Objective—To investigate whether an accelerometer-based activity monitor could be used in pet dogs to differentiate among and delineate the amount of time spent in activities of differing intensity. Animals—104 dogs. Procedures—For the first phase of the study, each dog (n = 104) wore an accelerometer-based activity monitor and was led through a series of standard activities (recumbency [sedentary], walking, and trotting). Receiver operating characteristic curves were generated to determine the optimal activity counts for predicting whether a dog was sedentary, walking, or trotting. For the second phase of the study, dogs (n = 99) wore an activity monitor on their collars continuously for 14 days at home; intensity of activity for each dog was classified by use of cut points determined on the basis of results obtained during the first phase of the study. Results—Analysis of receiver operating characteristic curves indicated that there was 100% specificity and 100% sensitivity in distinguishing sedentary activity from walking activity and 92% specificity and 92% sensitivity in distinguishing trotting activity from walking activity. Analysis of data collected during the 14-day period at home indicated that dogs were sedentary most of the time (median, 87%; range, 65% to 95%). Conclusions and Clinical Relevance—Counts recorded by an accelerometer-based activity monitor could be used to discriminate effectively among standardized activities in pet dogs. There is potential for use of the method to improve the ability of clinicians and researchers to accurately estimate a pet dog's daily energy requirement.

Objective—To describe daily, hourly, and animal-to-animal effects on lying behavior in steers. Animals—25 crossbred beef steers. Procedures—Wireless accelerometers were used to record behavioral data for cattle housed in a drylot cattle research facility during two 20-day periods (winter 2007 [n = 10 steers] and spring 2008 [15]). Behavioral data were categorized into lying, standing, and walking behaviors for each time point recorded. Logistic regression models were used to determine potential associations between the percentage of time spent lying and several factors, including time (hour) of day, day of trial, and steer. Results—Lying behavior was significantly associated with hour of day, and a distinct circadian rhythm was identified. Steers spent > 55% of the time between 8:00 pm and 4:00 am lying and were most active (<30% lying behavior) during feeding periods (6:00 am to 7:00 am and 4:00 pm to 5:00 pm). Model-adjusted mean percentage of time spent lying was significantly associated with study day and was between 45% and 55% on most (27/40 [67.5%]) days. Lying behavior varied significantly among steers, and mean ± SD percentage of time spent lying ranged from 28.9 ± 6.1 % to 66.1 ± 6.6%. Conclusions and Clinical Relevance—Cattle had distinct circadian rhythm patterns for lying behavior, and percentage of time spent lying varied by day and among steers. Researchers need to account for factors that affect lying patterns of cattle (ie, time of day, day of trial, and individual animal) when performing research with behavioral outcomes.