Advertisement

A Plantar Inclinometer Based Approach to Fall Detection in Open Environments

  • Jianfei Sun
  • Zumin Wang
  • Liming Chen
  • Baofeng Wang
  • Changqing Ji
  • Shuai Tao
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 647)

Abstract

In this paper, we report a threshold-based method of fall detection using plantar inclinometer sensor, which provides us the information of angle variations during walking, and of angle status after a fall. The angle variations and status are collected in three-dimensional space. We analyzed the normal range of angle variations during walking, and selected the thresholds by testing the distribution of plantar angles of falls. In the experiments, thresholds were selected from plantar angles of fall status in four directions: forward, backward, left and right. Using the selected thresholds, we detected falls of five subjects in different situations for five hundred times and obtained the average detection rate of 85.4 %.

Keywords

Sensor Module Angle Variation Fall Detection Subsequent Injury Privacy Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant No. 61501076)

References

  1. 1.
    Angelini, L., Caon, M., Carrino, S., Bergeron, L., Nyffeler, N., Jean-Mairet, M., Mugellini, E.: Designing a desirable smart bracelet for older adults. In: Proceedings of the 2013 ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication, pp. 425–434. ACM (2013)Google Scholar
  2. 2.
    Bourke, A.K., Van de Ven, P.W., Chaya, A.E., OLaighin, G.M., Nelson, J.: Testing of a long-term fall detection system incorporated into a custom vest for the elderly. In: Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE, pp. 2844–2847. IEEE (2008)Google Scholar
  3. 3.
    Chen, D., Zhang, Y., Feng, W., Li, X.: A wireless real-time fall detecting system based on barometer and accelerometer. In: 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA), pp. 1816–1821. IEEE (2012)Google Scholar
  4. 4.
    Chen, G.C., Huang, C.N., Chiang, C.Y., Hsieh, C.J., Chan, C.T.: A reliable fall detection system based on wearable sensor and signal magnitude area for elderly residents. In: Aging Friendly Technology for Health and Independence, pp. 267–270. Springer (2010)Google Scholar
  5. 5.
    Chen, J., Kwong, K., Chang, D., Luk, J., Bajcsy, R.: Wearable sensors for reliable fall detection. In: 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005, pp. 3551–3554. IEEE (2006)Google Scholar
  6. 6.
    Cockerham, W.C.: This aging society (1991)Google Scholar
  7. 7.
    Dunning, K., Moomaw, C., Flaherty, M.L., Osborne, J., James, M.L., Worrall, B.B., Woo, D.: Abstract t p279: falls after intracerebral hemorrhage. Stroke 46(Suppl 1), ATP279–ATP279 (2015)Google Scholar
  8. 8.
    Elveru, R.A., Rothstein, J.M., Lamb, L.R.: Goniometric reliability in a clinical setting. Subtalar and ankle joint measurements. Phys. Ther. 68(5), 672–677 (1988)Google Scholar
  9. 9.
    Gao, L., Cao, X., Zhang, M.: The study on community health education of empty nest elderly. Engineering 5(10), 137 (2013)CrossRefGoogle Scholar
  10. 10.
    Guimaraes, R., Isaacs, B.: Characteristics of the gait in old people who fall. Disabil. Rehabil. 2(4), 177–180 (1980)Google Scholar
  11. 11.
    Leardini, A., O’Connor, J.J.: C.F.G.S.: A geometric model of the human ankle joint. J. Biomech. 32(6), 585591 (1999)Google Scholar
  12. 12.
    Liu, X.Q., Kuang, L.J., Li, J.C., Huang, J.Z.: The design and production of panels control system based on the angle sensor sca60c. Mech. Electr. Eng. Technol. 8, 011 (2012)Google Scholar
  13. 13.
    Miaou, S.G., Sung, P.H., Huang, C.Y.: A customized human fall detection system using omni-camera images and personal information. In: 1st Transdisciplinary Conference on Distributed Diagnosis and Home Healthcare, 2006. D2H2, pp. 39–42. IEEE (2006)Google Scholar
  14. 14.
    Noury, N.: A smart sensor for the remote follow up of activity and fall detection of the elderly. In: Biology 2nd Annual International IEEE-EMB Special Topic Conference on Microtechnologies in Medicine & amp, pp. 314–317. IEEE (2002)Google Scholar
  15. 15.
    P.H.A.: Report on Seniors’ Falls in Canada [electronic Resource]. Division of Aging and Seniors, Public Health Agency of Canada (2005)Google Scholar
  16. 16.
    Rougier, C., Meunier, J., St-Arnaud, A., Rousseau, J.: Monocular 3d head tracking to detect falls of elderly people. In: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006. EMBS’06, pp. 6384–6387. IEEE (2006)Google Scholar
  17. 17.
    Tao, S., Kudo, M., Nonaka, H.: Privacy-preserved behavior analysis and fall detection by an infrared ceiling sensor network. Sensors 12(12), 16920–16936 (2012)CrossRefGoogle Scholar
  18. 18.
    Tian, Q., Meng, C.: An empirical investigation of rural empty-nesters in chongqing and a construction of service system. Asian Agric. Res. 5(02) (2013)Google Scholar
  19. 19.
    Wenlong, Z., Qing, G., Baoshan, L.: Design of landslide warning system. In: 2011 Third International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), vol. 1, pp. 974–977. IEEE (2011)Google Scholar
  20. 20.
    Williams, A., Ganesan, D., Hanson, A.: Aging in place: fall detection and localization in a distributed smart camera network. In: Proceedings of the 15th international conference on Multimedia, pp. 892–901. ACM (2007)Google Scholar
  21. 21.
    Wong, W.K., Lim, H.L., Loo, C.K., Lim, W.S.: Home alone faint detection surveillance system using thermal camera. In: 2010 Second International Conference on Computer Research and Development, pp. 747–751. IEEE (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jianfei Sun
    • 1
  • Zumin Wang
    • 1
  • Liming Chen
    • 2
  • Baofeng Wang
    • 1
  • Changqing Ji
    • 1
  • Shuai Tao
    • 1
  1. 1.Information and Engineering CollegeDalian UniversityDalianChina
  2. 2.School of Computer Science and InformaticsDe Montfort UniversityLeicesterUK

Personalised recommendations