The present study examined whether a new footwear outsole with tread blocks and a hybrid rubber surface pattern, composed of rough and smooth surfaces, could increase slip resistance and reduce the risk of fall while walking on a wet floor surface. A drag test was performed to measure static and dynamic coefficient of friction (SCOF and DCOF, respectively) values for the footwear with the hybrid rubber surface pattern outsole and two types of commercially available boots that are conventionally used in food factories and restaurant kitchens with respect to a stainless steel floor covered with glycerol solution. Gait trials were conducted with 14 participants who wore the footwear on the wet stainless steel floor. The drag test results indicated that the hybrid rubber surface pattern sole exhibited higher SCOF (≥0.44) and DCOF (≥0.39) values than the soles of the comparative footwear (p<0.001). Because of such high SCOF and DCOF values, the slip frequency (p<0.01), slip distance (p<0.001), and slip velocity (p<0.001) for the footwear with the hybrid rubber surface pattern outsole were significantly lower than those for the comparative footwear, which resulted in no falls during trials.
The present study examined whether a new footwear outsole with tread blocks and a hybrid rubber surface pattern, composed of rough and smooth surfaces, could increase slip resistance and reduce the risk of fall while walking on a wet floor surface. A drag test was performed to measure static and dynamic coefficient of friction (SCOF and DCOF, respectively) values for the footwear with the hybrid rubber surface pattern outsole and two types of commercially available boots that are conventionally used in food factories and restaurant kitchens with respect to a stainless steel floor covered with glycerol solution. Gait trials were conducted with 14 participants who wore the footwear on the wet stainless steel floor. The drag test results indicated that the hybrid rubber surface pattern sole exhibited higher SCOF (≥0.44) and DCOF (≥0.39) values than the soles of the comparative footwear (p<0.001). Because of such high SCOF and DCOF values, the slip frequency (p<0.01), slip distance (p<0.001), and slip velocity (p<0.001) for the footwear with the hybrid rubber surface pattern outsole were significantly lower than those for the comparative footwear, which resulted in no falls during trials.
Falls are the leading cause of occupational accidents in Japan1). Slip is one of the frequent events leading to falling
accidents2,3,4,5). Most slip and fall accidents in the workplace occur on wet
(liquid-contaminated) floor surfaces6,7,8).
Floor surfaces in food factories and restaurant kitchens are often wet because of spilling
water or oil, causing slips because of low friction due to the formation of a fluid film at
the contact interface between the shoe sole and the floor surface. Therefore, a footwear
pattern with high slip resistance on wet floor surfaces is required.The coefficient of friction (COF) between the footwear and the underfoot surface is widely
used as a measure of slip resistance. High static and dynamic coefficeint of friction (SCOF
and DCOF, respectively) values are needed at the shoe-floor interface while walking to
prevent slip initiation and to stop a slip if it occurs. Biomechanical studies on the safety
limits of SCOF and DCOF9,10,11,12,13,14) indicate that SCOF and DCOF values of >0.4 are required
at the shoe-floor interface to continue level walking without a slip and fall.Surface pattern designs of footwear soles, including the tread pattern (macroscopic
pattern) and surface roughness (microscopic pattern), are helpful to drain liquid from the
shoe-floor interface to increase slip resistance, i.e., COF6, 15,16,17,18,19). However, design criteria
for a shoe sole pattern with a sufficiently high SCOF and DCOF on wet surfaces are
unclear.Yamaguchi et al.20)
found that a rectangular rubber block with a rough surface has high SCOF and low DCOF
values, whereas a rubber block with a smooth surface has low SCOF and high DCOF values on a
smooth stainless steel surface wet with glycerol solution. Based on this finding, they
developed a rubber block with a surface pattern of rough and smooth surfaces (hybrid rubber
surface pattern), as shown in Fig. 1. They demonstrated that the hybrid rubber block with a rough surface area ratio (a
ratio of the surface area of the rough surface component to that of a single tread block) of
50% had SCOF and DCOF values of >0.4 on a wet surface. Superior slip resistance of the
hybrid rubber surface pattern was achieved by dissipating the liquid film from the contact
interface, resulting in a sufficient contact area between the rubber block and the mating
surfaces at slip initiation (corresponding to SCOF) and while sliding (corresponding to
DCOF)20). These results indicate that
the hybrid rubber surface pattern would be applicable to the surface pattern of a footwear
outsole to prevent slips and falls on wet surfaces.
