Open Access
| Issue |
MATEC Web Conf.
Volume 227, 2018
2018 4th International Conference on Communication Technology (ICCT 2018)
|
|
|---|---|---|
| Article Number | 02019 | |
| Number of page(s) | 5 | |
| Section | Communication Technology and Information Engineering | |
| DOI | https://doi.org/10.1051/matecconf/201822702019 | |
| Published online | 14 November 2018 | |
- Liu R, Zhou J.Z, Liu M, et al. A wearable acceleration sensor system for gait recognition[C]//Proceedings of the 2007 2nd IEEE Conference on Industrial Electronics and Applications. 2007:2654-2659 [Google Scholar]
- Pan G, Zhang Y, Wu Z. Accelerometer-based gait recognition via voting by signature points[J]. Electronics Letters, 2009, 45(22):1116-1118 [CrossRef] [Google Scholar]
- Wang Fei, Wen Shiguang, Zhang Yuzhong, Jin Jizhun, Wu Chengdong. Automated classification of gait patterns based on time-frequency analysis[J]. Journal of University of Science and Technology Beijing, 2012, 34(1):31 [Google Scholar]
- Wang N, Ambikeairajah E, Celler B G, et al. Accelerometry based classification of gait patterns using empirical mode decomposition//Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing. Las Vegas, 2008:617 [Google Scholar]
- Chen M, Huang B F, Xu Y S. Intelligent shoes for abnormal gait detection//Proceedings of the 2008 IEEE International Conference on Robotics and Automation, Passdena, 2008:2019 [Google Scholar]
- Wang N, Ambikairajah E, Lovell N H, et al. Accelerometry based classification of walking patterns using time-frequency analysis//Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Lyon, 2007 [Google Scholar]
- Sekine M, Tamurs T, Fujimoto T, et al. Classification of walking pattern using acceleration waveform in elderly people//Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Chicago, 2000:1356 [Google Scholar]
- Khandelwal S, Wickstrom N. Gait event detection in real-world environment for long-term applications: Incorporating domain knowledge into time-frequency analysis[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2016, 24(12):1363-1372 [CrossRef] [Google Scholar]
- Li Y X, Wang X B, Qiao F. Gait authentication based on acceleration signals of ankle[J]. Chinese Journal of Electronics, 2011, 20(3):447-451 [Google Scholar]
- Lu yongle, Zhang Xin, Gong Shuang, et al. Recognition of multiple human motion patterns based on MEMS inertial sensors[J]. Journal of Chinese Inertial Technology, 2016, 24(5):589-594. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.