Human Movement Detection Based on Acceleration Measurements and k-NN Classification (CROSBI ID 529559)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Fudurić, Darko ; Siladi, Denis ; Žagar, Mario
engleski
Human Movement Detection Based on Acceleration Measurements and k-NN Classification
This paper addresses the problem of human movement detection and recognition using acceleration measurements and classification of acquired data with k-NN classification algorithm. For achieving the functionality of movement detection, two Crossbow’ s Mica2 motes are positioned on a person’ s body in order to measure the acceleration in the X, Y and Z axes. Several characteristic movements, such as falling, walking, running, sitting and standing can be successfully classified. We have developed a data acquisition, analysis and simulation environment based on the Tiny-OS, nesC and .NET technology. High level specialized movement detection tool was created. This tool can acquire, save, replay (simulate saved data), step-by-step present and classify all events during the measuring process. The paper presents the obtained results along with the system configuration and the initially required conditions.
acceleration; motes; Tiny-OS; movement detection; k-NN classification
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Podaci o prilogu
589-594-x.
2007.
objavljeno
Podaci o matičnoj publikaciji
Szumny, Rafal ; Bury, Marek
Varšava: Warsaw University of Technology
1-4244-0813-X
Podaci o skupu
The IEEE Region 8 International Conference on Computer as a Tool (EUROCON 2007)
predavanje
09.09.2007-12.09.2007
Varšava, Poljska