Implementation of anxiety evaluation systems in laboratory mice using digital image processing
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Abstract
Currently, there are several techniques to evaluate anxiolytic behavior in laboratory animals since their behavior is very similar to that of humans. Such techniques include manual and observational methods, where the evaluator must carefully observe the entire experiment and document each of the events of interest made by the mouse or acquire electronic equipment that fulfills this function. However, the last option could be expensive. This article proposes the design and implementation of two low-cost anxiety assessment devices (Elevated Plus Maze and Light-Dark Box) using digital image processing, which, after the validation of the operation, delivers results automatically through an application developed in Matlab. The results provided by the application coincide with those that an observer would obtain manually and visually, facilitating the tasks of the evaluator and reducing the possible human errors and ambiguity existing in manual tests.
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