Open Access
CC BY 4.0 · VCOT Open 2023; 06(S 01): A1-A11
DOI: 10.1055/s-0043-1768887
Canine Scientific/Clinical Abstract Podium Sessions

Mobile Gait Analysis: Evaluating Phone-Based Applications for Kinematic Analysis in Dogs

C. E. Zelaya-Nunez
1   Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, Missouri, United States
,
D. T. Graham
1   Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, Missouri, United States
,
R. A. Seabolt
1   Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, Missouri, United States
,
B. T. Torres
1   Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, Missouri, United States
› Author Affiliations
 
 

    Introduction: Currently, there is little research into mobile phone-based kinematic applications in dogs. This study compares kinematic data from phone-based applications to computer-based software. We hypothesized that there would be no significant differences between applications.

    Materials and Methods: Thoracic and pelvic limb sagittal plane data were obtained from five normal dogs utilizing two phone-based applications (Dartfish Express, OnForm) and a computer-based application (Kinovea). Dogs were collected at a walk and trot and recorded with an iPhone-11 at 60FPS. Data were compared with analysis of variance and a Tukey test. Significance was p less than 0.05.

    Results: Flexion – at a trot, there were no differences between applications. At a walk, differences were only found in the shoulder. Extension – at a trot, differences were only found in the stifle, hip, elbow and carpus. At a walk, differences were only found in the stifle and carpus. Range of motion – at a trot, differences were only found in the stifle, hip, elbow, shoulder and carpus. At a walk, differences were only found in the shoulder, carpus, hip, stifle and tarsus.

    Discussion/Conclusion: Our hypothesis was rejected, and differences were found between applications. These findings may result from differences in programmes, equipment or investigators. The smaller phone touchscreen may impact marker identification. Additionally, the phone-based applications require static measurements and rely on correctly identifying the frame-of-interest. Conversely, the computer-based software employs automated maker-tracking. Interestingly, there were fewer differences between the phone-based applications and measurements were generally lower – indicating challenges in isolating the extremes of joint motion with phones. Further research is warranted.

    Acknowledgments:

    There was no proprietary interest or funding provided for this project.


    No conflict of interest has been declared by the author(s).

    Publication History

    Article published online:
    01 May 2023

    © 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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