Fig. 1.
Rubber block with a hybrid rubber surface pattern.
Rubber block with a hybrid rubber surface pattern.A new footwear outsole with a hybrid rubber surface pattern was prepared and tested in the
present study to determine its efficacy for increasing slip resistance and reducing the risk
of fall due to a slip while walking on a wet floor surface. We hypothesized that the
footwear outsole with the hybrid rubber surface pattern would demonstrate higher SCOF and
DCOF values on a wet floor than the outsoles of the conventional footwear used in food
factories and restaurant kitchens. We also hypothesized that the footwear outsole would
reduce slip occurence and prevent falling.
Methods
Test footwear
Figure 2 shows the test footwear. Footwear A (Fig.
2a) and B (Fig. 2b) were commercially
available and are conventionally used in food factories and restaurant kitchens. Footwear
C had an outsole with tread blocks (height: 3.5 mm, width: 9 mm) and a hybrid rubber
surface pattern (Fig. 2c) and was manufactured
for this study. The rough surface area ratio was 50% for the outsole with the hybrid
rubber surface pattern. Comparative footwear A (Fig.
2a) had tread blocks (height: 4–7 mm) with a pearskin finish surface and a round
chamfered edge, while footwear B (Fig. 2b) had
tread blocks (height: 7 mm, width: 5 mm) with a smooth surface and a right edge. The
outsole of all types of footwear was made from nitrile butadiene rubber [shore hardness:
53 (A/15) for footwear A; 55 (A/15) for footwear B; and 41 (A/15) for footwear C].
Fig. 2.
Test footwear. (a) footwear A; (b) footwear B; (c) footwear C (with an outsole
containing tread blocks with a hybrid rubber surface pattern).
Test footwear. (a) footwear A; (b) footwear B; (c) footwear C (with an outsole
containing tread blocks with a hybrid rubber surface pattern).
Drag test
A drag test was used to measure the relative slipperiness of each footwear type with
respect to a wet stainless steel floor surface for testing our first hypothesis.1. Experimental apparatus: A cart-type friction testing system for measuring SCOF and
DCOF values for the shoe-floor interface (Fig.
3: µ-CART; Trinity-Lab Inc., Tokyo, Japan)21) was used for the drag test. The cart-type friction
tester was pushed by the experimenter on the floor surface. The tested footwear was
attached with a mechanical foot, and a normal load was applied to the footwear-floor
interface with weights. The footwear was connected to a load cell, which measured the drag
force, through the shaft and chassis. An accelerometer attached on the horizontal chassis
or mechanical foot measured acceleration acting on the footwear. The force and
acceleration data collected from the load cell and accelerometer (through an amplifier),
respectively, were stored on a logger in the control box. If the sliding velocity of the
footwear was constant during dragging, COF between the footwear and the floor surface was
equivalent to the drag force, measured using the load cell, divided by the normal load.
However, as the experimenter pushed the cart and the footwear was dragged on the floor
surface, a variation in the sliding velocity of the footwear was unavoidable. Horizontal
acceleration acting on the footwear during dragging was measured using the accelerometer
mounted on the mechanical foot or chassis so that the inertia acting on the footwear could
be compensated with respect to the drag force measured using the load cell. Based on the
mechanical model presented in Fig. 4, COF between the shoe and the floor surface was calculated using the following
formula:
Fig. 3.
(a) A cart-type friction testing system for measuring static and dynamic
coefficient of friction (SCOF and DCOF, respectively) values for the shoe–floor
interface and (b) schematic diagram of the configuration of the mechanical system
(cross-sectional view).
Fig. 4.
Mechanical model for calculating the coefficient of friction (COF).
