Smart Garment for Continuous Respiration Monitoring in Canines

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Authors: Seokkyoon Hong, Taewoong Park, YoungJun Lee, Juan C. Mesa, Tianhao Yu, Yuhyun Ji, Junsang Lee, Jinheon Jeong, Seok-Won Kang, Dong Rip Kim, Young L. Kim, Hyowon Lee
+3 more Rachel Kathleen Surowiec, Luís Felipe Neves dos Santos, Chi Hwan Lee
Cited by: 1
References: 61

Abstract

There is a growing need for at-home respiration monitoring in canines, who are prone to respiratory issues due to breed-specific anatomy and active lifestyles. Continuous monitoring of respiration provides critical insight into stress and illness; however, current solutionsranging from clinical instruments to wearable devicesare either accurate but invasive and episodic or limited in fit and comfort. Here, we introduce a smart garment that integrates a spongy-like strain sensor and compact data acquisition module into commercially available canine apparel, enabling continuous, non-invasive monitoring of respiration, body temperature, and physical activity. Validation with two breeds, Labrador and Boxer, confirmed its ability to capture breed- and activity-specific respiration patterns, including differences in breathing rate, amplitude, and panting behavior. Using convolutional neural network (CNN)-assisted machine learning (ML), the system classified respiratory patterns across breeds and activity levels with over 94.3% accuracy. Beyond canines, this platform may hold potential for future adaptation to other companion animals, such as cats, suggesting a broader scope for home-based veterinary monitoring.

Fields of Study & Subjects

Non-Invasive Vital Sign Monitoring Intravenous Infusion Technology and Safety Food Supply Chain Traceability

Publication details

Journal / source
ACS Sensors
Publisher
American Chemical Society (ACS)
Volume
11
Issue
3
Pages
2111–2120
Publication date
3 March 2026
Language
EN