A Novel Energy-Efficient Approach for Human Activity Recognition

Lingxiang Zheng, Dihong Wu, Xiaoyang Ruan, Shaolin Weng, Ao Peng, Biyu Tang, Hai Lu, Haibin Shi, Huiru Zheng

Research output: Contribution to journalArticle

15 Citations (Scopus)
2 Downloads (Pure)
Original languageEnglish
Pages (from-to)2064
JournalSensors
Volume17
Issue number9
DOIs
Publication statusPublished - 8 Sep 2017

Keywords

  • activity recognition
  • low power consumption
  • low sampling rate
  • energy-efficient classifier

Cite this

Zheng, L., Wu, D., Ruan, X., Weng, S., Peng, A., Tang, B., Lu, H., Shi, H., & Zheng, H. (2017). A Novel Energy-Efficient Approach for Human Activity Recognition. Sensors, 17(9), 2064. https://doi.org/10.3390/s17092064