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Multimodal detection of human interaction events in a nursing home environment

Published: 13 October 2004 Publication History

Abstract

In this paper, we propose a multimodal system for detecting human activity and interaction patterns in a nursing home. Activities of groups of people are firstly treated as interaction patterns between any pair of partners and are then further broken into individual activities and behavior events using a multi-level context hierarchy graph. The graph is implemented using a dynamic Bayesian network to statistically model the multi-level concepts. We have developed a coarse-to-fine prototype system to illustrate the proposed concept. Experimental results have demonstrated the feasibility of the proposed approaches. The objective of this research is to automatically create concise and comprehensive reports of activities and behaviors of patients to support physicians and caregivers in a nursing facility.

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cover image ACM Conferences
ICMI '04: Proceedings of the 6th international conference on Multimodal interfaces
October 2004
368 pages
ISBN:1581139950
DOI:10.1145/1027933
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 13 October 2004

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Author Tags

  1. group activity
  2. human interaction
  3. medical care
  4. multimodal
  5. stochastic modeling

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Overall Acceptance Rate 453 of 1,080 submissions, 42%

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  • (2018)An interaction-embedded HMM framework for human behavior understandingIEEE Transactions on Information Technology in Biomedicine10.1109/TITB.2010.205206114:5(1236-1246)Online publication date: 25-Dec-2018
  • (2018)Multimodal human-computer interactionComputer Vision and Image Understanding10.1016/j.cviu.2006.10.019108:1-2(116-134)Online publication date: 31-Dec-2018
  • (2013)UWB Indoor Location for Monitoring Dementia PatientsInternational Journal of Ambient Computing and Intelligence10.4018/ijaci.20131001045:4(45-59)Online publication date: Oct-2013
  • (2011)A Case-Driven Ambient Intelligence System for Elderly in-Home Assistance ApplicationsIEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews10.1109/TSMCC.2010.205245641:2(179-189)Online publication date: 1-Mar-2011
  • (2011)Using Indoor Location to Assess the State of Dementia PatientsProceedings of the 2011 Seventh International Conference on Intelligent Environments10.1109/IE.2011.22(32-39)Online publication date: 25-Jul-2011
  • (2010)Situation-Aware Patient Monitoring in and around the Bed Using Multimodal Sensing IntelligenceProceedings of the 2010 Sixth International Conference on Intelligent Environments10.1109/IE.2010.31(128-133)Online publication date: 18-Jul-2010
  • (2010)Ambient and wearable sensing for gait classification in pervasive healthcare environmentsThe 12th IEEE International Conference on e-Health Networking, Applications and Services10.1109/HEALTH.2010.5556563(240-245)Online publication date: Jul-2010
  • (2010)Assistance Instruments Detection Using Geometry Constrained Knowledge for Health Care Centers2010 5th International Conference on Future Information Technology10.1109/FUTURETECH.2010.5482662(1-5)Online publication date: May-2010
  • (2010)Body and Visual Sensor Fusion for Motion Analysis in Ubiquitous Healthcare SystemsProceedings of the 2010 International Conference on Body Sensor Networks10.1109/BSN.2010.38(250-254)Online publication date: 7-Jun-2010
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