An Analysis of the Accuracy of Wearable Sensors for Classifying the Causes of Falls in Humans

  title={An Analysis of the Accuracy of Wearable Sensors for Classifying the Causes of Falls in Humans},
  author={Omar Aziz and Stephen N. Robinovitch},
  journal={IEEE Transactions on Neural Systems and Rehabilitation Engineering},
Falls are the number one cause of injury in older adults. Wearable sensors, typically consisting of accelerometers and/or gyroscopes, represent a promising technology for preventing and mitigating the effects of falls. At present, the goal of such “ambulatory fall monitors” is to detect the occurrence of a fall and alert care providers to this event. Future systems may also provide information on the causes and circumstances of falls, to aid clinical diagnosis and targeting of interventions. As… CONTINUE READING
Highly Cited
This paper has 212 citations. REVIEW CITATIONS
36 Citations
27 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 36 extracted citations

212 Citations

Citations per Year
Semantic Scholar estimates that this publication has 212 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 27 references

Video-based recording of the cause of falls among older adults in long term care

  • S. N. Robinovitch, F. Feldman, D. Wan, O. Aziz, T. Sarraf
  • presented at the 19th Int. Conf. Int. Soc…
  • 2009
1 Excerpt

An introduction to kernelbased learning algorithms

  • K. Tsuda, B. Scholkopf
  • Pattern Recognition and Machine Learning
  • 2006

An optimum accelerometer configuration and simple algorithm for accurately detecting falls

  • A. K. Bourke, C. N. Scanaill, K. M. Culhane, J.V.O. Brien, G. M. Lyons
  • presented at the 24th IASTED Int. Conf. Biomed…
  • 2006
2 Excerpts

Similar Papers

Loading similar papers…