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Radar classifications of consecutive and contiguous human gross‐motor activities
- Source :
- IET Radar, Sonar & Navigation. 14:1417-1429
- Publication Year :
- 2020
- Publisher :
- Institution of Engineering and Technology (IET), 2020.
-
Abstract
- The authors consider radar classifications of activities of daily living, which can prove beneficial in fall detection, analysis of daily routines, and discerning physical and cognitive human conditions. They focus on contiguous motion classifications, which follow and commensurate with the human ethogram of possible motion sequences. Contiguous motions can be closely connected with no clear time gap separations. In the proposed approach, they utilise the Radon transform applied to the radar range-map to detect the translation motion, whereas an energy detector is used to provide the onset and offset times of in-place motions, such as sitting down and standing up. It is shown that motion classifications give different results when performed forward and backward in time. The number of classes, thereby classification rates, considered by a classifier, is made varying depending on the current motion state and the possible transitioning activities in and out of the state. Two different examples are given to delineate the performance of the proposed approach under typical sequences of human motions.
- Subjects :
- Offset (computer science)
Contextual image classification
Radon transform
business.industry
Signal reconstruction
Computer science
Doppler radar
020206 networking & telecommunications
Pattern recognition
02 engineering and technology
law.invention
Time–frequency analysis
law
0202 electrical engineering, electronic engineering, information engineering
Artificial intelligence
Electrical and Electronic Engineering
Radar
business
Classifier (UML)
Subjects
Details
- ISSN :
- 17518792
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- IET Radar, Sonar & Navigation
- Accession number :
- edsair.doi...........7e4f153ff99d1710ef88fa24119f62e3