Classifying human actions in daily life using computational intelligence techniques

Romina Torres, Mauricio Poblete, Rodrigo Salas

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

1 Scopus citations

Abstract

Nowadays, there are several effective computational intelligence techniques that, theoretically, could be useful to classify human daily life actions. Moreover, sensors are getting smaller, cheaper, portable and even wearable. In this paper, we have built an annotation tool by applying several computational intelligence techniques (K-Nearest Neighbor, the Support Vector Machine and the Multilayer Perceptron) to detect six types of human actions in daily life based on signals obtained from an accelerometer sensor (standing-up, walking, running, resting, jumping and sitting-down) with an accuracy over 85%. In the future, this component will be the base to infer abnormal behavior from common daily behavior that could be an emergency situation in evolution.

Original languageEnglish
Title of host publication2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781538631232
DOIs
StatePublished - 19 Dec 2017
Externally publishedYes
Event2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017 - Pucon, Chile
Duration: 18 Oct 201720 Oct 2017

Publication series

Name2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017 - Proceedings
Volume2017-January

Conference

Conference2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017
Country/TerritoryChile
CityPucon
Period18/10/1720/10/17

Keywords

  • Annotating tool
  • Computational Intelligence
  • Uman life monitoring

Fingerprint

Dive into the research topics of 'Classifying human actions in daily life using computational intelligence techniques'. Together they form a unique fingerprint.

Cite this