(a) A cart-type friction testing system for measuring static and dynamic
coefficient of friction (SCOF and DCOF, respectively) values for the shoe–floor
interface and (b) schematic diagram of the configuration of the mechanical system
(cross-sectional view).Mechanical model for calculating the coefficient of friction (COF).(1)where fh and fn are friction
force and normal load applied at the interface, respectively, F is the
drag force measured using a load cell, m is the mass of the mechanical
foot, footwear, and weights, ah is the horizontal acceleration of the footwear measured
using an accelerometer, and g is the gravitational force. The capacity of the load cell
was 490 N, and the range of acceleration and the frequency response of the accelerometer
were −6 to 6 G and DC–1,500 Hz, respectively.2. Experimental condition: Fig. 5 shows the experimental set-up for the drag test. Three types of size 8 (26 cm)
footwear were dragged using the cart-type friction tester on a stainless steel floor (2 m
× 1 m × 2 mm), polished with a #400 abrasive paper. The floor was covered with glycerol
solution (glycerin concentration: 70 wt%; viscosity: 19.7 mPa·s; Wako Pure Chemical
Industries, Ltd., Osaka, Japan) using a spatula to ensure an even distribution of the
solution before every test. The normal load was 514.5 N, which included the load of the
weights (500 N), shaft, mechanical foot, and footwear. The cart was pushed, and the test
footwear was dragged 1.0 m in approximately 2 s. The experimenter was asked to start
dragging the footwear within 5 s after the weights were placed. The test was performed
five times under identical conditions. The sampling frequency of the drag force and
acceleration of the footwear was 1 kHz.
Fig. 5.
Experimental set-up for the drag test. (a) overview, (b) attaching part of the
footwear.
Experimental set-up for the drag test. (a) overview, (b) attaching part of the
footwear.3. Data analysis: The drag force and acceleration data were low pass filtered (10 Hz).
Then, COF was calculated using the above formula, and the sliding velocity of the test
footwear v at the kth frame was calculated by numerical
integration using the following formula:(2)where i is the frame number and Δt is the sampling
rate.A representative time variation of COF and sliding velocity during the drag test is shown
in Fig 6. SCOF was determined as the first peak of COF just before sliding onset. Mean SCOF
and DCOF values at sliding velocities of 0.1, 0.2, 0.3, 0.4, and 0.5 m/s for five drag
tests under identical condition were used for analysis.
Fig. 6.
Representative time variation in the coefficient of friction (COF) and sliding
velocity; test footwear: footwear A, sliding velocity was calculated by numerically
integrating the horizontal acceleration of the footwear.
Representative time variation in the coefficient of friction (COF) and sliding
velocity; test footwear: footwear A, sliding velocity was calculated by numerically
integrating the horizontal acceleration of the footwear.Statistical analysis was performed using SPSS ver. 19.0 (SPSS, Inc., Chicago, IL, USA).
One-way analysis of variance (ANOVA) was used to test if the SCOF values were affected by
the footwear type. Post-hoc paired t-test with a Bonferroni correction
were used to determine specific significant differences between footwear conditions.
Two-way ANOVA was used to test if the DCOF values were affected by the footwear type and
sliding velocity conditions. Post-hoc paired t-tests with a Bonferroni
correction was used to determine specific significant differences between footwear or
sliding velocity conditions. The significance level was set at
p=0.05.
Gait trial
A repeated measures study was conducted with participants walking on the wet stainless
steel floor surface while wearing the three types of footwear to test our second
hypothesis.1. Subjects: The study included 14 healthy adult males with an average age of 23.0 yr
(range: 21–25 yr). Mean ± SD height and weight values of the subjects were 1.74 ± 0.03 m and
61.4 ± 4.7 kg, respectively. This study was approved by the Institutional Review Board of
National Nishitaga Hospital, Japan, and informed consent was obtained from all subjects.2. Experimental procedure: Fig. 7 is a schematic representation of the experimental set-up. The stainless steel floor
used in the drag test was mounted on a walkway and was covered with glycerol solution
(glycerol concentration: 70 wt%) using a spatula to ensure an even distribution of the
solution between trial blocks. A six-camera motion measurement system (Vicon 370; Oxford
Metrics Ltd., Oxford, UK) recorded three-dimensional motion data at a sampling rate of 60 Hz
from four infrared reflective markers attached bilaterally to the toe and heel of the
footwear.
Fig. 7.
Schematic of the experimental set-up for the gait trial.
