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Video based fall risk estimation and fall detection

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Presentation
  • Session
  • Thursday, 05 November 2015
  • 15:5 - 15:5
  • Duration: 34 mins
  • Publication date: 16 Dec 2015
  • Location: NA, Kingston University, Surrey, United Kingdom
  • Part of event TechAAL 2019

About the session

Active and assisted living (AAL) makes “use of information and communication technologies (ICT) in a person's daily living and working environment to enable them to stay active longer, remain socially connected and live independently into old age” (http://www.aal-europe.eu). Research efforts in AAL have increased rapidly to support independent living, as the social and economic impact of aging population becomes a more concrete problem in European society. The impact of the European demographic change is widely recognised making critical the need to address the problem both from a societal and economic standpoint. In the light of this, research into aging, age-related conditions and into supporting an aging population has become a priority for many governments around the world.

AAL aims to provide assistive solutions for people affected by a wide range of physical and cognitive challenges, in particular elderly persons. AAL applies the paradigm of the Internet of Things where sensing technology is embedded in objects, or in the environment or worn on the person to promote health and enhance well being, or to help maintain an independent life at home. Captured sensor data are analysed to detect activity and infer knowledge about the physical or cognitive status of a monitored person; recognising and classifying patterns, detecting trends, and unusual or anomalous behaviour.

AAL systems should be intelligent, able to learn and adapt to a wide variety of needs and requirements in real-time, synchronised with the specific need and designed and implemented to pre-empt, whenever possible, accidents and incidents that might occur in an assisted environment.

Nowadays, this is a very relevant area for research and innovation. Therefore, this event aims to provide assistive solutions and will serve as an important channel to present the latest advances in this area. Being a multidisciplinary area, the event would attract researchers and professionals with different expertise: technological, health care, business and social sciences.

Keywords:
  • Fall
  • Fall estimation
  • Fall risk assessment
  • Imaging
  • TechAAL
  • Vision
  • Vision & Imaging TPN
  • fall detection

Channels

Communities

Communities

Control

Control

Health care

Health care

Speaker

  • Prof. Bart Vanrumste

    Prof. Bart Vanrumste

    KU Leuven

    He received a Master in Electrical Engineering (ir.) from the Ghent University, Belgium in 1994. In 1998 he received a Master in Biomedical Engineering also from Ghent University. In 2001 he received a Ph.D. in Engineering (dr.) from the same institute. His Ph.D. work on ‘EEG Dipole Source Analysis in a Realistic Head Model’ was supervised by Prof. Ignace Lemahieu and Prof. Paul Boon. He worked as a Post-Doctoral Fellow from 2001 until 2003 at the Electrical & Computer Engineering Department of the University Of Canterbury, New Zealand under supervision of Prof. Philip J Bones and Prof. Richard D. Jones.From 2003 until 2005 he was Post-Doctoral Fellow at the Department of Electrical Engineering (ESAT) at KU Leuven. His supervisor was Prof. Sabine Van Huffel. In 2005 he was appointed Professor in the Engineering Technology Department at the “Katholieke Hogeschool Kempen” in Geel and the “Katholieke Hogeschool Limburg”, which have been integrated in the Faculty of Engineering Technology of KU Leuven. Bart Vanrumste currently teaches courses on Digital Signal Processing, Digital Image Processing and Medical Instrumentation. He is head of the Advanced Integrated Sensing Lab (AdvISe), associated member of the ESAT-STADIUS division and Principle Investigator of iMinds Future Health Department. His research interests is Decision Support in Healthcare in general and Ambient Assisted Living in particular. His current research activities focus among other on multimodal sensor integration for monitoring of older persons and patients with chronic illnesses at their homes. Bart Vanrumste has (co-)authored over 90 peer reviewed papers in international journals or conference proceedings. He is an active reviewer for many Biomedical Technology and Ambient Assisted Living journals. He also has been a reviewer for the IWT and STW.He was awarded for his contribution on the 9th World Congress of the International Society for Brain Electromagnetic Topography, the10th World Congress of the International Society for Brain Electromagnetic Topography and 4th International Conference on Bioelectromagnetism.Since 2013 he is chair of the IEEE Engineering in Medicine and Biology Benelux Chapter and member of the International Society for Bioelectromagnetism.
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