Smart Garment for Continuous Respiration Monitoring in Canines
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 solutionsranging from clinical instruments to wearable devicesare 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.
Authors
- Juan C. Mesa
- Yuhyun Ji
- Jinheon Jeong (ORCID: https://orcid.org/0009-0002-1059-8416)
- Tianhao Yu (ORCID: https://orcid.org/0000-0001-5172-8139)
- Taewoong Park (ORCID: https://orcid.org/0000-0001-6923-8541)
- Young L. Kim (ORCID: https://orcid.org/0000-0003-3796-9643)
- Dong rip Kim
- Luís Felipe Neves dos Santos (ORCID: https://orcid.org/0000-0002-9964-9242)
- Hyowon Lee (ORCID: https://orcid.org/0000-0001-7628-1441)
- Seokkyoon Hong
- Chi Hwan Lee
- YoungJun Lee
- Seok-Won Kang
- Rachel K. Surowiec
Institutions
- Purdue University West Lafayette (US)
- Institute of Nanotechnology (GB)
- Weldon City Schools (US)
- Hanyang University (KR)
- Yeungnam University (KR)
Publication Details
- Journal
- ACS Sensors
- Published
- 2026-03-03
- DOI
- https://doi.org/10.1021/acssensors.5c03783
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.00