New Sensor Data Structuring for Deeper Feature Extraction in Human Activity Recognition
For the effective application of thriving human-assistive technologies in healthcare services and human–robot collaborative tasks, computing devices must be aware of human movements. Developing a reliable real-time activity recognition method for the continuous and smooth operation of such smart dev...
Main Authors: | Tsige Tadesse Alemayoh, Jae Hoon Lee, Shingo Okamoto |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-04-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/8/2814 |
Similar Items
-
Deep-Learning-Based Character Recognition from Handwriting Motion Data Captured Using IMU and Force Sensors
by: Tsige Tadesse Alemayoh, et al.
Published: (2022-10-01) -
A Deep Learning Approach for Biped Robot Locomotion Interface Using a Single Inertial Sensor
by: Tsige Tadesse Alemayoh, et al.
Published: (2023-12-01) -
Leg Joint Angle Estimation From a Single Inertial Sensor During Variety of Walking Motions: A Deep Learning Approach
by: Tsige Tadesse Alemayoh, et al.
Published: (2023-01-01) -
Leg-Joint Angle Estimation from a Single Inertial Sensor Attached to Various Lower-Body Links during Walking Motion
by: Tsige Tadesse Alemayoh, et al.
Published: (2023-04-01) -
Improving Inertial Sensor-Based Activity Recognition in Neurological Populations
by: Yunus Celik, et al.
Published: (2022-12-01)