In this study, we analyze Mucociliary Transport (MCT) by measuring the magnitude and identifying regions of ciliary beats using high-frame-rate microscopic videos. Our methodology, integrating Dense Optical Flow, Connected Component Labeling (CCL), Butterworth Filter, and Fast Fourier Transform (FFT), captures ciliary movement and magnitude. We focus on region extraction, quantification of ciliary activity, and classification of power and recovery strokes in CBF, crucial for evaluating MCT efficiency. Our approach was able to extract the ciliary region semi-automatically. Despite dataset challenges and limited ground truth, our approach shows a promising result for ciliary dynamics research and medical diagnostics, particularly for diagnosing Primary Ciliary Dyskinesia (PCD) patients, demonstrating its potential impact in medical fields.