A Smart and Passive Floor-Vibration Based Fall Detector for Elderly
By M. Alwan, P. Rajendran, S. Kell, D. Mack, S. Dalal, M. Wolfe, R. Felder. 2006 2nd International Conference on Information & Communication Technologies, 2006
447 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Physical Therapy, Sports Therapy and Rehabilitation
View Paper: https://www.semanticscholar.org/paper/1e51bd9f3fef571ada32bbe95e891861908c73f6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- Alain St-Arnaud
- Ling Shao
- Nicholas Luke Seed
- Jean Meunier
- Lionel Ming-shuan Ni
- Muhammad Mubashir
- Caroline Rougier
- Jacqueline Rousseau
In Computer Vision and Pattern Recognition
- Ling Shao
- Nicholas Luke Seed
- Muhammad Mubashir
- Alain St-Arnaud
- Daqing Zhang
- Dominic K. C. Ho
- Jean Meunier
- Mihail Popescu
In Physical Therapy, Sports Therapy and Rehabilitation
- Alain St-Arnaud
- Ling Shao
- Nicholas Luke Seed
- Jean Meunier
- Muhammad Mubashir
- Caroline Rougier
- Jacqueline Rousseau
Citations in the corpus
- A Method for Automatic Fall Detection of Elderly People Using Floor Vibrations and Sound—Proof of Concept on Human Mimicking Doll Falls (2009, background): “The idea of floor vibrations was also explored by Alwan et al. [ 16 ], however, our proposed solution is different”
- A Microphone Array System for Automatic Fall Detection (2012, background): “Some nonwearable devices include floor vibration sensors [9]–[11], video cameras [12], [13], IR cameras [14], and bed sensors [15].”
- Survey on Fall Detection and Fall Prevention Using Wearable and External Sensors (2014, unknown): “[35] developed a floor-vibration fall detector.”
- A survey on fall detection: Principles and approaches (2013, background): “in [10] that developed the working principle and the design of a floor vibration-based fall detector.”
- WiFall: Device-free fall detection by wireless networks (2017, background): “tems using ambient devices [3], [4] leverage floor vibration caused by a fall to detect a risky situation.”
- A Survey on Ambient Intelligence in Health Care (2013, unknown): “They also rely on techniques such as floor vibration detection and ambient audio analysis to detect possible fall [150], [151].”
- Robust Video Surveillance for Fall Detection Based on Human Shape Deformation (2011, background): “Floor vibrationbased detectors could be a promising solution but they depend upon the floor dynamics and are still in their infancy [6].”
- A Survey on Ambient-Assisted Living Tools for Older Adults (2013, unknown): “Ambient fall detection systems rely on sensors such as PIR sensors, pressure sensors, as well as floor vibration detection and audio analysis [155], [156].”
- RT-Fall: A Real-Time and Contactless Fall Detection System with Commodity WiFi Devices (2017, background): “For elderswho live alone and independently, about 50 percent of the falls occur within their own homes [1], thus timely and automatic detection of falls has long been the research goal in the assistive living community.”