Monitoring behavior in home using a smart fall sensor and position sensors
By Norbert Noury, Thierry Hervé, Vincent Rialle, Gilles Virone, E. Mercier, G. Morey, A. I. Moro, T. Porcheron. 1st Annual International IEEE-EMBS Special Topic Conference on Microtechnologies in Medicine and Biology. Proceedings (Cat. No.00EX451), 2000
297 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Health, Toxicology and Mutagenesis, Pediatrics, Perinatology and Child Health
View Paper: https://www.semanticscholar.org/paper/e3157a3e997acdcfb24da17ae12e57bf11102fa5
How researchers see this paper
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In Computer Vision and Pattern Recognition
- Ling Shao
- Anthony Fleury
- Nicholas Luke Seed
- Aboul Ella Otifey Hassanien
- Norbert Noury
- Muhammad Mubashir
- J. Stankovic
- Jianbing Shen
Citations in the corpus
- Computer simulation of the activity of the elderly person living independently in a Health Smart Home (2012, methodology): “he experimental platform “Habitat Intelligent pour la Sante” HIS) was early developed by Noury [12] in Grenoble, France.”
- A survey on fall detection: Principles and approaches (2013, methodology): “A smart fall sensor was designed by Noury et al. for fall detection in [3] .”
- Accurate, Fast Fall Detection Using Gyroscopes and Accelerometer-Derived Posture Information (2009, background): “Noury [10] developed a fall detector consisting of three sensors: a tilt sensor to monitor body orientation, a piezoelectric accelerometer to (a) (b) Fig.”
- Wearable and Implantable Wireless Sensor Network Solutions for Healthcare Monitoring (2011, background): “Some of the health applications of sensor networks involve providing interfaces for the disabled, integrated patient monitoring, diagnostics, drug administration in hospitals, telemonitoring of human physiological data, and tracking and monitoring doctors and/or patients inside a hospital [34-36].”
- Fall detection - Principles and Methods (2007, background): “Noury [ 12 , 13], University of Grenoble-France, designed an autonomous sensor, attached under the armpit, which detects when the velocity exceeds a specific threshold, the sequence from a vertical posture to the lying posture, and the absence of movements after the fall.”