Elder Action Recognition Based on Convolutional Neural Network and Long Short-Term Memory

To assist in the identification of possible dangerous situations in the elderly care situation, such as a fall. This study utilizes action recognition to detect and record elder daily movement. If there is any abnormality, the detection system will send out a warning for help. The accuracy is 87.5%...

Full description

Saved in:
Bibliographic Details
Published in2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW) pp. 1 - 2
Main Authors Tseng, Hsiao-Ting, Hsieh, Chen-Chiung, Hsu, Ti-Yun
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.09.2021
Subjects
Conferences
Convolutional neural networks
Senior citizens
Online AccessGet full text

Cover

More Information
Summary:To assist in the identification of possible dangerous situations in the elderly care situation, such as a fall. This study utilizes action recognition to detect and record elder daily movement. If there is any abnormality, the detection system will send out a warning for help. The accuracy is 87.5% for the elder action recognition that developed with CNN and LSTM.
ISSN:2575-8284
DOI:10.1109/ICCE-TW52618.2021.9603253