A Deep Learning Network with Aggregation Residual Transformation for Human Activity Recognition Using Inertial and Stretch Sensors
With the rise of artificial intelligence, sensor-based human activity recognition (S-HAR) is increasingly being employed in healthcare monitoring for the elderly, fitness tracking, and patient rehabilitation using smart devices. Inertial sensors have been commonly used for S-HAR, but wearable device...
Main Authors: | Sakorn Mekruksavanich, Anuchit Jitpattanakul |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-07-01
|
Series: | Computers |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-431X/12/7/141 |
Similar Items
-
Physical Activity Recognition Based on Deep Learning Using Photoplethysmography and Wearable Inertial Sensors
by: Narit Hnoohom, et al.
Published: (2023-01-01) -
Device Position-Independent Human Activity Recognition with Wearable Sensors Using Deep Neural Networks
by: Sakorn Mekruksavanich, et al.
Published: (2024-03-01) -
Biometric User Identification Based on Human Activity Recognition Using Wearable Sensors: An Experiment Using Deep Learning Models
by: Sakorn Mekruksavanich, et al.
Published: (2021-01-01) -
Deep Convolutional Neural Network with RNNs for Complex Activity Recognition Using Wrist-Worn Wearable Sensor Data
by: Sakorn Mekruksavanich, et al.
Published: (2021-07-01) -
Deep Residual Network for Smartwatch-Based User Identification through Complex Hand Movements
by: Sakorn Mekruksavanich, et al.
Published: (2022-04-01)