Name
Title | ||
|---|---|---|
A Body Sensor Data Fusion and Deep Recurrent Neural Network-based Behavior Recognition Approach for Robust Healthcare |
Abstract | ||
|---|---|---|
•Sensor-based user behavior and health status monitoring is getting much attention.•Proposed a deep RNN-based activity recognition system based on body sensor data.•Data fusion was performed from multiple body sensors data.•The extracted features are further enhanced via kernel principal component analysis.•Three publicly available standard datasets were used for performance comparison. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.inffus.2019.08.004 | Information Fusion |
Keywords | Field | DocType |
Body sensor data fusion,Behavior recognition,Deep recurrent neural network,Robust healthcare | Health care,Accelerometer,Wearable computer,Recurrent neural network,Sensor fusion,Kernel principal component analysis,Artificial intelligence,Behavior recognition,Deep learning,Machine learning,Mathematics | Journal |
Volume | ISSN | Citations |
55 | 1566-2535 | 8 |
PageRank | References | Authors |
0.53 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Md. Zia Uddin | 1 | 158 | 14.34 |
| Mohammed Mehedi Hassan | 2 | 13 | 1.01 |
| Ahmed Alsanad | 3 | 8 | 3.24 |
| Claudio Savaglio | 4 | 37 | 1.91 |