SAN JOSE, Calif., July 23, 2020 /PRNewswire/ -- Amidst the global COVID-19 pandemic, innovators and designers are showing ever greater interest in using non-intrusive health-monitoring devices. Maxim Integrated Products, Inc. (NASDAQ: MXIM), working with researchers at Texas A&M University AgriLife Extension, monitored young calves against the onset of bovine respiratory disease (BRD) in a series of experiments designed to examine the challenges and successes in creating a longitudinal health monitor.
BRD, which results in respiratory infections in cattle, is one of the costliest diseases to the livestock industry. It is particularly difficult to control because it can be caused by a multitude of pathogens. American ranchers harvest nearly 300 million calves each year, all of which could potentially be victims of BRD. Because the causes for BRD onset are multifactorial, the cattle industry has not been able to reduce the damages resulting from BRD despite decades of research and improvements in animal welfare.
To improve animal welfare and to reduce costs associated with animal mortality and morbidity, the cattle industry has paid significant attention to improving early onset detection. Conventionally, the industry depends on experienced pen-riders who may notice behavioral changes in specific animals and, consequently, test their temperatures. If an animal's core temperature is above 40.5 °C (104.9°F), it is deemed sick with BRD. There is much room for improvement.
First, using a rigid temperature threshold to diagnose BRD ignores the reality that each animal has different nominal core temperatures. 40.5 °C is merely the average feverish temperature over a large herd of cattle. Some of them have core temperatures that are naturally lower than the average and could already be experiencing a fever even when their core temperature is below the threshold. This is the same principle that guides the understanding that longitudinal and personalized health monitoring results in better healthcare for human patients.
Second, although most feedlot operators are confident in their pen-riders' abilities, researchers report a majority of harvested cattle examined had lesions in their lungs, i.e. had suffered (and recovered) from serious respiratory illnesses, even though most were never treated for BRD. In truth, an experienced pen-rider can expect to take care of 8,000 to 12,000 heads of cattle per day. Consequently, each possibly sick animal could command fewer than two minutes of a rider's attention. Furthermore, because of the labor cost required to handle and test a possibly sick animal, riders are trained to err on false negatives.
Because a fixed core temperature threshold, 40.5°C, has been the gold standard for diagnosing BRD, there have been a lot of attempts to monitor temperature on a head of each cow. These attempts include measuring rumen telemetry temperature using an ingested bolus, measuring air temperature in the ear canal or the temperature of the tympanic membrane, measuring skin temperature, and applying thermal imaging to estimate ocular temperature. These approaches either suffer from very low data reliability or prove to be incompatible with workflow at the feedlot.
Veterinary medicine researchers investigating other onset symptoms of BRD incidentally reported on SpO2 (blood oxygen) measured from cattle at different stages of BRD. The data showed declining average value as the disease became more severe. Since BRD is a respiratory disease, it makes sense that SpO2 would drop as respiratory infection compromises oxygen intake.
Given the established workflow at feedlots, a smart livestock system could assist pen-riders by alerting them of animals whose oxygen reading has dropped below the longitudinal norm of that specific animal. The system would consist of an ear tag equipped with SpO2 and other sensors. The ear tag would collect sensor data and local processing would extract biomarkers including SpO2. A low-power radio would transmit these biomarkers to a base station, which could conveniently be housed in the office of a feedlot or installed on feed delivery trucks. Algorithms in the cloud could then process the biomarker data, maintain a longitudinal record for each animal and send an alert when the biomarkers deviate markedly from the norm. Biomarker data are only needed to generate at most one assessment per day, so the ear tag could run for a long time on a primary cell battery.
In the experiments conducted by Maxim Integrated and AgriLife Extension researchers, the tag used included an optical photophlethysmogram (PPG) using a MAX86141 analog front-end with red and infrared LEDs. Because optical SpO2 measurements are vulnerable to motion artifacts, the team included an accelerometer to detect motion and reject any PPG data captured when the tag was moving. Through the experiments, the team examined various design changes with the sensor as well as the mechanical ear tag design.
For detailed analysis of the BRD experiments and findings, read the blog post, "Can Wearable Health Technology Pinpoint Disease Onset?" A better understanding of how an individual animal's wellness can be monitored can lead to insights for enhancing the implementation of personalized healthcare for human patients.