Defense: Slip, Stumble, and Fall Accidents

2009 ◽  
pp. 89-89-13
Author(s):  
AD Rutledge
Keyword(s):  
Fall Accidents

Fall Detection via Inaudible Acoustic Sensing

2021 ◽  
Vol 5 (3) ◽  
pp. 1-21
Author(s):  
Jie Lian ◽  
Xu Yuan ◽  
Ming Li ◽  
Nian-Feng Tzeng
Keyword(s):  
Continuous Wave ◽  
Detection System ◽  
Fall Detection ◽  
Superior Performance ◽  
Medical Assistance ◽  
Acoustic Sensing ◽  
Value Decomposition ◽  
Human Motions ◽  
Audio Device ◽  
Fall Accidents

The fall detection system is of critical importance in protecting elders through promptly discovering fall accidents to provide immediate medical assistance, potentially saving elders' lives. This paper aims to develop a novel and lightweight fall detection system by relying solely on a home audio device via inaudible acoustic sensing, to recognize fall occurrences for wide home deployment. In particular, we program the audio device to let its speaker emit 20kHz continuous wave, while utilizing a microphone to record reflected signals for capturing the Doppler shift caused by the fall. Considering interferences from different factors, we first develop a set of solutions for their removal to get clean spectrograms and then apply the power burst curve to locate the time points at which human motions happen. A set of effective features is then extracted from the spectrograms for representing the fall patterns, distinguishable from normal activities. We further apply the Singular Value Decomposition (SVD) and K-mean algorithms to reduce the data feature dimensions and to cluster the data, respectively, before input them to a Hidden Markov Model for training and classification. In the end, our system is implemented and deployed in various environments for evaluation. The experimental results demonstrate that our system can achieve superior performance for detecting fall accidents and is robust to environment changes, i.e., transferable to other environments after training in one environment.

scholarly journals Fatal Fall Accidents in Small Building Construction Projects

2020 ◽  
Author(s):  
Yilmaz Hatipkarasulu ◽  
Harrison Pierce ◽  
Suat Gunhan ◽  
Rui Liu
Keyword(s):  
Construction Projects ◽  
Building Construction ◽  
Small Building ◽  
Fall Accidents

Trends of Fall Accidents in the U.S. Construction Industry

2017 ◽  
Vol 143 (8) ◽  
pp. 04017043 ◽  
Author(s):  
Youngcheol Kang ◽  
Sohaib Siddiqui ◽  
Sung Joon Suk ◽  
Seokho Chi ◽  
Changwan Kim
Keyword(s):  
Construction Industry ◽  
The U.S ◽  
Fall Accidents

Causal factors and risk assessment of fall accidents in the U.S. construction industry: A comprehensive data analysis (2000–2020)

2022 ◽  
Vol 146 ◽  
pp. 105537
Author(s):  
Yahia Halabi ◽  
Hu Xu ◽  
Danbing Long ◽  
Yuhang Chen ◽  
Zhixiang Yu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Data Analysis ◽  
Construction Industry ◽  
Causal Factors ◽  
Comprehensive Data ◽  
The U.S ◽  
Fall Accidents

scholarly journals Ambient Intelligence to Improve Construction Site Safety: Case of High-Rise Building in Thailand

2020 ◽  
Vol 17 (21) ◽  
pp. 8124
Author(s):  
Kriengsak Panuwatwanich ◽  
Natapit Roongsrisoothiwong ◽  
Kawin Petcharayuthapant ◽  
Sirikwan Dummanonda ◽  
Sherif Mohamed
Keyword(s):  
Risk Factors ◽  
Ambient Intelligence ◽  
Light Emitting Diode ◽  
Behavioural Change ◽  
High Rate ◽  
Construction Site ◽  
High Rise ◽  
High Rise Building ◽  
Safety Case ◽  
Fall Accidents

The relatively high rate of injuries in construction is not surprising, as site work by its very nature ranks highly on fundamental risk factors. Working at heights often magnifies these risk factors. The literature reveals that falls from heights accounts for a large percentage of injuries in construction worldwide. Thailand is no exception, where fall accidents constitute the majority of high-rise construction accidents despite preventive measures being implemented. This paper examines how the use of a simple Ambient Intelligence (AmI) system—a device comprising a microcontroller, microwave sensors, Light Emitting Diode (LED) and audio alarm—could help to affect safety behavioural change of on-site construction workers in order to decrease the potential for fall accidents. An experiment was conducted at a high-rise building construction site in Bangkok, Thailand to examine the effectiveness of the AmI in helping workers mitigate the risk of falling from heights. The analysis of the data collected over two work weeks from the pre- and post-AmI application using X-bar charts and one-way analysis of variance (ANOVA) revealed a significant reduction of about 78% in the number of workers passing through the fall hazard zones. The finding established the potential of a simple AmI for reducing the risk of fall accidents.

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