Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering
Reference28 articles.
1. Bisio, I., Delfino, A., Lavagetto, F., & Sciarrone, A. (2016). Enabling IoT for in-home rehabilitation: Accelerometer signals classification methods for activity and movement recognition. IEEE Internet of Things Journal, 4662, 1–1.
2. Cao, L., Wang, Y., Zhang, B., Jin, Q., & Vasilakos, A. V. (2017). GCHAR: An efficient group-based context aware human activity recognition on smartphone. Journal of Parallel and Distributed Computing, 118, 67–80.
3. Rokni, S. A., & Ghasemzadeh, H. (2018). Autonomous training of activity recognition algorithms in mobile sensors: A transfer learning approach in context-invariant views. IEEE Transactions on Mobile Computing, 1233, 1–14.
4. Shoaib, M., Bosch, S., Incel, O., Scholten, H., & Havinga, P. (2015). A survey of online activity recognition using mobile phones. Sensors, 15(1), 2059–2085.
5. Morales, J., & Akopian, D. (2017). Physical activity recognition by smartphones, a survey. Biocybernetics and Biomedical Engineering, 37(3), 388–400.
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献