Deep CNN-LSTM With Self-Attention Model for Human Activity Recognition Using Wearable Sensor

Deep CNN-LSTM With Self-Attention Model for Human Activity Recognition Using Wearable Sensor

Human Activity Recognition (HAR) systems are devised for continuously observing human behavior - primarily in the fields of environmental compatibility, sports injury detection, senior care, rehabilitation, entertainment, and the surveillance in intelligent home settings. Inertial sensors, e.g., acc...

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Bibliographic Details
Main Authors: Mst. Alema Khatun, Mohammad Abu Yousuf, Sabbir Ahmed, Md. Zia Uddin, Salem A. Alyami, Samer Al-Ashhab, Hanan F. Akhdar, Asaduzzaman Khan, Akm Azad, Mohammad Ali Moni
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
Sensors
smartphones
accelerometers
attention
gyroscopes
LSTM
Online Access:https://ieeexplore.ieee.org/document/9781408/

Internet

https://ieeexplore.ieee.org/document/9781408/

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