Electrode positioning in the horse: towards standardisation of surface EMG measurements

Surface electromyography (sEMG) is a well-established method in human gait analysis, and its application has extended towards the equine field in the past decades. However, methodological consensus regarding electrode positioning is lacking, resulting in different user methodologies, hampering study comparison and repeatability. This study investigated the standardisation of bipolar electrode positioning to measure muscle activity in horses during dynamic contractions. Ultrasound scans were made of three muscles (Triceps Brachii caput longum (TB), Longissimus Dorsi (LD), and Semitendinosus (ST)) of six horses to determine the muscle borders and fibre direction. Linear arrays of approximately ten electrodes (4 mm diameter, 20 mm inter-electrode distance) were placed on the clipped and cleaned skin, parallel to the muscle fibre direction. The middle of the array was always placed at 50% between two anatomical landmarks chosen near (one of ) the origins and insertions of the respective muscle. Data were collected (SAGA® TMSi, 4,000 Hz) for one minute at trot on a treadmill. The root mean square (RMS) values, innervation zone (IZ) location and presence of crosstalk were determined to evaluate electrode positions. The optimal positions were at 40-49 and 32-45% between the used anatomical landmarks for TB and ST respectively. Electrodes positioned within the thoracic region of the LD recorded higher, i.e. better, RMS values compared to electrodes in the lumbar region, though results were similar regarding IZ location and presence of crosstalk. The proposed positions may serve as a standardised reference for bipolar electrode placement to measure sEMG in horses during dynamic contractions.Effect of body position on a 3-dimensional scanning assessment of muscle massA. Borer-Matsui1, G.C. Donnelly2 and S. Valberg11Michigan State University, Large Animal Clinical Sciences, 736 Wilson Rd, 48824, East Lansing MI, USA, 2University of California, Davis, Department of Population Health and Reproduction, One Shields Drive, 95616, Davis CA, USA; [email protected] performance relies on well-developed musculature which has been difficult to accurately measure. We recently devised a 3-dimensional photonic scan to capture body volume (V) as a proxy for muscle mass validated in horses with 4 hooves square, a difficult stance to achieve. The purpose of this study was to determine the effect of modest differences in body position on measurement of body V. Anatomic markers were placed on 8 horses positioned with; 4 hooves square; neck turned ⌁25°; head raised mean 17 cm; one hind hoof (HH) anterior offset ⌁15 cm; a front and opposite HH ⌁15 cm offset (n=7); one HH resting. A handheld Occipital Structure Sensor scanner connected to an iPad and Skanect and Materialise 3-Matic programs were used to capture V in specific body sectors delineated by anatomic markers. Volume of back and hindquarter sectors standing square were compared to various positions using ANOVA (

Quantitative lameness assessment in the horse based on upper body movement symmetry: The effect of different filtering techniques on the quantification of motion symmetry

Quantitative gait analysis in horses is rapidly gaining importance, both clinically and in research. The number of available systems is increasing, but the methods of signal analysis differ between systems and research groups. Our objectives are to describe and evaluate the effects of different methods of signal analysis for processing of data from equine kinematic gait analysis. To this end, we use theoretical signals based on previously published work, followed by the evaluation of the performance of each technique using real data from horses with induced lameness. Two infinite impulse response (IIR), high-pass filters (Butterworth and Chebyshev), a signal decomposition method and a moving average filtering technique were evaluated. First, we describe methods to fine-tune each filter to the optimal settings based on residual analysis. Second the performance of each filter is evaluated based on differences in calculated symmetry parameters from horses with induced lameness. We show that optimisation of filtering techniques is crucial when processing signals used for objective lameness quantification. Improper selection of the cut-off frequency for IIR filters can result in false negative results (average values above or below predefined reference values). The IIR Butterworth filter and the signal decomposition method achieved the best reduction of unwanted signal components. Knowledge of the available filtering techniques is a pre-requisite for adequate signal processing of gait data from quantitative analysis systems in horses