Investigation of personal variations in activity recognition using miniature inertial sensors and magnetometers
Proceedings of the 20th IEEE Conference on Signal Processing and Communications Applications, 2012
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In 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.
Time domain analysis