Article Details: Received: 2020-10-26 | Accepted: 2020-11-27 | Available online: 2021-01-31 https://doi.org/10.15414/afz.2021.24.mi-prap.135-139 The purpose of the work was aimed at determining changes in locomotion activity of dairy cows with healthy claws, as opposed to cows suffering from claw disorders. To achieve this goal, Heatime RuminAct technical equipment was used. Data gathering took place at the dairy farm of University of Agriculture in Nitra, where locomotion activity was measured via Heatime RuminAct hardware with DataFlowTMII software. This data came from 87 dairy cows, whose locomotion activity was monitored during a period of 21 days. This period consisted of 10 days of monitoring before the claw trimming, monitoring during the day of the trimming, and afterwards, another 10 days of monitoring after the trimming was complete. Units of locomotion activity in 24 hours (u.24h -1 ) were used to formulate the locomotion activity of the dairy cows. Health conditions of claws of the dairy cows were recorded and based on the presence of claw disorders, the cows were divided into two groups - cows with observed claw disorders formed a group of 33 cows, and cows exhibiting no claw disorder related symptoms formed a group of 54 cows. Conclusions based on results from the data gathered confirm a crucial difference in locomotion activity between healthy cows and cows afflicted by claw disorders. Keywords: dairy cow, Heatime RuminAct, locomotion activity, claw health, claw disorders References Anil, L. et al. (2005). Pain detection and amelioration in animals on the farm: issues and options. Journal of Applied Animal Welfare Science , 8, 261-278. https://doi.org/10.1207/s15327604jaws0804_3 Beer, G. et al. (2016). Use of extended characteristics of locomotion and feeding behavior for automated identification of lame dairy cows. PLoS One , 11, e0155796. https://doi.org/10.1371/journal.pone.0155796 Bruijnis, M. R. et al. H. (2010). Assessing economic consequences of foot disorders in dairy cattle using a dynamic stochastic simulation model. Journal of Dairy Scienc e, 93(6), 2419-2432. https://doi.org/10.3168/jds.2009-2721 Flower, F. C. et al.(2006). Effect of hoof pathologies on subjective assessments of dairy cow gait. Journal of Dairy Science , 89, 139-146. https://doi.org/10.3168/jds.S0022-0302(06)72077-X Hudson, C. et al. (2008) H. Recognition and management of pain in cattle. In Practice, 30, 126-134. https://doi.org/ 10.1136/inpract.30.3.126 King, M. T. M. et al. (2017). Cow-level associations of lameness, behavior, and milk yield of cows milked in automated systems. Journal of Dairy Science , 100(6), 4818-4828. https://doi.org/10.3168/jds.2016-12281 Nechanitzky, K. et al. (2016). Analysis of behavioral changes in dairy cows associated with claw horn lesions. Journal of Dairy Science , 99(4), 2904-2914. https://doi.org/10.3168/jds.2015-10109 O'Callaghan, K. A. et al. (2003). Subjective and objective assessment of pain and discomfort due to lameness in dairy cattle. Animal Welfare , 12, 605-610. O'Leary, N. W. et al. (2020). Invited review: Cattle lameness detection with accelerometers. Journal of Dairy Science , 103(5), 3895-3911. https://doi.org/10.3168/jds.2019-17123 Shepley, E. et al. (2017). Validation of the ability of a 3D pedometer to accurately determine the number of steps taken by dairy cows when housed in tie-stalls. Agriculture (Basel), 7, 53. https://doi.org/10.3390/agriculture7070053 Stoddard, G. C. and Cramer, G. (2017). A Review of the Relationship Between Hoof Trimming and Dairy Cattle Welfare. Veterinary Clinics of North America: Food Animal Practice , 33(2), 365-375. https://doi.org/10.1016/j.cvfa.2017.02.012 Strapak, P. et al. (2013). Cattle Breeding . Nitra: Slovak University of Agriculture. In Slovak. Thorup, V. M. et al. (2015). Lameness detection via leg-mounted accelerometers on dairy cows on four commercial farms. Animal , 9, 1704-1712. https://doi.org/10.1017/S1751731115000890 Weigele, H. C. et al. (2018). Moderate lameness leads to marked behavioral changes in dairy cows. Journal of Dairy Science , 101(3), 2370-2382. https://doi.org/10.3168/jds.2017-13120