The Community for Technology Leaders
2012 16th International Symposium on Wearable Computers (2012)
Newcastle UK
June 18, 2012 to June 22, 2012
ISSN: 1550-4816
ISBN: 978-0-7695-4697-1
pp: 114-115
ABSTRACT
Using inertial body-worn sensors, we propose a segmentation approach to detect when a user changes actions. We use Adaboost to combine three threshold-based detectors: force/gravity ratios, peaks of autocorrelation, and local minimums of velocity. Experimenting with the CMU Multi-Modal Activity Database, we find that the first two features are the most important, and our combination approach improves performance with an acceptable level of granularity.
INDEX TERMS
Detectors, Correlation, Gravity, Acceleration, Measurement uncertainty, Wearable computers
CITATION
Yuanchun Shi, Yue Shi, Xia Wang, "Inertial Body-Worn Sensor Data Segmentation by Boosting Threshold-Based Detectors", 2012 16th International Symposium on Wearable Computers, vol. 00, no. , pp. 114-115, 2012, doi:10.1109/ISWC.2012.27
92 ms
(Ver 3.3 (11022016))