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Keynote Speaker: Prof. Norbert Noury

Keynote Speaker: Prof. Norbert  Noury

Keynote Speaker: Prof. Norbert Noury

Stand, Walk, Fall… automatic detection of the fall of the elderly subject in daily activities

Norbert Noury is a Full Professor at University of Lyon, France. His lectures cover Electronics and Physics for Medical devices. His research activity is in the field of eHealth, connected health sensors, Ambient assistive living environments. After his MSc in Electronics at Grenoble University (1985), he occupied several R&D engineer positions  in various industrial companies for 8 years. He defended his PhD in applied Physics (1992) and joined the University of Grenoble (1993), where he initiated new research in Health Smart Homes and wearable health sensors and was teaching electrical engineering. In 2008 he moved to University of Lyon, where he took various responsibilities - Director of the Department of Biomedical Engineering at Polytech'Lyon School of Engineering, Director of the Master in Regulations of Medical devices, Director of the BSc in Medical Technologies. Since 2008, he also joined the Biomedical Sensors research team at INL-INSA Lyon where he developed his activities in eHealth, launched a Living Lab for Health and developed innovative wearable non-invasive Smart Sensors for continuous monitoring of actimetrics, fall detection, thermal measurement, Non invasive blood pressure. He is also an entrepreneur who contributed to launching 2 Start Up, exploiting his work and (15) patents. He guided 20 PhD students, authored or co-authored more than 200 scientific papers (H index 36), and is a recognized expert at the European Commission. He also is frequently involved in the organization committees of international scientific events (IEEE-EMBC2007, IEEE-Healthcom2010, pHealth2011, member of the steering Committee of the IEEE-Healthcom conference since 2010,…).

https://univ-lyon1.academia.edu/NorbertNoury

Stand, Walk, Fall… automatic detection of the fall of the elderly subject in daily activities

Elderly patients who could not rise up or activate an alert device are particularly at risk and should be monitored with caution. That encourages the development of autonomous devices that enable earliest detection of falls. Because they sometimes have no apparent direct consequence, falls tend to be overly trivialized by doctors and patients, and are thus largely underestimated. Falls represent a real public health problem because they are not only the main factor of morbidity and mortality in the elderly but also of entry into institutions. Falls in the elderly are therefore, along with degenerative dementia, one of the priority areas for research in gerontology. To improve detection capabilities, systems have combined different techniques: three-dimensional accelerometers, inclinometers, vibration sensor, and angular velocity detector during transitions between vertical and horizontal positions. Recent research has confirmed that three-dimensional accelerometers can reduce the number of false alarms. Data collected during simulated falls, led to the conclusion that locating the sensor on the patient's chest was generally more appropriate for greater detection reliability. The autonomous detection of fall with body worn accelerometers is satisfactory, although a sensitivity and a specificity of 100% are not achievable, knowing the diversity of the situations of fall. Still the data fusion with contextual information can improve these characteristics. The direct analysis of a fall is complex because the phenomenon is ill-defined. The artificial intelligence approach is an attractive way, because it doesn’t need the detailed understanding of the complex process in itself. But it needs the collection of a personalized database of signals before to correctly classify the fall situation, which hinders its application on the field with patients which need the detection since the first inclusion. The design of an autonomous wearable detector must include the study of the usage to respect intimacy and non-stigmatization of the wearer.