A fall detection method based on multi-threshold value and EML learning machine

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Yang Jia,Gao Tongyue,Huang Kaida

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Reference5 articles.

1. A survey on fall detection: Principles and approaches

2. Kangas, M., Konttila, A., Winblad, I., Jamsa, and T: Determination of simple thresholds for accelerometry-based parameters for fall detection. In: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2007, pp. 1367–1370 (2007).

3. Mehner, S., Klauck, R., Koenig, and H: Location-independent fall detection with smartphone. In: Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2013, pp. 11:1–11:8 (2013).

4. Xinxi Zhang, Rong Zhang, Meifeng Guo, Luna Mi, Yongjian Zhang, Mingliang Song, Xinxi Zhang, An Algorithm for Improving the Convergence Rate of Attitude by Using GPS Heading Angle in MEMS-INS/GPS Integrated Navigation. 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC), 2013, pp. 2856–2860.

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