AVAILABLE COEFFICIENT OF FRICTION ASSOCIATED WITH
DIFFERENT SLIP PROBABILITIES FOR LEVEL WALKING
Wen-Ruey Chang, Simon Matz and Chien-Chi Chang
Liberty Mutual Research Institute for Safety, 71 Frankland Road, Hopkinton, MA 01748 USA

Different slip probabilities for level straight walking were investigated whencomparing a given available coefficient of friction (ACOF) value with thestochastic distribution of the required coefficient of friction (RCOF). The RCOF
of each foot for each walking condition by each participant was assumed to have anormal distribution. The slip probability was calculated by averaging thecumulative probabilities of the RCOF exceeding a given ACOF from both feet andevaluated at five levels, one out of 20, 200, 10,000, 100,000 and 1,000,000. The
ANOVA results showed that both age group and walking speed had a statisticallysignificant effect on the ACOF associated with all slip probabilities evaluated. TheACOF value obtained in an earlier study was less than that with the current study
for higher slip probabilities, and greater for lower slip probabilities.

Introduction
In occupational injuries, falls on the same level are a serious problem. In 2010, costs in the US for
disabling workplace injuries due to falls on the same level were estimated to be approximately
8.61 billion US dollars or 16.9% of the total cost burden for all and are listed as the second leading
sources of occupational injuries (Liberty Mutual Research Institute for Safety, 2012). Courtney etal. (2001) reported that slipperiness or slipping contributed to between 40 and 50% of fall-related
injuries.
The available coefficient of friction (ACOF) represents the maximum coefficient of friction(COF) that can be supported at the shoe and floor interface without a slip, while required COF(RCOF) represents COF needed at the shoe and floor interface to support human locomotion. Aslip may occur when the RCOF value for an activity is lower than the ACOF (Chang, 2004).
However, the RCOF is not a constant for each individual, even under the same walking conditions,as demonstrated by Chang et al. (2008, 2012b).
Pye and Harrison (1997) investigated the level of the ACOF associated with different slip
probabilities. Their results showed that the ACOF values were 0.24, 0.27, 0.29, 0.34 and 0.36 forthe slip probabilities of one out of 20, 200, 10,000, 100,000 and 1,000,000, respectively, forstraight walking. No details were given of how their data were obtained. It was understood,
however, that their results were derived from the data reported by Harper et al. in 1961 (Roys,2011). In an attempt to understand the method used by Pye and Harrison (1997) by verifying theirresults, we undertook a preliminary analysis using the same Harper et al. (1961) data of both feetfrom 48 participants (35 males and 13 females) and demonstrated that Pye and Harrison hadconstructed a normal distribution based on the RCOF data. The ACOF value at which thecumulative probability of the RCOF exceeding the ACOF was calculated for five probability
levels.

- 247 -

RCOF can be affected by walking speed, footwear type, age, gender and foot (Chang et al.,2012a, 2012b). Even under the same walking condition, there can be individual differences in theRCOF. Chang et al. (2012b) investigated the stochastic distribution of the RCOF with 50participants who walked under four walking conditions. The results of the Kolmogorov-Smirnov
two-sample test showed that 76% of the RCOF data had a difference in distribution between both
feet for the same participant under each walking condition. The results of the KolmogorovSmirnov goodness-of-fit test showed that most of the distribution of the RCOF appeared to have agood match with the normal distribution (85.5%). By combining the RCOF data of different
individuals, different walking conditions and different feet, the standard deviation would besubstantially larger than that at the individual levels. In this study, approaches similar to that ofPye and Harrison (1997) were applied to the RCOF under each walking condition at the individuallevel with the consideration of individual contributions from each foot. The objective was toexplore the effects of walking speed, footwear, gender and age group on the ACOF associated withdifferent slip probabilities.

