{"title":"Wearable Sensing Devices for Continuous Animal Health Monitoring","authors":"Keer Chen, Youmin Zheng, Yifan Gu, Guozhen Liu","doi":"10.1002/smtd.70982","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Continuous, noninvasive animal health monitoring systems are increasingly required in livestock farming, companion animal care, and wildlife conservation. The translation of wearable sensing technologies across these sectors is complicated. Their practical performance depends not only on sensing accuracy but also on the variability of anatomical features, uncontrolled movement, environmental exposure, wireless connectivity, power supply, and animal welfare considerations. This review presents a system-level, design-oriented analysis of animal health monitoring sensing technologies. It classifies sensing modalities into physical and physiological, biochemical and molecular, environmental and spatial, and multimodal sensing, followed by examining their integration into on-animal and ingestible devices. Communication, edge and cloud computing, power management, and representative applications across livestock, companion animals, and wildlife are also discussed. The review further identifies key barriers to translation, including the need for signal stability, interoperability between systems, energy supply constraints, maintenance burden, and ethical and welfare concerns related to long-term monitoring. Future systems should prioritize species- and site-specific integration, long-term field validation, interoperable data architectures, welfare-conscious design, and clinically or managerially actionable outputs. This framework offers practical guidance for translating continuous sensing into scalable decisions for animal health and welfare.</p>\n </div>","PeriodicalId":229,"journal":{"name":"Small Methods","volume":"10 19","pages":""},"PeriodicalIF":8.7000,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Small Methods","FirstCategoryId":"88","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/smtd.70982","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/8/18 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Continuous, noninvasive animal health monitoring systems are increasingly required in livestock farming, companion animal care, and wildlife conservation. The translation of wearable sensing technologies across these sectors is complicated. Their practical performance depends not only on sensing accuracy but also on the variability of anatomical features, uncontrolled movement, environmental exposure, wireless connectivity, power supply, and animal welfare considerations. This review presents a system-level, design-oriented analysis of animal health monitoring sensing technologies. It classifies sensing modalities into physical and physiological, biochemical and molecular, environmental and spatial, and multimodal sensing, followed by examining their integration into on-animal and ingestible devices. Communication, edge and cloud computing, power management, and representative applications across livestock, companion animals, and wildlife are also discussed. The review further identifies key barriers to translation, including the need for signal stability, interoperability between systems, energy supply constraints, maintenance burden, and ethical and welfare concerns related to long-term monitoring. Future systems should prioritize species- and site-specific integration, long-term field validation, interoperable data architectures, welfare-conscious design, and clinically or managerially actionable outputs. This framework offers practical guidance for translating continuous sensing into scalable decisions for animal health and welfare.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.