Research Article
Data Fusion for Human Activity Recognition Based on RF Sensing and IMU Sensor
@INPROCEEDINGS{10.1007/978-3-030-95593-9_1, author={Zheqi Yu and Adnan Zahid and William Taylor and Hasan Abbas and Hadi Heidari and Muhammad A. Imran and Qammer H. Abbasi}, title={Data Fusion for Human Activity Recognition Based on RF Sensing and IMU Sensor}, proceedings={Body Area Networks. Smart IoT and Big Data for Intelligent Health Management. 16th EAI International Conference, BODYNETS 2021, Virtual Event, October 25-26, 2021, Proceedings}, proceedings_a={BODYNETS}, year={2022}, month={2}, keywords={Data fusion Human activity recognition Artificial intelligence Signal processing}, doi={10.1007/978-3-030-95593-9_1} }- Zheqi Yu
Adnan Zahid
William Taylor
Hasan Abbas
Hadi Heidari
Muhammad A. Imran
Qammer H. Abbasi
Year: 2022
Data Fusion for Human Activity Recognition Based on RF Sensing and IMU Sensor
BODYNETS
Springer
DOI: 10.1007/978-3-030-95593-9_1
Abstract
This paper proposes a new data fusion method, which uses the designed construction matrix to fuse sensor and USRP data to realise Human Activity Recognition. At this point, Inertial Measurement Unit sensors and Universal Software-defined Radio Peripherals are used to collect human activities signals separately. In order to avoid the incompatibility problem with different collection devices, such as different sampling frequency caused inconsistency time axis. The Principal Component Analysis processing the fused data to dimension reduction without time that is performed to extract the time unrelated(5 \times 5)feature matrix to represent corresponding activities. There are explores data fusion method between multiple devices and ensures accuracy without dropping. The technique can be extended to other types of hardware signal for data fusion.
