A Pilot Study for Estimating the Cardiopulmonary Signals of Diverse Exotic Animals Using a Digital Camera

Abstract

Monitoring the cardiopulmonary signal of animals is a challenge for veterinarians in conditions when contact with a conscious animal is inconvenient, difficult, damaging, distressing or dangerous to personnel or the animal subject. In this pilot study, we demonstrate a computer vision-based system and use examples of exotic, untamed species to demonstrate this means to extract the cardiopulmonary signal. Subject animals included the following species: Giant panda (Ailuropoda melanoleuca), African lions (Panthera leo), Sumatran tiger (Panthera tigris sumatrae), koala (Phascolarctos cinereus), red kangaroo (Macropus rufus), alpaca (Vicugna pacos), little blue penguin (Eudyptula minor), Sumatran orangutan (Pongo abelii) and Hamadryas baboon (Papio hamadryas). The study was done without need for restriction, fixation, contact or disruption of the daily routine of the subjects. The pilot system extracts the signal from the abdominal-thoracic region, where cardiopulmonary activity is most likely to be visible using image sequences captured by a digital camera. The results show motion on the body surface of the subjects that is characteristic of cardiopulmonary activity and is likely to be useful to estimate physiological parameters (pulse rate and breathing rate) of animals without any physical contact. The results of the study suggest that a fully controlled study against conventional physiological monitoring equipment is ethically warranted, which may lead to a novel approach to non-contact physiological monitoring and remotely sensed health assessment of animals. The method shows promise for applications in veterinary practice, conservation and game management, animal welfare and zoological and behavioral studies.

A Systematic Review of the Use of Technology to Monitor Welfare in Zoo Animals: Is There Space for Improvement?

“…The latter is specifically of great importance because it can contribute to easily disseminate the findings of this novel field in the zoo setting. However, the employment of more technology field-specific journals is still limited (i.e., we found only one publication in the journal Sensors [ 37 ]), likely due to the fact that these journals are more focused on recent advances in agriculture, livestock farming, and land sustainability where the application of automated monitoring systems is clearly greater. Thus, we suggest that a more interdisciplinary approach with regard to the choice of the most suitable journal is needed for zoo research on automated monitoring systems.…”

“…Although technology can integrate the current approaches applied in zoos for animal welfare monitoring and assessment, scientists are still far from taking full advantage of it [ 35 ]. For instance, when collecting physiological indicators of welfare such as heart and breathing rate or body temperature, the use of devices such as digital [ 37 ] and IR thermal cameras [ 39 ] or mobile ECG monitors programmed with algorithms [ 46 ] had the advantage that animals did not need to be anesthetized nor to carry over equipment which can be stressful and invasive procedures. A study on gorillas also suggested that IR thermal cameras may have the potential to investigate the emotional response of the animals; however, the authors stated that the application of this device in the absence of other related physiological/behavioural measures needs further validation [ 38 ].…”

A Review of Monitoring Techniques for Livestock Respiration and Sounds

“…Statistical and mathematical models can be used to evaluate the performance of the model. Al-Naji et al (2019) used machine vision to calculate the respiration rate of exotic animals (like Giant panda, African lions, Sumatran tiger, Koala, Red kangaroo, Alpaca, little blue penguin, Sumatran orangutan and Hamadryas baboon). The videos were recorded using a digital camera (Nikon D610, Nikon Inc., Tokyo, Japan) when the animals were not moving much to avoid any noise in the data.…”

“…Once the symptoms of disease become evident, the producers either take no action, seek help from veterinary professionals, use antibiotics or adopt a combination of these three approaches to cure their livestock (Neethirajan, 2020). Getting to this point though involves understanding the physiological issues and novel sensing technology approaches have been investigated to estimate respiratory rates or detect behavioral changes linked to respiratory diseases to identify sick livestock at an early stage (Silva et al, 2008;Weixing and Zhilei, 2010;Mutlu et al, 2018;Al-Naji et al, 2019;Barbosa and Pereira, 2019;Lowe et al, 2019;Wu et al, 2020). Respiratory rate detection technology can be broadly classified into either contact or non-contact technologies.…”

An Adaptive Threshold Method for WMSN Image Denoising

“…Therefore, the effective denoising of acquired WMSN images has been a hot topic in related fields [4][5][6]. Wavelet transform can characterize both time and frequency domain features, and effectively determine the abnormal points in the images and their degree of abnormality, due to these advantages, it has been widely applied in the field of image denoising [7][8][9][10][11]. Among the many wavelet denoising methods, the wavelet threshold denoising method is the most commonly-used method [12].…”