A real-time fall detection model based on BlazePose and improved ST-GCN
Author:
Publisher
Springer Science and Business Media LLC
Subject
Information Systems
Link
https://link.springer.com/content/pdf/10.1007/s11554-023-01377-6.pdf
Reference31 articles.
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2. Zigel, Y., Litvak, D., Gannot, I.: A method for automatic fall detection of elderly people using floor vibrations and sound—proof of concept on human mimicking doll falls. IEEE Trans. Biomed. Eng. 56, 2858–2867 (2009). https://doi.org/10.1109/TBME.2009.2030171
3. Salman Khan, M., Yu, M., Feng, P., Wang, L., Chambers, J.: An unsupervised acoustic fall detection system using source separation for sound interference suppression. Signal Process. 110, 199–210 (2015). https://doi.org/10.1016/j.sigpro.2014.08.021
4. Lee, J.-S., Tseng, H.-H.: Development of an enhanced threshold-based fall detection system using smartphones with built-in accelerometers. IEEE Sensors J. 19, 8293–8302 (2019). https://doi.org/10.1109/JSEN.2019.2918690
5. Xi, X., Jiang, W., Lü, Z., Miran, S.M., Luo, Z.-Z.: Daily activity monitoring and fall detection based on surface electromyography and plantar pressure. Complexity 2020, 1–12 (2020). https://doi.org/10.1155/2020/9532067
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