WiFi CSI Based Passive Human Activity Recognition Using Attention Based BLSTM

By Zhenghua Chen, Le Zhang, Chaoyang Jiang, Zhiguang Cao, Wei Cui. IEEE Transactions on Mobile Computing, 2019

444 citations recorded by the source corpus.

Human activity recognition can benefit various applications including healthcare services and context awareness. Since human actions will influence WiFi signals, which can be captured by the channel state information (CSI) of WiFi, WiFi CSI based human activity recognition has gained more and more attention. Due to the complex relationship between human activities and WiFi CSI measurements, the accuracies of current recognition systems are far from satisfactory. In this paper, we propose a new deep learning based approach, i.e., attention based bi-directional long short-term memory (ABLSTM), for passive human activity recognition using WiFi CSI signals. The BLSTM is employed to learn representative features in two directions from raw sequential CSI measurements. Since the learned features may have different contributions for final activity recognition, we leverage on an attention mechanism to assign different weights for all the learned features. Real experiments have been carried out to evaluate the performance of the proposed ABLSTM for human activity recognition. The experimental results show that our proposed ABLSTM is able to achieve the best recognition performance for all activities when compared with some benchmark approaches.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/0017ece1f39a0ed3a054697e87bc4d92c52a3658

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Jun Liu
2. Jia Zhu
3. Yuanhao Cui
4. Weijie Yuan

In Computer Vision and Pattern Recognition

1. Qiuhong Ke
2. Jun Liu
3. Hossein Rahmani
4. Zehua Sun
5. Jiaqi Zou
6. G. Wang
7. Amir Shahroudy
8. Mohammed Bennamoun

In Electrical and Electronic Engineering

1. Jun Liu
2. Jia Zhu
3. Yuanhao Cui
4. Weijie Yuan

Citations in the corpus

• Integrated Sensing and Communications: Recent Advances and Ten Open Challenges (2023, methodology): “Although a wide variety of solutions have been proposed for wireless human sensing [18], [126], [127], [180], [181], there are still numerous open problems to be solved.”
• Human Action Recognition From Various Data Modalities: A Review (2020, methodology): “LSTM networks have also been used for HAR using CSI signal [295], [296], [297].”