A Data-Driven Feature Extraction Method Based on Data Supplement for Human Activity Recognition
Author:
Affiliation:
1. Department of Computer Engineering, Gachon University, Seongnam, South Korea
Funder
National Research Foundation of Korea (NRF) through the Korean Government [Ministry of Science and Information and Communications Technology (ICT)]
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/7361/10599846/10547639.pdf?arnumber=10547639
Reference58 articles.
1. Human Gait Analysis and Activity Recognition: A Review
2. A Novel Feature Extraction Method for Preimpact Fall Detection System Using Deep Learning and Wearable Sensors
3. Tracking of Fall Detection Using IMU Sensor: An IoHT Application
4. Development of the LSTM Model and Universal Polynomial Equation for All the Sub-Phases of Human Gait
5. Pattern identification of different human joints for different human walking styles using inertial measurement unit (IMU) sensor
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