The FAST software package and all documentation can be downloaded from www.flagellarCapture.com. Summary 1 Flagella are critical across all eukaryotic life, and the human sperm 2 flagellum is crucial to natural fertility. Existing automated sperm di-3 agnostics (CASA) rely on tracking the sperm head and extrapolating 4 measures. We describe fully-automated tracking and analysis of flag-5 ellar movement for large cell numbers. The analysis is demonstrated 6 on freely-motile cells in low and high viscosity fluids, and validated on 7 published data of tethered cells undergoing pharmacological hyperac-8 tivation. Direct analysis of the flagellar beat reveals that the CASA 9 measure 'beat cross frequency', does not measure beat frequency. A 10 new measurement, track centroid speed, is validated as an accurate 11 differentiator of progressive motility. Coupled with fluid mechanics 12 codes, waveform data enables extraction of experimentally intractable 13 quantities such as energy dissipation, disturbance of the surrounding 14 medium and viscous stresses. We provide a powerful and accessible 15 research tool, enabling connection of the cell's mechanical activity to 16 its motility and effect on its environment. 17 Introduction 18About 100 million men worldwide are suggested to be subfertile (Inhorn and 19 Patrizio, 2015), but for many of them an accurate diagnostic cause remains 20 elusive. The ability of sperm to successfully migrate through the female re-21 productive tract is key to natural fertilisation, however current techniques for 22 assessing sperm motility lack diagnostic power and mechanistic insight. The 23 heterogeneity of human sperm requires tools that can acquire and analyse 24 2 (2018) and associated special issue). Such systems are widely used for vet-25 erinary work and in domestic animal breeding, conservation, and toxicology 26 (Amann and Waberski, 2014), but have not yet made the breakthrough into 27 routine clinical usage. The reasons for this have been discussed elsewhere 28 (Gallagher et al., 2018b). 29 Standard CASA systems produce a motility assessment from the track of 30 the head movement, however this does not enable causative or mechanistic 31 insight because it lacks detail on the movement of the flagellum. Knowledge 32 of this beat could provide hitherto untapped information for the estimation 33 of non-visible attributes such as the contribution of different metabolic path-34 ways, and modulation in response to the physical and biochemical environ-35 ments (Ooi et al., 2014). The capability to capture flagellar movements and 36 associated mechanistic insights has broader applicability in the life sciences 37 including the role of cilia in embryonic development (Smith et al., 2019), 38 swimming of multiflagellate microorganisms (Wan and Goldstein, 2018), the 39 use of high-speed holographic microscopy to image the flagellar waveforms 40 of malaria parasites (Wilson et al., 2013), and even the design of hybrid 41 bio-robots for biomedical applications (Xu et al., 2017).42 The use of comp...