A Machine Learning Approach for the Classification of Falls and Activities of Daily Living in Agricultural Workers-Reference-Cited by-同舟云学术

A Machine Learning Approach for the Classification of Falls and Activities of Daily Living in Agricultural Workers

Published:2022 Issue: Volume:10 Page:77418-77431
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Son Hyunmok¹,Lim Jae Woon¹,Park Sangbae²,Park Byeongjoo¹,Han Jinsub¹,Kim Hong Bae¹,Lee Myung Chul³,Jang Kyoung-Je⁴,Kim Ghiseok¹,Chung Jong Hoon¹^ORCID

Affiliation:

1. Department of Biosystems Engineering, Seoul National University, Seoul, Korea

2. Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Korea

3. Department of Medicine, Brigham and Women’s Hospital, Division of Engineering in Medicine, Harvard Medical School, Cambridge, MA, USA

4. Division of Agro-System Engineering, College of Agriculture and Life Science, Gyeongsang National University, Jinju, South Korea

Funder

National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT, South Korea

Basic Science Research Program through the National Research Foundation of Korea

Ministry of Education

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09828392.pdf?arnumber=9828392

Reference54 articles.

1. Optimal Placement of Accelerometers for the Detection of Everyday Activities

2. Enhanced Human Activity Recognition Based on Smartphone Sensor Data Using Hybrid Feature Selection Model

3. Structural Design of Garlic Plants Footplate Considering Physical Characteristics of Elderly Women

4. Analysis of static stability by modified mathematical model for asymmetric tractor-harvester system: Changes in lateral overturning angle by movement of center of gravity coordinates;choi;Biosystems Engineering,2017

5. Analysis of static lateral stability using mathematical simulations for 3-axis tractor-baler system;hong;Biosystems Engineering,2017

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design;Journal of Medical Internet Research;2024-08-05

2. A Novel Embedded Deep Learning Wearable Sensor for Fall Detection;IEEE Sensors Journal;2024-05-01

3. Prediction of Noise Levels According to Some Exploitation Parameters of an Agricultural Tractor: A Machine Learning Approach;AgriEngineering;2024-04-15

4. An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design (Preprint);2024-01-25

5. Classification of Fall Detection Based on Daily Living Activities using Machine Learning Approach;2023 International Conference on Recent Advances in Science and Engineering Technology (ICRASET);2023-11-23