You are currently viewing a new version of our website. To view the old version click .
Sensors
  • Correction
  • Open Access

2 June 2021

Correction: Liu et al. Detection of Human Fall Using Floor Vibration and Multi-Features Semi-Supervised SVM. Sensors 2019, 19, 3720

,
,
,
and
1
Department of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen 518055, China
2
School of Engineering, San Francisco State University, San Francisco, CA 94132, USA
*
Author to whom correspondence should be addressed.
The authors wish to add one reference [] to this paper [].
On page 1, the original sentences are as follows: Progress toward new methods without cameras has been made through the use of accelerometer sensors mounted on the structure to capture floor vibration for human activities detection [13–15].
Correction to be: Progress toward new methods without cameras has been made through the use of accelerometer sensors mounted on the structure to capture floor vibration for human activities detection [13–16].
The sequential references originally in the paper (i.e., [16–47]) will shift by one (i.e., [17–48]).
The authors apologize for any inconvenience caused and state that the scientific conclusions are unaffected. The original article has been updated.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Davis, B.T. Characterization of Human-Induced Vibrations. Ph.D. Dissertation, University of South Carolina, Columbia, SC, USA, 2016. Available online: https://scholarcommons.sc.edu/etd/3770 (accessed on 25 January 2019).
  2. Liu, C.; Jiang, Z.; Su, X.; Benzoni, S.; Maxwell, A. Detection of human fall using floor vibration and multi-features semi-supervised SVM. Sensors 2019, 19, 3720. [Google Scholar] [CrossRef]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Article Metrics

Citations

Article Access Statistics

Multiple requests from the same IP address are counted as one view.