Development and validation of a novel pedometer algorithm to quantify extended characteristics of the locomotor behavior of dairy cows

Alsaaod, Maher; Niederhauser, J J; Beer, Gian; Zehner, N; Schüpbach, Gertraud; Steiner, Adrian (2015). Development and validation of a novel pedometer algorithm to quantify extended characteristics of the locomotor behavior of dairy cows. Journal of dairy science, 98(9), pp. 6236-6242. American Dairy Science Association 10.3168/jds.2015-9657

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Behavior is one of the most important indicators for assessing cattle health and well-being. The objective of this study was to develop and validate a novel algorithm to monitor locomotor behavior of loose-housed dairy cows based on the output of the RumiWatch pedometer (ITIN+HOCH GmbH, Fütterungstechnik, Liestal, Switzerland). Data of locomotion were acquired by simultaneous pedometer measurements at a sampling rate of 10 Hz and video recordings for manual observation later. The study consisted of 3 independent experiments. Experiment 1 was carried out to develop and validate the algorithm for lying behavior, experiment 2 for walking and standing behavior, and experiment 3 for stride duration and stride length. The final version was validated, using the raw data, collected from cows not included in the development of the algorithm. Spearman correlation coefficients were calculated between accelerometer variables and respective data derived from the video recordings (gold standard). Dichotomous data were expressed as the proportion of correctly detected events, and the overall difference for continuous data was expressed as the relative measurement error. The proportions for correctly detected events or bouts were 1 for stand ups, lie downs, standing bouts, and lying bouts and 0.99 for walking bouts. The relative measurement error and Spearman correlation coefficient for lying time were 0.09% and 1; for standing time, 4.7% and 0.96; for walking time, 17.12% and 0.96; for number of strides, 6.23% and 0.98; for stride duration, 6.65% and 0.75; and for stride length, 11.92% and 0.81, respectively. The strong to very high correlations of the variables between visual observation and converted pedometer data indicate that the novel RumiWatch algorithm may markedly improve automated livestock management systems for efficient health monitoring of dairy cows.

Item Type:

Journal Article (Original Article)

Division/Institute:

05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) > Veterinary Public Health Institute
05 Veterinary Medicine > Research Foci > Veterinary Public Health / Herd Health Management
05 Veterinary Medicine > Department of Clinical Veterinary Medicine (DKV)
05 Veterinary Medicine > Department of Clinical Veterinary Medicine (DKV) > Clinic for Ruminants
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH)

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Alsaaod, Maher; Beer, Gian; Schüpbach, Gertraud and Steiner, Adrian

Subjects:

500 Science > 590 Animals (Zoology)
600 Technology > 610 Medicine & health
600 Technology > 630 Agriculture

ISSN:

0022-0302

Publisher:

American Dairy Science Association

Language:

English

Submitter:

Patrik Zanolari

Date Deposited:

11 Jan 2016 12:17

Last Modified:

17 Jan 2016 17:35

Publisher DOI:

10.3168/jds.2015-9657

PubMed ID:

26142842

Uncontrolled Keywords:

accelerometer; dairy cow; behavior; locomotion; walking

BORIS DOI:

10.7892/boris.74489

URI:

https://boris.unibe.ch/id/eprint/74489

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