Classification performance of sEMG and kinematic parameters for distinguishing between non-lame and induced lameness conditions in horses.
| Autor: | St George LB; Research Centre for Applied Sport, Physical Activity and Performance, University of Central Lancashire, Preston, United Kingdom., Spoormakers TJP; Department of Clinical Sciences, Equine Department, Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands., Hobbs SJ; Research Centre for Applied Sport, Physical Activity and Performance, University of Central Lancashire, Preston, United Kingdom., Clayton HM; Department of Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, East Lansing, MI, United States., Roy SH; Delsys/Altec Inc., Natick, MA, United States., Richards J; Allied Health Research Unit, University of Central Lancashire, Preston, United Kingdom., Serra Bragança FM; Department of Clinical Sciences, Equine Department, Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands. |
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| Jazyk: | angličtina |
| Zdroj: | Frontiers in veterinary science [Front Vet Sci] 2024 Apr 02; Vol. 11, pp. 1358986. Date of Electronic Publication: 2024 Apr 02 (Print Publication: 2024). |
| DOI: | 10.3389/fvets.2024.1358986 |
| Abstrakt: | Despite its proven research applications, it remains unknown whether surface electromyography (sEMG) can be used clinically to discriminate non-lame from lame conditions in horses. This study compared the classification performance of sEMG absolute value (sEMGabs) and asymmetry (sEMGasym) parameters, alongside validated kinematic upper-body asymmetry parameters, for distinguishing non-lame from induced fore- (iFL) and hindlimb (iHL) lameness. Bilateral sEMG and 3D-kinematic data were collected from clinically non-lame horses ( n = 8) during in-hand trot. iFL and iHL (2-3/5 AAEP) were induced on separate days using a modified horseshoe, with baseline data initially collected each day. sEMG signals were DC-offset removed, high-pass filtered (40 Hz), and full-wave rectified. Normalized, average rectified value (ARV) was calculated for each muscle and stride (sEMGabs), with the difference between right and left-side ARV representing sEMGasym. Asymmetry parameters (MinDiff, MaxDiff, Hip Hike) were calculated from poll, withers, and pelvis vertical displacement. Receiver-operating-characteristic (ROC) and area under the curve (AUC) analysis determined the accuracy of each parameter for distinguishing baseline from iFL or iHL. Both sEMG parameters performed better for detecting iHL (0.97 ≥ AUC ≥ 0.48) compared to iFL (0.77 ≥ AUC ≥ 0.49). sEMGabs performed better (0.97 ≥ AUC ≥ 0.49) than sEMGasym (0.76 ≥ AUC ≥ 0.48) for detecting both iFL and iHL. Like previous studies, MinDiff Poll and Pelvis asymmetry parameters (MinDiff, MaxDiff, Hip Hike) demonstrated excellent discrimination for iFL and iHL, respectively (AUC > 0.95). Findings support future development of multivariate lameness-detection approaches that combine kinematics and sEMG. This may provide a more comprehensive approach to diagnosis, treatment, and monitoring of equine lameness, by measuring the underlying functional cause(s) at a neuromuscular level. Competing Interests: SR is employed by Delsys/Altec Inc., the manufacturers of the sEMG sensors used in this study. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2024 St. George, Spoormakers, Hobbs, Clayton, Roy, Richards and Serra Bragança.) |
| Databáze: | MEDLINE |
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