Such analyses benefit greatly from computer vision techniques, which can accurately and efficiently monitor complex locomotor characteristics. Until recently, the quantification of zebrafish behavior was performed manually, making it vulnerable to human error and incorrect data interpretation, thereby reducing the validity of an experiment. While visual monitoring of behavior is time-consuming and prone to subjective variation, the development of dedicated computer vision techniques is desired in exploiting the information contained in the acquired image and video data. Computerized video analytic tools that analyze zebrafish movements provide standardized observation of behavioral measurements and reduce human errors. Video analytic technology helps fast and objective quantification of zebrafish behavior. These tools also provide basic measurements which cannot be scored manually. However, these systems analyze the fish only as a point and cannot quantify body wave kinematics of swimming. Several studies have been developed to examine details of zebrafish body waving in video Fluconazole recorded with high frame rates. However, a majority of these studies have focused on larval locomotion, less is known for adult zebrafish, where the escape response of wild-type zebrafish and transgenic zebrafish have been studied. In this study, we present a video analytic tool that is able to provide precise quantitative measurements of behavioral abnormalities for detecting effects on muscular or Bitopertin nervous system function. The tool analyses the movement behavior of a single adult Zebrafish in an automated and batch manner. Two new body-waving parameters are presented that expand the currently available toolbox of zebrafish motion measurements. We demonstrate the capability of the developed video analytic tool to distinguish wild-type zebrafish from transgenic lines that express disease-associated mutations in CLCN1. The mutant CLCN1 channels affect zebrafish body curvature and tail offset as a result from effects on muscle function.The zebrafish model could provide additional insights into myotonia congenita pathogenesis and, combined with the video analytic tools, be used for automated small molecule screening and monitoring of disease progression.