Yurtman, ArasBarshan, Barshan2016-02-082016-02-082012-04http://hdl.handle.net/11693/28211Conference Name: 20th IEEE Conference on Signal Processing and Communications Applications, 2012Date of Conference: 18-20 April 2012This paper provides a comparative study on the different techniques of classifying human activities using a tag-based radio-frequency (RF) localization system. Non-uniformly-sampled data containing position measurements of the tags on the body is first converted to a uniformly-sampled one using different curve-fitting algorithms. Then, the data is partitioned into segments. Finally, various classification techniques are applied to classify human activities. Curve-fitting, segmentation, and classification methods are compared using different cross-validation techniques and the combination resulting in the best performance is presented. The results indicate that the system demonstrates acceptable performance despite the fact that tag-based RF localization is not very accurate.TurkishClassification methodsClassification techniqueComparative studiesCross-validation techniqueHuman activitiesHuman activity recognitionLocalization systemRadio frequenciesTag-basedSignal processingCurve fittingConference Paper10.1109/SIU.2012.6204571