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Collaborative Fall Detection Using Smart Phone and Kinect

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Abstract

Humanfall detection has attracted broad attentions as sensors and mobile devices are increasingly adopted in real-life scenarios such as smart homes. The complexity of activities in home environments pose severe challenges to the fall detection research with respect to the detection accuracy. We propose a collaborative detection platform that combines two subsystems: a threshold-based fall detection subsystem using mobile phones and a support vector machine (SVM)-based fall detection subsystem using Kinects. Both subsystems have their respective confidence models and the platform detects falls by fusing the data of both subsystems using two methods: the logical rules-based and D-S evidence fusion theory-based methods. We have validated the two confidence models based on mobile phone and Kinect, which achieve the accuracy of 84.17% and 97.08%, respectively. Our collaborative fall detection approach achieves the best accuracy of 100%.

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Acknowledgments

Funded by the 2014 Microsoft Research Asia Collaborative Research Program.

Author information

Authors and Affiliations

  1. Harbin Institute of Technology, Harbin, China

    Xue Li, Lanshun Nie & Hanchuan Xu

  2. Singapore Management University, Singapore, Singapore

    Xianzhi Wang

Authors
  1. Xue Li
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  2. Lanshun Nie
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  3. Hanchuan Xu
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  4. Xianzhi Wang
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Corresponding author

Correspondence to Xue Li.

Appendix

Appendix

Table 1 Sensor information
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Table 2 Fall detection results (smart phone tied to the waist)
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Table 3 Fall detection results (smart phone placed in a loose trousers pocket)
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Table 4 Fall detection results (smart phones placed in a tight trousers pocket)
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Table 5 Fall detection results (smart phone placed in a coat pocket)
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Table 6 Fall detection results using the Kinect
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Table 7 Fall sensitively collaborative statistical results
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Table 8 Fall dully collaborative statistical results
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Table 9 The accuracy of the two methods in different situations
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Table 10 The accuracy of D-S evidence theory fusion results
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Li, X., Nie, L., Xu, H. et al. Collaborative Fall Detection Using Smart Phone and Kinect. Mobile Netw Appl 23, 775–788 (2018). https://doi.org/10.1007/s11036-018-0998-y

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