Schematic of the experimental set-up for the gait trial.Subjects were asked to walk straight, turn 180° at the end of the stainless steel floor,
and return to the starting position, as shown in Fig.
8. They were instructed to walk at a self-selected pace and to do whatever came
naturally to prevent a fall. The subjects wore a safety harness to help their balance, which
was designed to prevent impact with the floor without otherwise restricting movement. The
subjects were tested with the three types of footwear during separate sessions. The order of
testing footwear conditions was randomized to eliminate the effect of testing order on the
results. Each trial was replicated three times under the same conditions (i.e., nine trials
per subject), and all trials were videotaped.
Fig. 8.
Schematic of the 180° turn after walking straight on the stainless steel floor.
Schematic of the 180° turn after walking straight on the stainless steel floor.3. Data analysis: We defined a fall when the subject’s feet were off the floor and when
they were completely suspended by the harness after losing balance because of a slip.
Whether the subjects fell was determined by video data. Vertical coordinates of the heel and
toe reflective markers were used to determine whether both of the subject’s feet were off
the floor for trials in which it was difficult to identify a fall from the video data.The heel horizontal velocity was calculated using the following formula:(3)where, i is the frame number. The heel horizontal displacement from foot
strike was calculated using the following formula:(4)where, xheel (m) and
yheel (m) are the coordinates of the heel
markers in the x and y directions at foot strike, and
xheel (n) and
yheel (n) are the coordinates of the heel
markers in the x and y directions when the heel horizontal
velocity becomes 0 after foot strike. The coordinate data for the reflective markers were
digitally smoothed using a twoorder low-pass Butterworth filter with a cut-off frequency of
10 Hz. A macro-slip was considered to have occurred if the heel horizontal velocity failed
to reach 0 within a 3.0-cm heel horizontal displacement after foot strike13, 22); a slip of 0–3.0 cm was defined as a micro-slip, which is generally
undetected22). The foot strike was
determined on the basis of the vertical heel marker position. The slip trial associated with
a macro-slip was identified if the maximum slip distance, Dmax, which is the highest value
of the heel horizontal displacement among all steps in each trial, was >3.0 cm. The
frequency of trial with macro-slips/ fall for each subject–footwear condition was calculated
as the ratio of the number of trials with macro-slips/fall to the number of trials for each
condition (three times). Therefore, the frequency of trials with macro-slips/fall was 0%
(0/3), 33% (1/3), 67% (2/3), or 100% (3/3) for each subject-footwear condition.
Dmax and the maximum slip velocity,
vmax, which is the maximum horizontal velocity of the heel
marker among all steps in each trial, were used to examine slip severity.4. Statistical analysis: Statistical analysis was performed using SPSS ver. 19.0. One-way
repeated measures ANOVA was performed using the frequency of trial with macro-slips,
frequency of trial with a fall, Dmax, and
vmax as dependent variables, and the footwear type as
independent variables. Post-hoc paired t-tests with a Bonferroni correction
were used to determine the specific significant difference. A significance level of 0.05 was
used for these analyses. When appropriate, the frequency data were rank-transformed to
ensure that the assumptions associated with ANOVA were adhered.
Results
SCOF and DCOF values during the drag test
Figure 9 shows mean SCOF values (Fig. 9a) and mean
DCOF values as a function of sliding velocity (Fig.
9b) for the three types of footwear. Error bars indicate SD.
Fig. 9.
Mean (a) static and (b) dynamic coefficient of friction (SCOF and DCOF,
respectively) value as a function of the sliding velocity for each footwear
type.
