Abnormality detection for improving elder's daily life independent

Authors:
Ya-Xuan Hung;Chih-Yen Chiang;Steen J. Hsu;Chia-Tai Chan
Affiliations:
Institute of Biomedical Engineering National Yang-Ming University, Taipei, Taiwan;Institute of Biomedical Engineering National Yang-Ming University, Taipei, Taiwan;Department of Information Management, Minghsin University of Science and Technology, Hsinchu, Taiwan;Institute of Biomedical Engineering National Yang-Ming University, Taipei, Taiwan
Venue:
ICOST'10 Proceedings of the Aging friendly technology for health and independence, and 8th international conference on Smart homes and health telematics
Year:
2010

Citing 13
Cited 1

MetaCost: a general method for making classifiers cost-sensitive

KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
LOF: identifying density-based local outliers

SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Video Behaviour Profiling and Abnormality Detection without Manual Labelling

ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Fine-Grained Activity Recognition by Aggregating Abstract Object Usage

ISWC '05 Proceedings of the Ninth IEEE International Symposium on Wearable Computers
Activity recognition for context-aware hospital applications: issues and opportunities for the deployment of pervasive networks

Mobile Networks and Applications
Activity Recognition for the Smart Hospital

IEEE Intelligent Systems
An Intelligent RFID System for Improving Elderly Daily Life Independent in Indoor Environment

ICOST '08 Proceedings of the 6th international conference on Smart Homes and Health Telematics
Learning and inferring transportation routines

AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
High-level goal recognition in a wireless LAN

AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
A hybrid discriminative/generative approach for modeling human activities

IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
The use of the area under the ROC curve in the evaluation of machine learning algorithms

Pattern Recognition
Simultaneous tracking and activity recognition (STAR) using many anonymous, binary sensors

PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing

Abnormal behaviours identification for an elder's life activities using dissimilarity measurements

Proceedings of the 4th International Conference on PErvasive Technologies Related to Assistive Environments

Quantified Score

Hi-index	0.00

Visualization

Abstract

Since the dramatic demographic change makes it inevitable that rapid aging of the population is an unprecedented phenomenon in Taiwan. A growing social problem is supporting older adults who want to live independently in their own homes. It needs a health assistance system to make them independent living up to a higher age. Recently, technological advancements have spurred various ideas and innovations to assist the elders living independently. In this paper, we proposed a homecare sensory system that uses RFID-based sensor networks to collect elder's daily activities and conducts the data into Hidden Markov model (HMM) and Support Vector Machines (SVMs) to estimate whether the elder's behavior is abnormal or not. Through detecting and distinguishing the abnormal behaviors of elder's daily activities, the system provides assistance on elder's independent living and improvement of aged quality of life.