Predicting slips and falls considering required and available friction

This study investigated the relationship among measurements of friction, the biomechanics of gait, and actual slip and fall events. The goal was to develop a method for estimating the probability of slips and falls based on measurements of available friction and required friction. Five subjects wear...

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Veröffentlicht in:Ergonomics 1999-12, Vol.42 (12), p.1619-1633
Hauptverfasser: Hanson, James P., Redfern, Mark S., Mazumdar, Mainak
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creator Hanson, James P.
Redfern, Mark S.
Mazumdar, Mainak
description This study investigated the relationship among measurements of friction, the biomechanics of gait, and actual slip and fall events. The goal was to develop a method for estimating the probability of slips and falls based on measurements of available friction and required friction. Five subjects wearing safety harnesses walked down a ramp at various angles with either a tile or carpeted surface under dry, wet or soapy conditions. Ramp angles of 0°, 10° and 20° were used to vary the shear and normal foot force requirements. The dynamic coefficient of friction (DCOF) of shoe, floor surface and contaminant interfaces was measured. Required friction was assessed by examining the foot forces during walking trials when no slips occurred. Slips with recoveries and slips resulting in falls were recorded and categorized using a force plate and high-speed video camera. These data were then incorporated into a logistic regression to model the probability of a slip or fall event occurring based on the difference between the COF required by the foot forces generated and the measured DCOF. The results showed that the number of slip and fall events increased as the difference between the required COF and the measured DCOF increased. The logistic regression model fit the data well, resulting in an estimate of the probability of a slip or fall event based on the difference between the measured and required friction. This type of model could be used in the future to evaluate slip resistance measurement devices under various environments and assist in the design of safer work environments.
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The goal was to develop a method for estimating the probability of slips and falls based on measurements of available friction and required friction. Five subjects wearing safety harnesses walked down a ramp at various angles with either a tile or carpeted surface under dry, wet or soapy conditions. Ramp angles of 0°, 10° and 20° were used to vary the shear and normal foot force requirements. The dynamic coefficient of friction (DCOF) of shoe, floor surface and contaminant interfaces was measured. Required friction was assessed by examining the foot forces during walking trials when no slips occurred. Slips with recoveries and slips resulting in falls were recorded and categorized using a force plate and high-speed video camera. These data were then incorporated into a logistic regression to model the probability of a slip or fall event occurring based on the difference between the COF required by the foot forces generated and the measured DCOF. The results showed that the number of slip and fall events increased as the difference between the required COF and the measured DCOF increased. The logistic regression model fit the data well, resulting in an estimate of the probability of a slip or fall event based on the difference between the measured and required friction. 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The goal was to develop a method for estimating the probability of slips and falls based on measurements of available friction and required friction. Five subjects wearing safety harnesses walked down a ramp at various angles with either a tile or carpeted surface under dry, wet or soapy conditions. Ramp angles of 0°, 10° and 20° were used to vary the shear and normal foot force requirements. The dynamic coefficient of friction (DCOF) of shoe, floor surface and contaminant interfaces was measured. Required friction was assessed by examining the foot forces during walking trials when no slips occurred. Slips with recoveries and slips resulting in falls were recorded and categorized using a force plate and high-speed video camera. These data were then incorporated into a logistic regression to model the probability of a slip or fall event occurring based on the difference between the COF required by the foot forces generated and the measured DCOF. 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Allied Health Premium</collection><collection>MEDLINE - Academic</collection><jtitle>Ergonomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hanson, James P.</au><au>Redfern, Mark S.</au><au>Mazumdar, Mainak</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting slips and falls considering required and available friction</atitle><jtitle>Ergonomics</jtitle><addtitle>Ergonomics</addtitle><date>1999-12-01</date><risdate>1999</risdate><volume>42</volume><issue>12</issue><spage>1619</spage><epage>1633</epage><pages>1619-1633</pages><issn>0014-0139</issn><eissn>1366-5847</eissn><coden>ERGOAX</coden><abstract>This study investigated the relationship among measurements of friction, the biomechanics of gait, and actual slip and fall events. The goal was to develop a method for estimating the probability of slips and falls based on measurements of available friction and required friction. Five subjects wearing safety harnesses walked down a ramp at various angles with either a tile or carpeted surface under dry, wet or soapy conditions. Ramp angles of 0°, 10° and 20° were used to vary the shear and normal foot force requirements. The dynamic coefficient of friction (DCOF) of shoe, floor surface and contaminant interfaces was measured. Required friction was assessed by examining the foot forces during walking trials when no slips occurred. Slips with recoveries and slips resulting in falls were recorded and categorized using a force plate and high-speed video camera. These data were then incorporated into a logistic regression to model the probability of a slip or fall event occurring based on the difference between the COF required by the foot forces generated and the measured DCOF. The results showed that the number of slip and fall events increased as the difference between the required COF and the measured DCOF increased. The logistic regression model fit the data well, resulting in an estimate of the probability of a slip or fall event based on the difference between the measured and required friction. This type of model could be used in the future to evaluate slip resistance measurement devices under various environments and assist in the design of safer work environments.</abstract><cop>London</cop><cop>Washington, DC</cop><pub>Taylor &amp; Francis Group</pub><pmid>10643404</pmid><doi>10.1080/001401399184712</doi><tpages>15</tpages></addata></record>
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source MEDLINE; Periodicals Index Online; Taylor & Francis Journals Complete
subjects Accidental Falls - prevention & control
Adult
Applied physiology
Biological and medical sciences
Biomechanical Phenomena
Biomechanics
Coefficient
Ergonomics
Ergonomics. Work place. Occupational physiology
Fall
Falls
Friction
Gait
Gait - physiology
Human physiology applied to population studies and life conditions. Human ecophysiology
Humans
Logistic Models
Male
Mathematical models
Medical sciences
Occupational safety
Probability
Ramp
Regression analysis
Slip
Space life sciences
title Predicting slips and falls considering required and available friction
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