Mean (a) static and (b) dynamic coefficient of friction (SCOF and DCOF,
respectively) value as a function of the sliding velocity for each footwear
type.One-way ANOVA indicated that the mean SCOF values were significantly affected by the
footwear type (p<0.001); post-hoc analysis demonstrated that footwear
C showed higher SCOF values than footwear A and B (p<0.001), but no
significant differences were observed in the SCOF values for footwear A or B
(p>0.05).Two-way ANOVA indicated that the mean DCOF values were significantly affected by the
footwear type (p<0.001), sliding velocity condition
(p<0.001), and footwear-sliding velocity interaction
(p<0.001). Post-hoc analysis revealed that footwear C showed higher
DCOF values at all sliding velocity conditions (0.1–0.5 m/s) than footwear A and B
(p<0.001). In addition, DCOF values for footwear A and C did not
depend on the sliding velocity (p>0.05), whereas the mean DCOF value
at 0.1 m/s was lower than that at other sliding velocity conditions for footwear B
(p<0.001). Footwear B also showed higher mean DCOF values than
footwear A at sliding velocities of >0.2 m/s (p<0.01). As shown in
Fig. 9a and 9b, footwear C showed the mean
SCOF values of ≥0.44 and the mean DCOF value of ≥0.39, which would be sufficient to
continue level walking without slipping and falling based on the safety limits of SCOF and
DCOF values9,10,11,12,13,14).
Slip and fall frequency during the gait trial
Table 1 presents the mean frequency of trial with macro-slips and fall for each
footwear type. The mean values of the frequency of trial with macro-slips for footwear A,
B, and C were 95.2% (40/42), 26.2% (11/42), and 2.4% (1/42), respectively. One-way
repeated measures ANOVA indicated that the footwear type significantly affected the
frequency of trial with macro-slips (p<0.001); post-hoc analysis
revealed that wearing footwear C (hybrid rubber surface pattern) significantly reduced the
frequency of trial with macro-slips by 92.8 points and 23.8 points compared with wearing
footwear A and B, respectively. The frequency of trial with fall while wearing footwear A
was 54.0% (23/42), whereas no subjects fell while wearing footwear B and C.
Table 1.
Frequency of trial with macro-slips and fall
Footwear A(conventional)
Footwear B(conventional)
Footwear C(hybrid pattern)
Frequency of trial with macro-slips, %(number of trials with
macro-slips)
95.2 ± 12.1(40/42)
26.2 ± 19.3*(11/42)
2.4 ± 8.9*,**(1/42)
Frequency of trial with a fall, %(number of trials with a
fall)
54.0 ± 36.1(23/42)
0(0/42)
0(0/42)
* Significant difference to footwear A (p<0.01),
** Significant difference to footwear B
(p<0.01)
* Significant difference to footwear A (p<0.01),
** Significant difference to footwear B
(p<0.01)Figure 10a and 10b shows the mean maximum slip distance (Dmax) and slip
velocity (vmax) for all types of footwear. Error bars indicate
SDs. One-way repeated measures ANOVA indicated that the slip distance was significantly
affected by the footwear type (p<0.001). Post-hoc analysis suggested
that the mean Dmax value for footwear C (0.01 ± 0.009 m) was
significantly shorter than that for footwear A (0.32 ± 0.16 m,
p<0.001) and footwear B (0.02 ± 0.015 m, p<0.005),
as shown in Fig. 10a. One-way repeated measures
ANOVA indicated that the slip velocity was significantly affected by the footwear type
(p<0.001). Post-hoc analysis indicated that the mean
vmax value for footwear C (0.18 ± 0.17 m/s) was the lowest
among the three types of footwear (1.9 ± 0.9 m/s for footwear A; 0.43 ± 0.3 m/s for
footwear B). In particular, the mean slip distance for footwear C was 9.6 mm, which was
negligibly small. Slip distance and velocity are indicators of the risk of fall caused by
an induced slip while walking, and greater slip distance and velocity are associated with
a greater fall frequency22,23,24,25). Strandberg and Lanshammar23) reported that the slip distance of >0.1 m and the
slip velocity of >0.5 m/s result in a fall, and Brady et al.24) suggested that the critical slip
distance and velocity were 0.2 m and 1.1 m/s, respectively. The slip distance and velocity
for footwear A (0.32 ± 0.16 m, 1.9 ± 0.9 m/s) were greater than those critical values of
slip distance and velocity, thereby causing falls after slipping.
Fig. 10.
Mean (a) slip distance and (b) slip velocity values for each footwear type.
Mean (a) slip distance and (b) slip velocity values for each footwear type.
