Computer-assisted beat-pattern analysis and the flagellar waveforms of bovine spermatozoa
Plagued by hurdles in information extraction, handling, and processing, computer-assisted sperm analysis (CASA) systems have typically neglected the complex flagellar waveforms of spermatozoa, despite their defining role in cell motility. Recent developments in imaging techniques and data processing have produced significantly-improved methods of waveform digitisation. Here, we utilise these improvements to demonstrate that near-complete flagellar capture is realisable on the scale of hundreds of cells, and, further, that meaningful statistical comparisons of flagellar waveforms may be readily performed with widely-available tools. Representing the advent of high-fidelity computer-assisted beat-pattern analysis (CABA), we show how such a statistical approach can distinguish between samples using complex flagellar beating patterns rather than crude summary statistics. Dimensionality-reduction techniques applied to entire samples also reveal qualitatively-distinct components of the beat, and a novel data-driven methodology for the generation of representative synthetic waveform data is proposed.