Online Learning of Wearable Sensing for Human Activity Recognition
Author:
Affiliation:
1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China
2. Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, U.K.
Funder
China Postdoctoral Science Foundation
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/6488907/9955314/09816056.pdf?arnumber=9816056
Reference47 articles.
1. Human Activity Recognition by Wearable Sensors : Comparison of different classifiers for real-time applications
2. Elderly Fall Detection Using Wearable Sensors: A Low Cost Highly Accurate Algorithm
3. IoT Wearable Sensor and Deep Learning: An Integrated Approach for Personalized Human Activity Recognition in a Smart Home Environment
4. Accelerometer-based fall detection using feature extraction and support vector machine algorithms
5. Fall detection - Principles and Methods
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