Discussion
The drag test findings indicate that footwear C with tread blocks and the hybrid rubber
surface pattern showed higher SCOF (≥0.44) and DCOF (≥0.39) values than footwear A and B on
a stainless steel surface wet with glycerol solution. These results support our first
hypothesis. In addition, the hybrid rubber surface pattern outsole showed superior slip
resistance and efficacy in reducing the risk of fall during walking on a wet surface than
the soles of the other footwear, which supports our second hypothesis.As shown in Fig. 11a, when the tread block with the hybrid rubber surface pattern contacted the floor
covered with glycerol solution, the glycerol film was removed from the contact interface
because of the high contact pressure by the rough surface asperities, resulting in a direct
contact between the asperities of the rough surface component and the stainless steel floor
surface. Thus, SCOF reached a high value, resulting in a low frequency of slip onset.
Fig. 11.
Possible mechanisms for the low frequency of slips and falls using the footwear
outsole with a hybrid rubber surface pattern.
Possible mechanisms for the low frequency of slips and falls using the footwear
outsole with a hybrid rubber surface pattern.Even when a slip occurs because of a large traction caused by gait characteristics such as
large step length26, 27), the anterior right edge of the smooth surface component prevents
infiltration of glycerol solution into the contact interface and deformation of the tread
block increases the contact pressure at the anterior part of the block28), which allows the smooth surface part to contact directly
with the stainless steel surface (Fig. 11b).
Therefore, DCOF reached a high value, resulting in a shorter slip distance (<3.0 cm) and
low slip velocity.In contrast, footwear A had tread blocks with a pearskin finish surface and rounded surface
asperities. Therefore, the contact pressure between the asperities and the mating stainless
steel floor surface was not high enough to remove the glycerol film from the contact
interface when the tread block contacted the floor surface and during sliding, which
resulted in a low SCOF value at slip initiation and a low DCOF value during sliding. Thus,
slip and fall were more likely to occur in those wearing footwear A than those wearing
footwear C. A liquid film remained at the contact interface when the footwear B outsole,
which had tread blocks with a smooth surface and a right edge, contacted the floor surface
because of a low contact pressure, resulting in a lower SCOF value and higher slip frequency
than the footwear C outsole. However, after slipping, the contact area between the anterior
part of the tread block and the floor surface increased while wearing footwear B, which
resulted in a higher DCOF value than that while wearing footwear A. This high DCOF value
resulted in a short slip distance and a low slip velocity, thereby resulting in no fall
while wearing footwear B.The difference in the slip distance and velocity between footwear B and C was because of
the difference in the hardness of the rubber and the number of tread blocks. The hardness of
the rubber sole of footwear C was lower than that of footwear B. Therefore, the deformation
of tread blocks on footwear C would be higher than that on footwear B, which resulted in a
higher contact pressure at the anterior part of each tread block28). Thus, the effect of the infiltration and removal of the
solution film into and from the contact interface between the tread blocks and mating
surfaces was more significant with footwear C than with footwear B. Footwear C had more
tread blocks than footwear B; footwear B had no tread blocks at the planter arch part.
Therefore, the resulting contact area between the tread blocks and the mating steel surface
was larger while wearing footwear C, which would increase slip resistance.A limitation of this study was that the experimental design of the gait trials did not
eliminate the possibility of anticipating and adapting for a slip. The participants knew
prior to the trial that they had to land and walk on a wet surface, and this may have led to
a change in their gait to decrease slip potential, as reported in the literature29). Further investigations including a
comparison of the hybrid rubber surface pattern outsole with more types of footwear outsoles
are needed to clarify the efficacy of the outsole for preventing slips and falls on wet
surfaces.
Conclusions
Our drag test and gait trial results obtained on a stainless steel floor surface wet with
glycerol solution indicated that the newly developed hybrid rubber surface pattern outsole
showed higher slip resistance than the soles of two types of commercially available footwear
conventionally used in food factories and restaurant kitchens. The hybrid rubber surface
pattern outsole exhibited higher SCOF (≥0.44) and DCOF (≥0.39) values on the drag test than
the soles of the comparative footwear. Because of such high SCOF and DCOF values, slip
frequency, distance, and velocity for the footwear with the hybrid rubber surface pattern
outsole were significantly lower than those for the soles of the comparative footwear, which
resulted in no falls during trials. This study provides new information about footwear
outsole pattern design and indicates that the newly developed footwear outsole will
contribute to prevent slip and fall accidents in the workplace.