait changes in each injury model. These data demonstrate AGATHA is an accurate and precise platform for the analysis of rodent spatiotemporal gait patterns.
authors.affiliation: J Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, 1275 Center Drive, Biomedical Sciences Building, JG56, Gainesville, FL, 32610, USA.
authors.forename: Heidi E
authors.initials: HE
authors.lastname: Kloefkorn
authors.affiliation: J Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, 1275 Center Drive, Biomedical Sciences Building, JG56, Gainesville, FL, 32610, USA.
authors.forename: Travis R
authors.initials: TR
authors.lastname: Pettengill
authors.affiliation: Department of Physical Therapy, University of Florida, Gainesville, FL, USA.
authors.forename: Sara M F
authors.initials: SM
authors.lastname: Turner
authors.affiliation: Department of Physical Therapy, University of Florida, Gainesville, FL, USA.
authors.forename: Kristi A
authors.initials: KA
authors.lastname: Streeter
authors.affiliation: Department of Physical Therapy, University of Florida, Gainesville, FL, USA.
authors.forename: Elisa J
authors.initials: EJ
authors.lastname: Gonzalez-Rothi
authors.affiliation: Department of Physical Therapy, University of Florida, Gainesville, FL, USA.
authors.forename: David D
authors.initials: DD
authors.lastname: Fuller
authors.affiliation: J Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, 1275 Center Drive, Biomedical Sciences Building, JG56, Gainesville, FL, 32610, USA. kyle.allen@bme.ufl.edu.
authors.forename: Kyle D
authors.initials: KD
authors.lastname: Allen
mesh_terms: D000818:Animals; D005684:Gait; D006614:Hindlimb / Q000503:physiopathology*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D051381:Rats; D013119:Spinal Cord Injuries / Q000503:physiopathology*; D014741:Video Recording
keywords: Automated gait analysis; Behavioral analysis; Meniscus; Osteoarthritis; Rodent; Spatiotemporal gait patterns; Spinal cord contusion; Spinal cord injury