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

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3841
Author(s):  
Chengyin Liu ◽  
Zhaoshuo Jiang ◽  
Xiangxiang Su ◽  
Samuel Benzoni ◽  
Alec Maxwell
Keyword(s):  
Floor Vibration

The authors wish to add one reference [...]

scholarly journals Feasibility of Using Floor Vibration to Detect Human Falls

2020 ◽  
Vol 18 (1) ◽  
pp. 200
Author(s):  
Yu Shao ◽  
Xinyue Wang ◽  
Wenjie Song ◽  
Sobia Ilyas ◽  
Haibo Guo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Human Body ◽  
Nearest Neighbor ◽  
Body Movement ◽  
Modern Society ◽  
Recognition System ◽  
Machine Learning Algorithms ◽  
K Nearest Neighbor ◽  
Study Results ◽  
Floor Vibration

With the increasing aging population in modern society, falls as well as fall-induced injuries in elderly people become one of the major public health problems. This study proposes a classification framework that uses floor vibrations to detect fall events as well as distinguish different fall postures. A scaled 3D-printed model with twelve fully adjustable joints that can simulate human body movement was built to generate human fall data. The mass proportion of a human body takes was carefully studied and was reflected in the model. Object drops, human falling tests were carried out and the vibration signature generated in the floor was recorded for analyses. Machine learning algorithms including K-means algorithm and K nearest neighbor algorithm were introduced in the classification process. Three classifiers (human walking versus human fall, human fall versus object drop, human falls from different postures) were developed in this study. Results showed that the three proposed classifiers can achieve the accuracy of 100, 85, and 91%. This paper developed a framework of using floor vibration to build the pattern recognition system in detecting human falls based on a machine learning approach.

Vibration Behavior and Serviceability of Arched Prestressed Concrete Truss Due to Human Activity

2018 ◽  
Vol 18 (12) ◽  
pp. 1850146 ◽  
Author(s):  
Jiang Li ◽  
Jiepeng Liu ◽  
Liang Cao ◽  
Y. Frank Chen
Keyword(s):  
Steady State ◽  
Prestressed Concrete ◽  
Natural Frequencies ◽  
Current Trend ◽  
Threshold Values ◽  
Transient Vibration ◽  
Vibration Behavior ◽  
Detailed Evaluation ◽  
Floor Systems ◽  
Floor Vibration

The current trend toward longer spans and lighter floor systems, combined with reduced damping and new activities, have resulted in an increasing complaints on floor vibration from building owners and occupants. Heel-drop, jumping, and walking impacts, which may lead to discomfort problems in daily life, were imposed on a large-span arched prestressed concrete truss (APT) girder system studied. The natural frequencies, peak acceleration, average root-mean-square acceleration (ARMS), maximum transient vibration value (MTVV), and perception factor for the girder were obtained and checked against the existing codes and standards. The purpose of this paper is to provide researchers and engineers with a detailed evaluation on the vibration behavior of the APT girder under different human activities, with a comprehensive review on the relevant criteria and some suggestions. Lastly, the following threshold peak accelerations are suggested: 650[Formula: see text]mm/s2 for transient heel-drop impact, 1450[Formula: see text]mm/s2 for transient jumping impact, and 250[Formula: see text]mm/s2 for steady-state walking. In addition, the threshold values of 90[Formula: see text]mm/s2 and 50[Formula: see text]mm/s2 are suggested for MTVV and ARMS, respectively, under steady-state walking.

scholarly journals EXPERIMENTAL MODAL ANALYSIS OF A FLOOR OF A WOODEN HOUSE An Analysis of the floor vibration which is predominanted with high frequency by running train

2009 ◽  
Vol 15 (29) ◽  
pp. 151-154
Author(s):  
Yasuyuki SANO ◽  
Yasuhiko IZUMI ◽  
Shigenori YOKOSHIMA ◽  
Ryuta TOMITA ◽  
Toshihisa ISHIBASHI ◽  
...  
Keyword(s):  
Modal Analysis ◽  
High Frequency ◽  
Experimental Modal Analysis ◽  
Wooden House ◽  
Floor Vibration
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