Optics and Precision Engineering, Volume. 25, Issue 1, 182(2017)

Research on fall detection system based on support vector machine

PEI Li-ran*... JIANG Ping-ping and YAN Guo-zheng |Show fewer author(s)
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    References(13)

    [1] [1] LIN S I, CHANG K CH, LEE H C, et al.. Problems and fall risk determinants of quality of life in older adults with increased risk of falling [J]. Geriatrics & Gerontology International, 2015, 15(5): 579-587.

    [2] [2] SCHWICKERT L, BECKER C, LINDEMANN C, et al..Fall detection with body-worn sensors a systematic review [J]. Zeitschrift für Gerontologie und Geriatrie, 2013, 46(8): 706-719.

    [3] [3] ISABEL N F, CARLOS L, LUIS P, et al.. Exploring smartphone sensors for fall detection [J].Mobile User Experience, 2016, 5(1): 1-17.

    [4] [4] KANGAS M, KONTTILA A, LINDGREN P, et al. Comparison of low-complexity fall detection algorithms for body attached accelerometers [J]. Gait & Posture, 2008, 285-291.

    [5] [5] LAI CH F, CHAGN S Y, CHAO H CH, et al.. Detection of cognitive injured body region using multiple triaxial accelerometers for elderly falling [J].IEEE Sensor Joutnal, 2011, 11(3): 763-770.

    [6] [6] YU H, LIANG L H, WANG S J, et al.. Error compensation for high precision reference encoder based on RBF neural networks [J].Infrared and Laser Engineering, 2014, 43(12): 4123-4127.(in Chinese)

    [13] [13] BOURKE A K, VAN de VEN, GAMBLE M, et al.. Evaluation of waist-mounted tri-axial accelerometer based fall-detection algorithms during scripted and continuous unscripted activities [J]. Journal of Biomechanics, 2010, 43(15): 3051-3057.

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    PEI Li-ran, JIANG Ping-ping, YAN Guo-zheng. Research on fall detection system based on support vector machine[J]. Optics and Precision Engineering, 2017, 25(1): 182

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    Paper Information

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    Received: Aug. 24, 2016

    Accepted: --

    Published Online: Mar. 10, 2017

    The Author Email: Li-ran PEI (woaiwojiaPLR@sjtu.edu.cn)

    DOI:10.3788/ope.20172501.0182

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