HARKE: Human Activity Recognition from Kinetic Energy Harvesting Data in Wearable Devices

2018 ◽  
Vol 17 (6) ◽  
pp. 1353-1368 ◽  
Author(s):  
Sara Khalifa ◽  
Guohao Lan ◽  
Mahbub Hassan ◽  
Aruna Seneviratne ◽  
Sajal K. Das
Keyword(s):  
Energy Harvesting ◽  
Kinetic Energy ◽  
Activity Recognition ◽  
Human Activity ◽  
Wearable Devices ◽  
Human Activity Recognition

A Lightweight Framework for Human Activity Recognition on Wearable Devices

2021 ◽  
pp. 1-1
Author(s):  
Yves L. Coelho ◽  
Francisco A. S. Santos ◽  
Anselmo Frizera-Neto ◽  
Teodiano F. Bastos-Filho
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Wearable Devices ◽  
Human Activity Recognition ◽  
Lightweight Framework

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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