Drinking Gesture Detection Using Wrist-Worn IMU Sensors with Multi-Stage Temporal Convolutional Network in Free-Living Environments-Reference-Cited by-同舟云学术

Drinking Gesture Detection Using Wrist-Worn IMU Sensors with Multi-Stage Temporal Convolutional Network in Free-Living Environments

Published:2022-07-11 Issue: Volume: Page:
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Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Wang Chunzhuo¹,Kumar T. Sunil¹,De Raedt Walter²,Camps Guido³,Hallez Hans⁴,Vanrumste Bart¹

Affiliation:

1. KU Leuven,e-Media Research Lab,Leuven,Belgium,3000

2. IMEC,Life Science Department,Heverlee,Belgium Walter,3001

3. Wageningen University and Research,Division of Human Nutrition and Health,Department of Agrotechnology and Food Sciences,Wageningen,The Netherlands,6700EA

4. KU Leuven,M-Group, DistriNet,Department of Computer Science,Sint-Michiels,Belgium,8200

Funder

China Scholarship Council(CSC), China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871817.pdf?arnumber=9871817

Reference21 articles.

1. Fluid Intake Monitoring System Using a Wearable Inertial Sensor for Fluid Intake Management

2. Real-Time Drink Trigger Detection in Free-living Conditions Using Inertial Sensors

3. Towards a generalizable method for detecting fluid intake with wrist-mounted sensors and adaptive segmentation

4. Detection of drinking via a wrist-worn inertial sensor.

5. Sparse natural gesture spotting in free living to monitor drinking with wrist-worn inertial sensors

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