Title :
Movement recognition using the accelerometer in smartphones
Author :
Lau, Sian Lun ; David, Klaus
Author_Institution :
Dept. of Commun. Technol., Univ. of Kassel, Kassel, Germany
Abstract :
The area of activity recognition is essential for context-aware systems. Previous and current investigations demonstrate that the accelerometer is suitable for accurate movement and activity recognition. Since smartphones are used by people in their daily lives, they can be seen as an attractive sensor device for the purpose of activity recognition. In our work, experiments have been carried out to investigate the suitability of the built-in accelerometer by comparing the influences of classification algorithms, features and the combination of sampling rates and window sizes for features extraction have on the classification accuracy. Obtained results indicate that smartphones similar to the test device provide good accuracy in recognizing common movements.
Keywords :
accelerometers; feature extraction; gesture recognition; mobile radio; ubiquitous computing; accurate movement; activity recognition; attractive sensor device; built-in accelerometer; classification accuracy; classification algorithms; context-aware systems; features extraction; movement recognition; sampling rates; smartphones; Accelerometers; Accuracy; Classification algorithms; Context; Legged locomotion; Smart phones; activity recognition; classification; context-awareness; smartphone;
Conference_Titel :
Future Network and Mobile Summit, 2010
Conference_Location :
Florence
Print_ISBN :
978-1-905824-16-8