A new approach to the comprehensive assessment of problematic behavior of companion dogs. Message 1

The article proposes a new comprehensive method for assessing the problematic behavior of companion dogs. The aim of the study is to develop a system for the comprehensive analysis of dog behavior using behavioral markers, blank tests, wearable devices and neural networks. The method involves the sequential execution of a series of test samples and blank tests. To test and implement the method in accordance with the "Open Field Test" paradigm, a landfill has been prepared, within which, using two analog video cameras and a wearable accelerometer, the free behavior of a dog at the landfill is recorded as part of a series of experimental tests. The tests included familiarization with the training ground, typical behavior for this dog when interacting with the owner and a stranger, being alone, reactions to loud and quiet sounds, and ECG recording. Putting on an accelerometer and the dog's reaction to a thermal imaging camera were used as separate small tests. The owners separately filled out questionnaire blank tests to analyze the anamnesis of life and behavior of dogs outside the landfill. During the recording, minor behavioral signs of anxiety behavior were analyzed using a developed checklist. The analysis of the obtained data was carried out both manually (blank questionnaires, small behavioral signs) and in semi-automated mode (accelerometry, video recordings and thermography). During the testing process, the advantages and limitations of each of the methods used in the context of the approach were identified, and the effectiveness of its use – in whole or in separate samples – for evaluating the behavior of companion dogs, working and service dogs was shown. The results are applicable for monitoring the behavior of companion dogs, working and service dogs, analyzing possible correlates of anxious and aggressive behavior, in zoopsychologic and ethological studies.

1. Boyd, C. Mortality resulting from undesirable behaviours in dogs aged under three years attending primary-care veterinary practices in England / C. Boyd, S. Jarvis, P. McGreevy, et al // Animal Welfare. – 2018. – 27(3). – C. 251-262. DOI 10.7120/09627286.27.3.251

2. Bruno, E.A. Global positioning system derived performance measures are responsive indicators of physical activity, disease and the success of clinical treatments in domestic dogs / E.A. Bruno, J.W. Guthrie, S.A. Ellwood, R.J. Mellanby, D.N. Clements // PLoS One. – 2015. – 10(2). – e0117094. –

3. DOI 10.1371/journal.pone.0117094.

4. Dreschel, N. A. The effects of fear and anxiety on health and lifespan in pet dogs / N.A. Dreschel // Applied Animal Behaviour Science. – 2010. – 125(3–4). – C. 157-162 DOI 10.1016/j.applanim.2010.04.003.

5. Gácsi, M. Human analogue safe haven effect of the owner: behavioural and heart rate response to stressful social stimuli in dogs / M. Gácsi, K. Maros, S. Sernkvist, T. Faragó, A. Miklósi // PLoS One. – 2013. – 8 (3). – e58475. – DOI 10.1371/journal.pone.0058475.

6. Kimura, Y. Perception biases for problematic behaviors in dogs due to owners' attributes / Y. Kimura, S. Totani, S. Kameshima, N. Itoh // J Vet Med Sci. – 2023. – 85(7). – C. 763-771. – DOI 10.1292/jvms.23-0022.

7. Aguilar-Lazcano, C.A. Machine learningbased sensor data fusion for animal monitoring: scoping review / C.A. Aguilar-Lazcano, I.E. Espinosa-Curiel, J.A. Ríos-Martínez, F.A. Madera-Ramírez, H. Pérez-Espinosa // Sensors (Basel). – 2023. - (12). – 5732. – DOI 10.3390/s23125732.

8. Li, M.F. The activity patterns of nonworking and working sled dogs / M.F. Li, L. Nagendran, L. Schroeder, D.R. Samson // Sci Rep. – 2022. – 12(1). – 7999. – DOI 10.1038/s41598-022-11635-5.

9. Bleuer-Elsner, S. Computational Analysis of Movement Patterns of Dogs with ADHDLike Behavior / S. Bleuer-Elsner, A. Zamansky, A. Fux, D. Kaplun, S. Romanov, A. Sinitca, S. Masson, D. van der Linden // Animals (Basel). – 2019. – 9(12). – 1140. – DOI 10.3390/ani9121140.

