Activity classification for real-time wearable systems : effect of window length, sampling frequency and number of features on classifier performance

statement of authorship
Ardo Allik, Kristjan Pilt, Deniss Karai, Ivo Fridolin, Mairo Leier, Gert Jervan
location of publication
[S.l.]
publisher
year of publication
pages
p. 460-464 : ill
conference name, date
2016 IEEE EMBS Conference on Biomedical Engineering and Sciences, 4-8 December, 2016
conference location
Kuala Lumpur, Malaysia
keyword
sampling frequency
window length
classification features
ISBN
978-1-4673-7791-1
notes
Bibliogr.: 15 ref
language
inglise
Allik, A., Pilt, K., Karai, D., Fridolin, I., Leier, M., Jervan, G. Activity classification for real-time wearable systems : effect of window length, sampling frequency and number of features on classifier performance // 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES) : Kuala Lumpur, 4-8 December 2016. [S.l.] : IEEE, 2016. p. 460-464 : ill. https://doi.org/10.1109/IECBES.2016.7843493