Deep learning based multimodal complex human activity recognition using wearable devices
- 26 November 2020
- journal article
- research article
- Published by Springer Nature in Applied Intelligence
- Vol. 51 (6) , 4029-4042
Abstract
No abstract availableKeywords
Funding Information
- the Fundamental Research Funds for the Central Universities (No. 2020QNA5017)
This publication has 41 references indexed in Scilit:
- Convolutional, Long Short-Term Memory, fully connected Deep Neural Networks2015
- Feature Selection and Activity Recognition System Using a Single Triaxial AccelerometerIEEE Transactions on Biomedical Engineering, 2014
- Convolutional Neural Networks for Human Activity Recognition using Mobile Sensors2014
- Time Series Classification Using Multi-Channels Deep Convolutional Neural Networks2014
- A tutorial on human activity recognition using body-worn inertial sensorsACM Computing Surveys, 2014
- Centinela: A human activity recognition system based on acceleration and vital sign dataPervasive and Mobile Computing, 2012
- Physical activity monitoring by use of accelerometer-based body-worn sensors in older adults: A systematic literature review of current knowledge and applicationsMaturitas, 2012
- Daily Routine Recognition through Activity Spotting2009
- Activity Recognition from User-Annotated Acceleration Data2004
- Long Short-Term MemoryNeural Computation, 1997