Key result
A video-based heart rate monitoring algorithm achieved a mean absolute error of 2.33 bpm in an anesthetized pig and 4.69 bpm in a resting pig compared to gold standard ECG.
Why the study?
Heart rate is a key vital sign linked to health and welfare, motivating the development of an algorithm to extract heart rate from raw video data in pigs.
Does a contactless video-based algorithm accurately measure heart rate in resting and anesthetized pigs compared to gold standard ECG?
Does a contactless video-based algorithm accurately measure heart rate in resting and anesthetized pigs compared to gold standard ECG?
A contactless video-based algorithm focusing on the abdominal region and using the green color channel can accurately estimate heart rate in resting and anesthetized pigs.
Supports non-contact monitoring development in animal models; leaves open human validation and clinical translation.
Heart rate (HR) is a vital bio-signal that is relatively easy to monitor with contact sensors and is related to a living organism's state of health, stress and well-being. The objective of this study was to develop an algorithm to extract HR (in beats per minute) of an anesthetized and a resting pig from raw video data as a first step towards continuous monitoring of health and welfare of pigs. Data were obtained from two experiments, wherein the pigs were video recorded whilst wearing an electrocardiography (ECG) monitoring system as gold standard (GS). In order to develop the algorithm, this study used a bandpass filter to remove noise. Then, a short-time Fourier transform (STFT) method was tested by evaluating different window sizes and window functions to accurately identify the HR. The resulting algorithm was first tested on videos of an anesthetized pig that maintained a relatively constant HR. The GS HR measurements for the anesthetized pig had a mean value of 71.76 bpm and standard deviation (SD) of 3.57 bpm. The developed algorithm had 2.33 bpm in mean absolute error (MAE), 3.09 bpm in root mean square error (RMSE) and 67% in HR estimation error below 3.5 bpm. The sensitivity of the algorithm was then tested on the video of a non-anaesthetized resting pig, as an animal in this state has more fluctuations in HR than an anaesthetized pig, while motion artefacts are still minimized due to resting. The GS HR measurements for the resting pig had a mean value of 161.43 bpm and SD of 10.11 bpm. The video-extracted HR showed a performance of 4.69 bpm in MAE, 6.43 bpm in RMSE and 57% in . The results showed that HR monitoring using only the green channel of the video signal was better than using three color channels, which reduces computing complexity. By comparing different regions of interest (ROI), the region around the abdomen was found physiologically better than the face and front leg parts. In summary, the developed algorithm based on video data has potential to be used for contactless HR measurement and may be applied on resting pigs for real-time monitoring of their health and welfare status, which is of significant interest for veterinarians and farmers.
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Wang et al. (2021) studied Heart rate monitoring in pigs (n=2). Video-based heart rate monitoring algorithm vs. Electrocardiography (ECG) monitoring system was evaluated on Heart rate estimation error (Mean Absolute Error and Root Mean Square Error). A video-based heart rate monitoring algorithm achieved a mean absolute error of 2.33 bpm in an anesthetized pig and 4.69 bpm in a resting pig compared to gold standard ECG.
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