A Multisensor Multiclassifier Hierarchical Fusion Model Based on Entropy Weight for Human Activity Recognition Using Wearable Inertial Sensors

2019 ◽  
Vol 49 (1) ◽  
pp. 105-111 ◽  
Author(s):  
Ming Guo ◽  
Zhelong Wang ◽  
Ning Yang ◽  
Zhenglin Li ◽  
Tiantian An
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Inertial Sensors ◽  
Human Activity Recognition ◽  
Fusion Model ◽  
Entropy Weight ◽  
Model Based ◽  
Wearable Inertial Sensors

Can You See It?

2021 ◽  
Vol 25 (2) ◽  
pp. 38-42
Author(s):  
Hyeokhyen Kwon ◽  
Catherine Tong ◽  
Harish Haresamudram ◽  
Yan Gao ◽  
Gregory D. Abowd ◽  
...  
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Inertial Sensors ◽  
Human Subjects ◽  
Wearable Devices ◽  
Human Activity Recognition ◽  
Training Data ◽  
Considerable Time ◽  
Administrative Work ◽  
Everyday Activities

Today's smartphones and wearable devices come equipped with an array of inertial sensors, along with IMU-based Human Activity Recognition models to monitor everyday activities. However, such models rely on large amounts of annotated training data, which require considerable time and effort for collection. One has to recruit human subjects, define clear protocols for the subjects to follow, and manually annotate the collected data, along with the administrative work that goes into organizing such a recording.

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