@article{ref1,
title="Intelligent music player for bike sport using electroencephalogram and global positioning system sensors",
journal="Sens. Lett.",
year="2013",
author="Liu, Ning-Han and Hsu, Hsiang-Ming and Chu, Hsuan-Chin and Hsu, Shu-Hao",
volume="11",
number="5",
pages="772-780",
abstract="This study combined cycling with music and proposed a music player for cyclists, which allow cyclists to listen to music so as to adjust their emotions and stress during cycling, and reduce the time scale of negative emotion in the sport process. The system is based on the Fuzzy Inference System (FIS), combined with EEG and G PS sensors to measure the sport data of cyclists. The save sport emotion and behavior of cyclists are predicted according to the sensor data. The suitable type of music works are arranged into the play list. Moreover, a music filtering mechanism is developed to filter out the music that the user dislikes according to the previous listening history. As we know, the system is not proposed in the previous researches. From the experiment results, the system really reduces the most of bikers' negative emotion.<p /> <p>Language: en</p>",
language="en",
issn="1546-198X",
doi="10.1166/sl.2013.2678",
url="http://dx.doi.org/10.1166/sl.2013.2678"
}