An engineering perspective on the development and evolution of implantable cardiac monitors in free-living animals

• Published in: Philosophical Transactions of the Royal Society B: Biological Sciences
• Main Authors: Laske, Timothy G., Garshelis, David L., Iles, Tinen L., Iaizzo, Paul A.
• Format: Article in Journal/Newspaper
• Language: English
• Published: The Royal Society 2021
• Subjects: Alces alces; Canis lupus; Elephant Seals; Mirounga leonina; Southern Elephant Seals; Ursus arctos
• Online Access: http://dx.doi.org/10.1098/rstb.2020.0217; https://royalsocietypublishing.org/doi/pdf/10.1098/rstb.2020.0217; https://royalsocietypublishing.org/doi/full-xml/10.1098/rstb.2020.0217

The latest technologies associated with implantable physiological monitoring devices can record multiple channels of data (including: heart rates and rhythms, activity, temperature, impedance and posture), and coupled with powerful software applications, have provided novel insights into the physiology of animals in the wild. This perspective details past challenges and lessons learned from the uses and developments of implanted biologgers designed for human clinical application in our research on free-ranging American black bears ( Ursus americanus ). In addition, we reference other research by colleagues and collaborators who have leveraged these devices in their work, including: brown bears ( Ursus arctos ), grey wolves ( Canis lupus ), moose ( Alces alces ), maned wolves ( Chrysocyon brachyurus ) and southern elephant seals ( Mirounga leonina ). We also discuss the potentials for applications of such devices across a range of other species. To date, the devices described have been used in fifteen different wild species, with publications pending in many instances. We have focused our physiological research on the analyses of heart rates and rhythms and thus special attention will be paid to this topic. We then discuss some major expected step changes such as improvements in sensing algorithms, data storage, and the incorporation of next-generation short-range wireless telemetry. The latter provides new avenues for data transfer, and when combined with cloud-based computing, it not only provides means for big data storage but also the ability to readily leverage high-performance computing platforms using artificial intelligence and machine learning algorithms. These advances will dramatically increase both data quantity and quality and will facilitate the development of automated recognition of extreme physiological events or key behaviours of interest in a broad array of environments, thus further aiding wildlife monitoring and management. This article is part of the theme issue ‘Measuring physiology in ...