Comparison of activity trackers in estimating canine behaviors

• DOI: 10.1080/01691864.2024.2343080
• Publication Date: 2024-04-28T17:40:00Z
• Authors: Miiamaaria V. Kujala; Anna Valldeoriola...; Sanni Somppi; Heini Törnqvist; Leena Inkilä; Aija Koskela; Anne Myller; Heli Väätäjä; Poika Isokoski; Päivi Majaranta; Veikko Surakka; Outi Vainio; Antti Vehkaoja
• Keywords: School of Wellbeing; aktiivisuus; behavioral differentiation; activity tracking; companion dog; 610; Companion dog; monitorointi; lemmikkieläimet; koira; 113; 213; Veterinary science; accelerometer; käyttäytymisanalyysi; Hyvinvoinnin tutkimuksen yhteisö; seuranta; liikeanalyysi; kiihtyvyys

peerReviewed<br/>Classifying behavior by tracking acceleration has received increased interest lately. Here, we evaluated the performance of three commercial activity trackers in differentiating seven dog behaviors. Adult companion dogs (N = 70) performed still (lying, sitting, standing) and dynamic (walking, sniffing, trotting, playing) tasks, while wearing ActiGraph GT9X Link, Kaunila and FitBark devices placed on the neck collar and ActiGraph GT9X Link placed on the back. Each task was performed for 3 min within a session and repeated in two sessions; the behaviors were confirmed from video recordings. Activity scores of devices were calculated as median values for behavioral differentiation, and as minute-based values for inter-device correlations and cutoff analysis. Measurements of all devices correlated with each other, and median activity scores of all devices − unaffected by dog age, weight or sex − differentiated the still from dynamic behaviors. Dynamic behaviors were also differentiated from each other, with exception of walking vs. sniffing by back-placed ActiGraph GT9X and Kaunila. The definition of cutoffs between behaviors varied from moderate to high accuracy; defined cutoffs for standing and walking were the least accurate. The classification performance of the cutoffs had an accuracy of 80% in all the devices; thus, they performed reasonably well in classifying these behaviors.<br/>