Covariance matrix based fall detection from multiple wearable sensors
- 25 April 2019
- journal article
- research article
- Published by Elsevier BV in Journal of Biomedical Informatics
- Vol. 94, 103189
- https://doi.org/10.1016/j.jbi.2019.103189
Abstract
No abstract availableThis publication has 22 references indexed in Scilit:
- Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review PaperJournal of Sensors, 2015
- Shape feature encoding via Fisher Vector for efficient fall detection in depth-videosApplied Soft Computing, 2015
- Fall Detection Using Smartphone Audio FeaturesIEEE Journal of Biomedical and Health Informatics, 2015
- Covariance Descriptors for 3D Shape Matching and RetrievalPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- A Ubiquitous and Low-Cost Solution for Movement Monitoring and Accident Detection Based on Sensor FusionSensors, 2014
- Classification of covariance matrices using a Riemannian-based kernel for BCI applicationsNeurocomputing, 2013
- Detection of falls using accelerometers and mobile phone technologyAge and Ageing, 2011
- Log‐Euclidean metrics for fast and simple calculus on diffusion tensorsMagnetic Resonance in Medicine, 2006
- Region Covariance: A Fast Descriptor for Detection and ClassificationLecture Notes in Computer Science, 2006
- A Riemannian Framework for Tensor ComputingInternational Journal of Computer Vision, 2006