10. den Uijl, I. External validation of a collarmounted triaxial accelerometer for secondby-second monitoring of eight behavioural states in dogs / I. den Uijl, C.B. Gómez Álvarez, D. Bartram, Y. Dror, R. Holland, A. Cook // PLoS One. – 2017. – 12(11). – e0188481. – DOI 10.1371/journal.pone.0188481.

11. Miller, S.L. The importance of evaluating positive welfare characteristics and temperament in working therapy dogs» / S.L. Miller, J.A. Serpell, K.R. Dalton, et al // Front Vet Sci. – 2022. – (9). – 844252. – DOI 10.3389/ fvets.2022.844252.

12. Foster, M. Preliminary evaluation of a system with on-body and aerial sensors for monitoring working dogs / M. Foster, T. Wu, D.L. Roberts, A. Bozkurt // Sensors (Basel). – 2022. – 22(19). – 7631. – DOI 10.3390/s22197631.

13. Kasnesis, P. Deep learning empowered wearable-based behavior recognition for search and rescue dogs / P. Kasnesis, V. Doulgerakis, D. Uzunidis, D.G. Kogias, S.I. Funcia, M.B. González, C. Giannousis, C.Z. Patrikakis // Sensors (Basel). – 2022 – 22(3). – 993. – DOI 10.3390/s22030993.

14. Mariti, C. The assessment of dog welfare in the waiting room of a veterinary clinic / C. Mariti, E. Raspanti, M. Zilocchi, B. Carlone, A. Gazzano // Animal Welfare. – 2015. – 24 (3). – C. 299 – 305 – DOI 10.7120/09627286.24.3.299

15. Marshall-Pescini, S. The Role of Oxytocin in the Dog-Owner Relationship / S. Marshall-Pescini, F.S. Schaebs, A. Gaugg, A. Meinert, T. Deschner, F. Range // Animals (Basel). – 2019. – 9(10). – 792. – DOI 10.3390/ani9100792.

16. Segurson, S.A. Evaluation of a behavioral assessment questionnaire for use in the characterization of behavioral problems of dogs relinquished to animal shelters / S.A. Segurson, J.A. Serpell, B.L. Hart // J Am Vet Med Assoc. – 2005. – 227(11). – 1755-61. – DOI 10.2460/javma.2005.227.1755.

17. Tiira, K. Prevalence, comorbidity, and behavioral variation in canine anxiety / K. Tiira, S. Sulkama, H. Lohi // Journal of Veterinary Behavior. – 2016. – 16. – C. 36-44. – DOI 10.1016/j.jveb.2016.06.008

18. Topál, J. Differential sensitivity to human communication in dogs, wolves, and human infants / J. Topál, G. Gergely, A. Erdohegyi, G. Csibra, A. Miklósi // Science. – 2009. – 325(5945). –1269-72. DOI 10.1126/science.1176960.

19. Vehkaoja, A. Description of movement sensor dataset for dog behavior classification / A. Vehkaoja, S. Somppi, H. Törnqvist, A. Valldeoriola Cardó, P. Kumpulainen, H. Väätäjä, P. Majaranta, V. Surakka, M.V. Kujala, O. Vainio // Data Brief. – 2022. – 40. – 107822. – DOI 10.1016/j.dib.2022.107822.

20. Duffy D. L. Predictive validity of a method for evaluating temperament in young guide and service dogs / Duffy D. L., Serpell J.A. // Applied Animal Behaviour Science.- 2012.- 1–2.- 99-109, https://doi.org/10.1016/j.applanim.2012.02.011

21. -Certificate of state registration of the computer program No. 2024680098 Russian Federation. Program for viewing and analyzing thermograms of the muzzles of domestic dogs: No. 2024667501: application. 07/25/2024: publ. 08/26/2024 / A. S. Fomina, V. O. Rachenkova, V. V. Dolgov, A. A. Krikunova ; applicant Federal State budgetary educational institution of higher education "Don State Technical University".(In Russ.).

22. Csoltova E. Behavioral and physiological reactions in dogs to a veterinary examination: Owner-dog interactions improve canine well-being / Csoltova E, Martineau M, Boissy A, Gilbert C. // Physiol Behav. – 2017.-177.-270-281. doi: 10.1016/j.physbeh.2017.05.013