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Title
The Effect of Personalization on Smartphone-Based Fall Detectors
Authors
Keywords
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Journal
SENSORS
Volume 16, Issue 1, Pages 117
Publisher
MDPI AG
Online
2016-01-18
DOI
10.3390/s16010117
References
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Related references
Note: Only part of the references are listed.- A comparison of public datasets for acceleration-based fall detection
- (2015) Raul Igual et al. MEDICAL ENGINEERING & PHYSICS
- Older adults’ perceptions of technologies aimed at falls prevention, detection or monitoring: A systematic review
- (2014) Helen Hawley-Hague et al. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
- Detecting Falls as Novelties in Acceleration Patterns Acquired with Smartphones
- (2014) Carlos Medrano et al. PLoS One
- Smartphone-Based Solutions for Fall Detection and Prevention: Challenges and Open Issues
- (2014) Mohammad Habib et al. SENSORS
- The risk of falling in young adults with neurological conditions: a systematic review
- (2013) Alessia Saverino et al. DISABILITY AND REHABILITATION
- Fall detection with body-worn sensors
- (2013) L. Schwickert et al. ZEITSCHRIFT FUR GERONTOLOGIE UND GERIATRIE
- Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls
- (2012) Fabio Bagalà et al. PLoS One
- Fall Classification by Machine Learning Using Mobile Phones
- (2012) Mark V. Albert et al. PLoS One
- A smartphone-based fall detection system
- (2012) Stefano Abbate et al. Pervasive and Mobile Computing
- LIBSVM
- (2012) Chih-Chung Chang et al. ACM Transactions on Intelligent Systems and Technology
- How smartphones are changing the face of mobile and participatory healthcare: an overview, with example from eCAALYX
- (2011) Maged Boulos et al. Biomedical Engineering Online
- Automatic individual calibration in fall detection – an integrative ambulatory measurement framework
- (2011) Jian Liu et al. COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING
- Comparison of acceleration signals of simulated and real-world backward falls
- (2010) J. Klenk et al. MEDICAL ENGINEERING & PHYSICS
- Mobile phone-based pervasive fall detection
- (2010) Jiangpeng Dai et al. Personal and Ubiquitous Computing
- Anomaly detection
- (2009) Varun Chandola et al. ACM COMPUTING SURVEYS
- A proposal for the classification and evaluation of fall detectors
- (2008) N. Noury et al. IRBM
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