Granger-causality: An efficient single user movement recognition using a smartphone accelerometer sensor
| Autor: | Eduardo Rodriguez-Martinez, Andrés Ferreyra-Ramírez, Juan Villegas-Cortez, Carlos Avilés-Cruz |
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| Rok vydání: | 2019 |
| Předmět: |
Computer science
SIGNAL (programming language) 02 engineering and technology Accelerometer 01 natural sciences Acceleration Granger causality Artificial Intelligence Human–computer interaction 0103 physical sciences Signal Processing 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition 010306 general physics Representation (mathematics) Lying Mobile device Software |
| Zdroj: | Pattern Recognition Letters. 125:576-583 |
| ISSN: | 0167-8655 |
| Popis: | In this research paper, a novel framework is proposed to classify and analyze human activities. Granger-causality is applied on a smartphone for the recognition of single user activity. It is done in two different ways. In the first one, human activity is recognized on the basis of casual relationships among X-Y-Z Cartesian axes while the second one is based on the casual relationships among the activities. The graphical representation allowed the understanding of mutual dependencies among activities. A tri-axial accelerometer sensor embedded in a smartphone is used to record the acceleration signal. Six human activities successfully classified are walking, walking-upstairs, walking-downstairs, sitting, standing and lying. |
| Databáze: | OpenAIRE |
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