Fall detection for elderly person care in a vision-based home surveillance environment using a monocular camera

Author:

Feng Weiguo,Liu Rui,Zhu Ming

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Reference28 articles.

1. Yu, X.: Approaches and principles of fall detection for elderly and patient. In: e-Health Networking, Applications and Services, 2008. HealthCom 2008. 10th International Conference on IEEE, pp. 42–47. (2008)

2. Mubashir, M., Shao, L., Seed, L.: A survey on fall detection: principles and approaches. Neurocomputing 100, 144–152 (2013)

3. Kangas, M., Konttila, A., Lindgren, P., Winblad, I., Jämsä, T.: Comparison of low-complexity fall detection algorithms for body attached accelerometers. Gait & Posture 28(2), 285–291 (2008)

4. Nguyen, T.T., Cho, M.C., Lee, T.S.: Automatic fall detection using wearable biomedical signal measurement terminal. In: Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE, pp. 5203–5206. (2009)

5. Bourke, A., Lyons, G.: A threshold-based fall-detection algorithm using a bi-axial gyroscope sensor. Med. Eng. Phys. 30(1), 84–90 (2008)

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