Paper Info
Title
Compression of Gait IMU signals Using Sensor Fusion and Compressive Sensing
Abstract
Sensors are the front end and the primary source of information for any internet of things (IoT) network. The amount of data from these sensors are increasing by the day which makes managing them a priority. The concept of IoT has recently been introduced to biomedical engineering to create networks between health monitoring devices. One of such devices is inertial measurement unit (IMU) which has a wide range of applications from navigation systems to biomedical health monitoring devices.The purpose of this study is to manage the gait data of 9-axis IMU devices collected from human subjects. The compression of these data can be of great importance, especially for their applications in IoT networks. Therefore, we attempted to compress and reconstruct the raw and fused signal by using sensor fusion and compressive sensing and compared the results. By making use of the combination of sensor fusion and compressive sensing, we were able to create accurate and compact data that can significantly reduce the load of a biomedical health monitoring IoT network.
Year
DOI
Venue
2020
10.1109/WTS48268.2020.9198727
2020 Wireless Telecommunications Symposium (WTS)
Keywords
DocType
ISSN
Internet of Things (IoT),Inertial Measurement Unit (IMU),Multi-Sensor Data Fusion (MSDF),Compressive Sensing (CS),Deterministic Binary Block Diagonal (DBBD)
Conference
1934-5070
ISBN
Citations 
PageRank 
978-1-7281-4696-6
0
0.34
References 
Authors
9
4
Name
Order
Citations
PageRank
Seyed Alireza Khoshnevis100.68
Sai Bharadwaj Appakaya211.38
Ehsan Sheybani3158.17
Ravi Sankar465655.66