Yurtman, ArasBarshan, Billur2016-02-082016-02-082012-04http://hdl.handle.net/11693/28203Conference Name: 20th IEEE Conference on Signal Processing and Communications Applications, 2012Date of Conference: 18-20 April 2012In this paper, data acquired from five sensory units mounted on the human body, each containing a tri-axial accelerometer, gyroscope, and magnetometer, during 19 different human activities is used to calculate inter-subject and inter-activity variations using different methods and the results are summarized in various forms. Absolute, Euclidean, and dynamic time-warping distances are used to assess the similarity of the signals. The comparisons are made using the raw and normalized time-domain data, raw and normalized feature vectors. Firstly, inter-subject distances are averaged out per activity and per subject. Based on these values, the "best" subject is defined and identified according to his/her average distance to the others. Then, the averages and standard deviations of inter-activity distances are presented per subject, per unit, and per sensor. Moreover, the effects of removing the mean and the different distance measures on the results are discussed. © 2012 IEEE.TurkishActivity recognitionAverage distanceDistance measureEuclideanFeature vectorsHuman activitiesHuman bodiesInertial sensorSensory unitStandard deviationTime-domain dataTriaxial accelerometerSignal processingTime domain analysisMagnetometersConference Paper10.1109/SIU.2012.6204573