Methods
Data obtained in the previous study by Chang et al. (2012b) were used in the current study.
Twenty five females and 25 males without active musculoskeletal disorders took part in thisexperiment. Three age groups were used to classify participants: 18 – 25 years old, 26 - 54, 55
and older, resulting in 7, 29, and 14 participants in each respective group. The mean andstandard deviation of weight, height and age at each level of gender and age group are shown in
Table 1. The protocol was approved by an institutional review board. The participants gave
written informed consent. Details of the experimental setup with three force plates weredescribed in Chang et al. (2008).
Table 1. Average and standard deviation of weight, height and age for each level of ageand gender
Variable
Level
Weight (kg)Height (cm)Age (years)
Genderfemale
64.8 ± 9.16
162.4 ± 5.54
45.2 ± 13.9
male
80.9 ± 14.07 172.7 ± 8.46
45.4 ± 13.2
Age Group (years)
18-25
65.3 ± 16.96 163.0 ± 8.50
20.6 ± 3.15
26-54
72.8 ± 13.93 169.2 ± 8.87
44.1 ± 6.64
55 and higher
76.7 ± 13.09 166.5 ± 8.33
60.0 ± 3.76
The participants walked at self-selected normal and fast speeds. A sneaker and a leather
loafer were the two types of footwear used. In this experiment, there were four different
walking conditions: loafer-fast (LF), loafer-normal (LN), sneaker-fast (SF) and sneaker-normal(SN). These four walking conditions were randomized for each participant.
All the force plate data, sampled at 1000 Hz, were processed with the fourth order zero-lag
Butterworth low pass filter with a cut-off frequency of 36 Hz. The method used to identify theRCOF was explained in detail by Chang et al. (2012b).
Based on the results obtains in the previous study (Chang et al., 2012b), it was assumed thatthe RCOF of each foot under each walking condition by each participant had a normaldistribution. The ACOF was obtained so that the average of the cumulative probabilities of theRCOF exceeding the given ACOF from both feet was equal to each slip probability value. TheACOF was represented by a constant and the stochastic distribution of RCOF of an individual
under a given walking condition was represented by the probability density functions pR andp L for right and left feet, respectively. The cumulative probability of the RCOF exceeding
the given ACOF was calculated by averaging the cumulative probabilities of the RCOF
exceeding the given ACOF for both feet as shown below:- 248 -P( ACOF )f1 f(³pR ( x)dx  ³pL ( y )dy ) .
ACOF
ACOF
2

Identical slip probabilities used by Pye and Harrison (1997) were used in the current study, i.e.,
one out of 20, 200, 10,000, 100,000 and 1,000,000.
A mixed linear model (models with both fixed and random effects) with four-way analysisof variance (ANOVA) was used for data analysis. The age group, footwear type, gender andwalking speed were considered as fixed effects with participant as a random effect. Post-hoc
analysis for the variable of age group (18 - 25, 26 - 54, 55 years and older) was carried out with
the Bonferroni adjustment to counteract multiple comparisons. The ANOVA for each slip
probability level was carried out individually.

Results and discussion
There were a total of 30,968 successful strikes. The averaged sample size, mean, standard
deviation, skewness and kurtosis, and the minimum and maximum of the RCOF for each footunder each walking condition across 50 participants are shown in Table 2.
The Kolmogorov-Smirnov goodness-of-fit test was used to check if the normal distribution
was a good representation for the RCOF for each foot under each walking condition for every
participant. Among 400 data pools by 50 participants, four walking conditions and two feet,
344 (86%) cases reached statistical significance for a match with a normal distribution.
Table 2. Averaged sample size (n), mean, standard deviation (SD), skewness and kurtosis,
and the minimum (Min) and maximum (Max) of the required coefficient of friction foreach foot under each walking condition across 50 participants
Condition FootnMean
SDSkewness Kurtosis
MinMaxLF
left
78 0.2394
0.0138
0.018
0.096
0.143
0.352
LF
right
78 0.2398
0.01700.139-0.097
0.148
0.353
LN
left
78 0.2172
0.0127-0.039
0.271
0.120
0.324
LN
right
77 0.2163
0.0153
0.211
0.057
0.124
0.332
SF
left
77 0.2456
0.0138-0.074
0.244
0.112
0.361
SF
right
77 0.2489
0.0159-0.059-0.007
0.145
0.368
SN
left
78 0.2286
0.0124
0.091
0.305
0.130
0.326
SN
right76 0.2275
0.0147
0.247
0.058
0.149
0.413
Note: The kurtosis values presented reflect the deviations from a normal distribution.
LF=Loafer Fast, LN=Loafer Normal, SF=Sneaker Fast, SN=Sneaker Normal
The results of the four-way ANOVA show that only the speed (p < 0.001) and age group (p= 0.009 ~ 0.029) reached the statistical significance for all slip probabilities evaluated, but theirinteraction did not reach statistical significance. For all levels of slip probability, the ACOF
values associated with age group 2 (26-54) had a statistically significant difference from that ofage group 3 (55 and older) with p < 0.05. For the lowest two probability levels (1/100,000 and1/1,000,000), the ACOF values of age group 1 (18 - 25) also had a statistically significant
difference from those of age group 3 with p < 0.05. The mean and standard deviation of theACOF values for each level of age group, footwear, gender and walking speed are shown in
Table 3. The results show that the ACOF value for the age group 55 and older was lower thanthat for the other two age groups, while the ACOF value associated with a fast walking speed
was higher than that for normal.
Pye and Harrison (1997) merged the data of the RCOF from both feet of 48 participants anddid not monitor walking speeds, which would have led to an increase in the standard deviationof the RCOF. The variation was investigated at the level of each foot for each walking
condition by each participant in the current study. Therefore, individual contribution to slip- 249 -probability from each foot was considered. The ACOF was shown to be significantly affectedby the walking speed and age group. Compared with the results obtained in the current study,
the ACOF value reported by Pye and Harrison (1997) for straight walking was lower for higher
slip probabilities such as one out of 20 and 200, while the opposite was true for lower slip
probabilities such as one out of 100,000 and 1,000,000.
Table 3. The means with standard deviations (in parentheses) of the available coefficient offriction (ACOF) associated with different slip probabilities obtained in the current study.
The results of Pye and Harrison (1997) are included for comparison.
1/200
0.280 (0.0356)
0.280 (0.0332)†
0.266 (0.0306)

