TY - GEN
T1 - Smart Pet Clothing for Monitoring of Health and Mood
AU - Lin, Yu Jin
AU - Chuang, Chen Wei
AU - Yen, Chun Yueh
AU - Huang, Sheng Hsin
AU - Lee, Shuenn Yuh
N1 - Funding Information:
The authors greatly appreciate the support from the Chip Implementation Center, Taiwan, and the Ministry of Science and Technology, Taiwan (Grant MOST 106-2314-B-006-001, MOST 107-2622-8-006-009 -TE2).
Publisher Copyright:
© 2018 IEEE.
PY - 2018/4/26
Y1 - 2018/4/26
N2 - A smart pet clothing with full hardware and software support for internet of things is proposed. The hardware comprises three parts: a special pet sensor, an analog front-end circuit for detecting electrocardiogram (ECG) and breath signals, and a micro printed circuit board with signal communication. The software also consists of three parts: an algorithm for biosignal processing, an application (app) as graphical user interface (GUI), and a web server for healthcare. The algorithm is used to calculate the heart rate (HR), HR variability (HRV), high-to-low-frequency ratio determined by HRV analysis, breath rate, and basic emotion analysis. The app is developed for building a user-friendly GUI and communication platform between the hardware device and the cloud server. The web server not only provides detailed information to the veterinarian and the pet owner but also runs a convolutional neural network algorithm on big data to identify abnormal ECG signals. The analog front-end circuits with ECG and breath detectors, an ARM Cortex M0 MCU, and Bluetooth and power modules are integrated into a device with the size of a coin that can be placed in an approximately 32 mm χ 32 mm × 24 mm box. The mechanism can be easily worn on clothing for monitoring pet health and mood.
AB - A smart pet clothing with full hardware and software support for internet of things is proposed. The hardware comprises three parts: a special pet sensor, an analog front-end circuit for detecting electrocardiogram (ECG) and breath signals, and a micro printed circuit board with signal communication. The software also consists of three parts: an algorithm for biosignal processing, an application (app) as graphical user interface (GUI), and a web server for healthcare. The algorithm is used to calculate the heart rate (HR), HR variability (HRV), high-to-low-frequency ratio determined by HRV analysis, breath rate, and basic emotion analysis. The app is developed for building a user-friendly GUI and communication platform between the hardware device and the cloud server. The web server not only provides detailed information to the veterinarian and the pet owner but also runs a convolutional neural network algorithm on big data to identify abnormal ECG signals. The analog front-end circuits with ECG and breath detectors, an ARM Cortex M0 MCU, and Bluetooth and power modules are integrated into a device with the size of a coin that can be placed in an approximately 32 mm χ 32 mm × 24 mm box. The mechanism can be easily worn on clothing for monitoring pet health and mood.
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U2 - 10.1109/ISCAS.2018.8351547
DO - 10.1109/ISCAS.2018.8351547
M3 - Conference contribution
AN - SCOPUS:85057084920
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
BT - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
Y2 - 27 May 2018 through 30 May 2018
ER -