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.

Functional Measures of Grip Strength and Gait Remain Altered Long-Term in a Rat Model of Post-Traumatic Elbow Contracture

“…associated hardware and open-source analysis software were used to acquire spatiotemporal gait data [17,23,24] (additional information available online 1 ). Briefly, the arena is an enclosed, Fig.…”

“…During gait collection, animals voluntarily explored (i.e., were not forced or prompted) the arena at selfselected velocities while being recorded with a high-speed video camera (FASTCAM Mini UX50, Photron, Tokyo, Japan) at 500 frames per second (fps). Utilizing similar exclusion criteria as previous studies using this techniques [15,23], trials with constant walking speed and containing at least three complete gait cycles were collected on injured and control animals. Based on a previous work, a minimum of five trials (collected on at least eight animals at 500 fps) were deemed necessary to ensure sufficient sensitivity to detect gait changes of 1% in symmetry and duty factor and 0.25 cm in stride length [23].…”

“…Utilizing similar exclusion criteria as previous studies using this techniques [15,23], trials with constant walking speed and containing at least three complete gait cycles were collected on injured and control animals. Based on a previous work, a minimum of five trials (collected on at least eight animals at 500 fps) were deemed necessary to ensure sufficient sensitivity to detect gait changes of 1% in symmetry and duty factor and 0.25 cm in stride length [23]. Because of postprocessing exclusion criteria (color thresholding errors or varying velocity), attempts were made to collect in excess of 10 trials per animal per time point.…”

“…Additionally, a recent study evaluated gait changes due to elbow contracture in a murine model [22]; however, in this study animals were only evaluated at a single time point for a single gait parameter. In this study, spatiotemporal gait compensations were investigated longitudinally in our rat PTJC model using an open source, fully automated technique validated to detect rodent gait abnormalities with high sensitivity [23,24]. We hypothesized (1) the unilateral, persistent range of motion loss observed previously [7] would be manifested as an asymmetric gait with imbalanced duty factor and reduced grip strength when compared to uninjured controls, and (2) metrics of gait and grip strength would partially recover over time but not reach levels of control animals.…”

Learning two programming languages in one semester does not adversely affect undergraduate biomedical engineering student performance

“…), this trend is likely to accelerate even more in the coming future. In addition, computer programing has become an essential part of data analysis [2][3][4] and simulation 5,6 in biomedical research. As interacting with computing-enable devices becomes easier and more prevalent, it is possible that engineers will graduate with the ability to quickly navigate user interfaces but without a detailed, theoretical knowledge of computing fundamentals.…”