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

Hsiao Ting Tseng, Chen Chiung Hsieh, Ti Yun Hsu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665433280
DOIs
StatePublished - 2021
Event8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021 - Penghu, Taiwan
Duration: 15 Sep 202117 Sep 2021

Publication series

Name2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

Conference

Conference8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
Country/TerritoryTaiwan
CityPenghu
Period15/09/2117/09/21

Fingerprint

Dive into the research topics of 'Elder Action Recognition Based on Convolutional Neural Network and Long Short-Term Memory'. Together they form a unique fingerprint.

Cite this