@inproceedings{liu2019realtime_har,
  //note = {Best Student Paper},
  title = {A Wearable Real-time Human Activity Recognition System using Biosensors Integrated into a Knee Bandage},
  author = {Liu, Hui and Schultz, Tanja},
  booktitle = {Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 1: BIODEVICES},
  pages = {47--55},
  organization = {INSTICC},
  publisher = {SciTePress},
  year = {2019},
  isbn = {978-989-758-353-7},
  issn = {2184-4305},
  doi = {10.5220/0007398800470055},
  url={https://www.csl.uni-bremen.de/cms/images/documents/publications/LiuSchultz_Biodevices2019.pdf},
  abstract = {This work introduces an innovative wearable real-time Human Activity Recognition (HAR) system. The system processes and decodes various biosignals that are captured from biosensors integrated into a knee bandage. The presented work includes (1) the selection of an appropriate equipment in terms of devices and sensors to capture human activity-related biosignals in real time, (2) the experimental tuning of system parameters which balances recognition accuracy with real-time performance, (3) the intuitive visualization of biosignals as well as n-best recognition results in the graphical user interfaces, and (4) the on-the-air extensions for rapid prototyping of applications. The presented system recognizes seven daily activities: sit, stand, stand up, sit down, walk, turn left and turn right. The amount of activity classes to be recognized can be easily extended by the "plug-and-play" function. To the best of our knowledge, this is the first work which demonstrates a real-time HAR system using biosensors integrated into a knee bandage.}
}