Deep Learning Based Systems Developed for Fall Detection: A Review
Accidental falls are a major source of loss of autonomy, deaths, and injuries among the elderly. Accidental falls also have a remarkable impact on the costs of national health systems. Thus, extensive research and development of fall detection and rescue systems are a necessity. Technologies related...
Main Authors: | Md. Milon Islam, Omar Tayan, Md. Repon Islam, Md. Saiful Islam, Sheikh Nooruddin, Muhammad Nomani Kabir, Md. Rabiul Islam |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9186685/ |
Similar Items
-
A combined deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images
by: Md. Zabirul Islam, et al.
Published: (2020-01-01) -
A New Data Driven Long-Term Solar Yield Analysis Model of Photovoltaic Power Plants
by: Biplob Ray, et al.
Published: (2020-01-01) -
Depth Estimation From a Single RGB Image Using Fine-Tuned Generative Adversarial Network
by: Naeem Ul Islam, et al.
Published: (2021-01-01) -
Deep Learning Methods for Classification of Certain Abnormalities in Echocardiography
by: Imayanmosha Wahlang, et al.
Published: (2021-02-01) -
Deep Learning to Predict Falls in Older Adults Based on Daily-Life Trunk Accelerometry
by: Ahmed Nait Aicha, et al.
Published: (2018-05-01)