ACS Applied Computer Science

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REMOTE HEALTH MONITORING: FALL DETECTION

Falling is a serious health issue among the elderly population; it can result in critical injuries like hip fractures. Immobilization caused by injury or unconsciousness means that the victim cannot summon help themselves. With elderly who live alone, not being found for hours after a fall is quite common and drastically increases the significance of fall-induced injuries. With an aging Baby Boomer population, the incidence of falls will only rise in the next few decades. The objective of this paper is to design and create a fall detection system. The system consists of a monitoring device that links wirelessly with a laptop. The device is able to accurately distinguish between fall and non-fall.

  • APA 6th style
Abdulhamid, M., & Peter, D. (2020). Remote health monitoring: fall detection. Applied Computer Science, 16(1), 95-102. doi:10.23743/acs-2020-08
  • Chicago style
Abdulhamid, Mohanad, and Deng Peter. "Remote Health Monitoring: Fall Detection." Applied Computer Science 16, no. 1 (2020): 95-102.
  • IEEE style
M. Abdulhamid and D. Peter, "Remote health monitoring: fall detection," Applied Computer Science, vol. 16, no. 1, pp. 95-102, 2020, doi: 10.23743/acs-2020-08.
  • Vancouver style
Abdulhamid M, Peter D. Remote health monitoring: fall detection. Applied Computer Science. 2020;16(1):95-102.