Evaluating Compensatory Lameness – Breaking Down the Algorithms, Part 2

In last month’s feature article, “Evaluating Compensatory Lameness – Breaking Down the Algorithms”, we described the interpretation assistance algorithms that drive the compensatory lameness AIDE comments on the straight line report. In case you missed it, you can review that article HERE. As a brief reminder, the AIDE statements that offer a suggestion of a primary lameness in a multiple limb lameness scenario are based on known compensatory lameness patterns, also taking into consideration the consistency, or evidence, (stride-by-stride variability) and amplitudes of each lameness.  Each lameness is assigned a weight, based on the evidence score and the amplitude score.  These weights are factored into the algorithm that may trigger the suggestion of a primary lameness when a compensatory pattern is identified.

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10 Common Data Collection Mistakes

1) Putting the RF sensor on upside down.

This most commonly occurs when the pastern wrap is applied with the sensor already within the pouch. The user may fail to recognize that the wrap is applied with the sensor pouch upside down. Always check that the RF sensor is positioned correctly, on the dorsal aspect of the pastern, with the label in its proper orientation when viewing straight on, and the LED blinking on the lateral side of the limb (in Gen 3 and newer sensors). An upside-down RF sensor will result in opposite of true results (for both forelimb and hind limb).

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