@inproceedings{e166728e48ce4ff8975cc02fb96c58b4,
title = "Acceleration trajectory analysis in remote gait monitoring",
abstract = "The study demonstrates part of an ambient assisted living system developed for the remote care of the elderly. Described methods and experiments involve acceleration-based trajectories analysis that yields a feature vector to be subjected to an expert system able to create an individual patient's model by learning high-level features of her/his motion. At this stage we have implemented a footstep detector that permits each foot movement to be analyzed separately and described in terms of predefined features. By mounting the sensors at five various locations on the subjects body, we have indicated areas that feature a high sensitivity to the measurement of abnormal step incidents. Our experiments demonstrate also features able to distinguish abnormal patient motion.",
author = "Pawel Badura and Ewa Pietka and Stanislaw Franiel",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 ; Conference date: 26-08-2014 Through 30-08-2014",
year = "2014",
month = nov,
day = "2",
doi = "10.1109/EMBC.2014.6944652",
language = "English",
series = "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4615--4618",
booktitle = "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014",
address = "United States",
}