Abstract
Stair falls on construction sites are leading causes of fatal injuries, and the dangers for workers are greater because they usually carry heavy loads. Nevertheless, there are very few studies related to stair falls among construction workers. The purpose of this study was to detect near fall incidence during stair descent and analyze the changes in weight bearing and center of pressure. A total of 10 healthy males participated in this study. Three experimental conditions were set up to analyze stair falls: natural descent (E1), weighted descent (E2), and near fall-simulated descent (E3). While walking down the stairs, subjects wore a three-axis accelerometer sensor attached to a Smart Helmet and a pair of textile pressure sensors (insole) placed inside Smart Shoes. The collected data were analyzed for: (1) whole body balance, (2) plantar pressure distribution, (3) head tilt pattern, and (4) conformity between the helmet and insole sensors. The results showed that our proposed smart helmet and smart shoes have relatively good performance in terms of classifying the weight-shifting patterns in the head and the feet during stair descent. The results of this study may be helpful in detecting near falls of workers on construction sites.
Highlights
The construction industry often obliges workers to operate in poor working conditions, in which serious accidents occur due to high labor intensity, long working hours, and dangerous working environments [1]
Out of theoffive steps taken down the(Smart stairs on each foot, the middle three steps were analyzed; three peak plantar pressure values from each foot were temporally matched with the SVM data of the head movements
Out of the five steps taken down the stairs on each foot, the middle three steps were analyzed; three In E1 and E2, the head movement pattern and the plantar pressure changes were well-matched peak plantar pressure values from each foot were temporally matched with the SVM data of the head bilaterally, but in E3, the head movements were visibly different according to bilaterally different leg movements
Summary
The construction industry often obliges workers to operate in poor working conditions, in which serious accidents occur due to high labor intensity, long working hours, and dangerous working environments [1]. It is inherently a dangerous work environment and potentially contributes to workplace injuries. Falls on construction sites can cause bone fractures and bruises, and it is especially important to assess the victim as soon as possible when a fall occurs. This is because transportation to a medical institution can help prevent further injuries. Many studies have been conducted to develop sensors and systems to monitor fall
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