Slip Probability
1/10,000
0.301 (0.0385)
0.298 (0.0383)†
0.283 (0.0332)

1/100,000
0.311 (0.0401)†0.307 (0.0409)†
0.291 (0.0347)

1/1,000,000
0.320 (0.0417)†
0.315 (0.0433)†
0.299 (0.0361)

Age group

18-25
26-54
55 and older

1/20
0.262 (0.0338)
0.264 (0.0293)†0.252 (0.0290)

Footwearloafersneaker

0.256 (0.0306)
0.265 (0.0292)

0.272 (0.0333)
0.280 (0.0328)

0.291 (0.0372)
0.298 (0.0377)

0.300 (0.0392)
0.307 (0.0402)

0.308 (0.0410)
0.314 (0.0425)

Genderfemalemale

0.257 (0.0303)
0.264 (0.0298)

0.273 (0.0342)
0.278 (0.0321)

0.293 (0.0395)
0.296 (0.0355)

0.302 (0.0421)
0.304 (0.0373)

0.311 (0.0446)
0.312 (0.0390)

fast
normalPye and Harrison (1997)

0.272 (0.0266)‡
0.249 (0.0288)
0.24

0.289 (0.0289)‡
0.263 (0.0325)
0.27

0.308 (0.0323)‡
0.281 (0.0375)
0.29

0.317 (0.0341)‡
0.289 (0.0401)
0.34

0.326 (0.0358)‡
0.297 (0.0425)
0.36

Walking speedG† - statistically significantly different from group 3 (55 and older) (p < 0.05)‡ - statistically significantly different from normal speed (p < 0.05)

References
Chang, W.R. (2004). A statistical model to estimate the probability of slip and fall incidents.
Safety Science, 42 (9), 779-789.
Chang, W.R., Chang, C.C., Matz, S., & Lesch, M.F. (2008). A methodology to quantify thestochastic distribution of friction coefficient required for level walking. Applied
Ergonomics, 39 (6), 766-771.
Chang, W.R., Matz, S., & Chang, C.C. (2012a). A comparison of required coefficient of friction
for both feet in level walking. Safety Science, 50 (2), 240 - 243.
Chang, W.R., Matz, S., & Chang, C.C. (2012b). Stochastic distribution of the required
coefficient of friction for level walking – an in-depth study. Ergonomics, 55 (8), 937 - 945.
Courtney, T.K., Sorock, G.S., Manning, D.P., Collins, J.W., & Holbein-Jenny, M.A. (2001).
Occupational slip, trip, and fall-related injuries - can the contribution of slipperiness be
isolated? Ergonomics, 44 (13), 1118-1137.
Harper, F.C., Warlow, W.J., & Clarke, B.L. (1961). The forces applied to the floor by the foot inwalking, National Building Research Paper 32, DSIR, Building Research Station. London:
Her Majesty’s Stationary Office.
Liberty Mutual Research Institute for Safety (2012). 2012 Workplace Safety Index, available at
http://www.libertymutual.com/researchinstitute. From Research to Reality, 15(3).
Pye, P.W., & Harrison, H.W. (1997). BRE building elements, Floors and Flooring, 34. Watford,United Kingdom: HIS Building Research Establishment.
Roys, M. (2011). Private communication.

- 250 -