Little is known about mite gait, but it has been suggested that there could be greater variation in locomotory styles for arachnids than insects. TheVarroa destructormite is a devastating ectoparasite of the honeybee. We aim to automatically detectVarroa-specific signals in long-term vibrational recordings of honeybee hives and additionally provide the first quantification and characterisation ofVarroagait through the analysis of its unique vibrational trace. These vibrations are used as part of a novel approach to achieve remote, non-invasiveVarroamonitoring in honeybee colonies, requiring discrimination between mite and honeybee signals. We measure the vibrations occurring in samples of freshly collected capped brood-comb, and through combined critical listening and video recordings we build a training database for discrimination and classification purposes. In searching for a suitable vibrational feature, we demonstrate the outstanding value of two-dimensional-Fourier-transforms in invertebrate vibration analysis. Discrimination was less reliable when testing datasets comprising ofVarroawithin capped brood-cells, whereVarroainduced signals are weaker than those produced on the cell surface. We here advance knowledge ofVarroavibration and locomotion, whilst expanding upon the remote detection strategies available for its control.