AnkFall—Falls, Falling Risks and Daily-Life Activities Dataset with an Ankle-Placed Accelerometer and Training Using Recurrent Neural Networks
Falls are one of the leading causes of permanent injury and/or disability among the elderly. When these people live alone, it is convenient that a caregiver or family member visits them periodically. However, these visits do not prevent falls when the elderly person is alone. Furthermore, in excepti...
Main Authors: | Francisco Luna-Perejón, Luis Muñoz-Saavedra, Javier Civit-Masot, Anton Civit, Manuel Domínguez-Morales |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-03-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/5/1889 |
Similar Items
-
Wearable Fall Detector Using Recurrent Neural Networks
by: Francisco Luna-Perejón, et al.
Published: (2019-11-01) -
SisFall: A Fall and Movement Dataset
by: Angela Sucerquia, et al.
Published: (2017-01-01) -
Accelerometer-Based Fall Detection Using Machine Learning: Training and Testing on Real-World Falls
by: Luca Palmerini, et al.
Published: (2020-11-01) -
Triaxial Accelerometer-Based Falls and Activities of Daily Life Detection Using Machine Learning
by: Turke Althobaiti, et al.
Published: (2020-07-01) -
Analysis of Public Datasets for Wearable Fall Detection Systems
by: Eduardo Casilari, et al.
Published: (2017-06-01)