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Published in final edited form as:
Ergonomics. 2001 October 20; 44(13): 1167–1199.
Human-centred approaches in slipperiness measurement
Raoul Grönqvist†,*, John Abeysekera‡, Gunvor Gard§, Simon M. Hsiang¶, Tom B.
Leamon¶¶, Dava J. Newman††, Krystyna Gielo-Perczak¶¶, Thurmon E. Lockhart‡‡, and Clive
Y.-C. Pai§§
†Finnish
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Institute of Occupational Health, Department of Physics, Topeliuksenkatu 41 FIN-00250,
Helsinki, Finland ‡Division of Industrial Ergonomics, Luleå University of Technology, S-971 87 Luleå,
Sweden §Department of Physical Therapy, Lund University, S-220 05 Lund, Sweden ¶Department
of Industrial Engineering, Texas Tech University, Lubbock, TX 79409-3061, USA ¶¶Liberty Mutual
Research Center for Safety and Health, 71 Frankland Road, Hopkinton, MA 01748, USA ††MIT
Department of Aeronautics and Astronautics, Cambridge, MA 02142, USA ‡‡Grado Department of
Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg,
VA 24061, USA §§Department of Physical Therapy, University of Illinois at Chicago, Chicago, IL
60612-7251, USA
Abstract
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A number of human-centred methodologies—subjective, objective, and combined—are used for
slipperiness measurement. They comprise a variety of approaches from biomechanically-oriented
experiments to psychophysical tests and subjective evaluations. The objective of this paper is to
review some of the research done in the field, including such topics as awareness and perception of
slipperiness, postural and balance control, rating scales for balance, adaptation to slippery conditions,
measurement of unexpected movements, kinematics of slipping, and protective movements during
falling. The role of human factors in slips and falls will be discussed. Strengths and weaknesses of
human-centred approaches in relation to mechanical slip test methodologies are considered. Current
friction-based criteria and thresholds for walking without slipping are reviewed for a number of work
tasks. These include activities such as walking on a level or an inclined surface, running, stopping
and jumping, as well as stair ascent and descent, manual exertion (pushing and pulling, load carrying,
lifting) and particular concerns of the elderly and mobility disabled persons. Some future directions
for slipperiness measurement and research in the field of slips and falls are outlined. Human-centred
approaches for slipperiness measurement do have many applications. First, they are utilized to
develop research hypotheses and models to predict workplace risks caused by slipping. Second, they
are important alternatives to apparatus-based friction measurements and are used to validate such
methodologies. Third, they are used as practical tools for evaluating and monitoring slip resistance
properties of foot wear, anti-skid devices and floor surfaces.
Keywords
Slipperiness measurement; Human factors; Postural and balance control; Slip recovery; Fall
avoidance; Safety criteria; Friction thresholds
© 2001 Taylor & Francis Ltd
*
Author for correspondence. raoul.gronqvist@occuphealth.fi.
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1. Introduction
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Data on how to accurately measure risk exposures to slipping and falling hazards seem to be
sparse. One of the underlying reasons is the complex nature of slip and fall avoidance strategies
such as their dependence upon anticipation of hazards and adaptations of gait to slippery
environments (Strandberg 1985, Llewellyn and Nevola 1992, Cham et al. 2000, Redfern et
al. 2001). A number of human-centred approaches for the measurement of slipperiness have
been utilized to estimate slipping and falling hazards and risks. These approaches have explored
initial events from slip onset to foot slide, as well as subsequent events from loss of balance
until falling. The output estimates have comprised, among others, perceived sense of slip and
slip distance evaluations, slipperiness ratings, heel velocity measurements, heel and trunk
acceleration and postural instability measurements, and falling frequency estimations
(Strandberg et al. 1985, Leamon and Son 1989, Grönqvist et al. 1993, Myung et al. 1993,
Cohen and Cohen 1994a, b, Hirvonen et al. 1994, Chiou et al. 2000). Other approaches have
focused on kinematics (spatial movement of the body) and kinetics (ground reaction forces,
utilized and required friction) of slipping and falling (Strandberg and Lanshammar 1981,
Morach 1993, Redfern and Rhoades 1996, Hanson et al. 1999, Brady et al. 2000, You et al.
2001) or electromyographic (EMG) activity of compensatory muscle responses during
simulated slipping (Tang et al. 1998).
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Human-centred measurement methodologies form an important complementary to mechanical
friction-based test methods which are discussed elsewhere (Chang et al. 2001a,b). The former
add a further dimension—the human factor—to the measurement of slipperiness process, and
have been widely used to validate mechanical test methods as well (Strandberg 1985, Jung and
Fischer 1993, Grönqvist 1999, Leclercq 1999).
The following human-centred approaches to slipperiness measurement will be addressed
(figure 1):
1.
‘subjective’ approaches such as rating scales, rankings and paired comparisons of
floors and footwear, as well as direct observation of protective responses to slipping;
2.
‘objective’ biomechanically-oriented approaches such as measuring ground reaction
forces, friction usage, body segment movements, joint angles and moments, slip
distances and velocities, centre of mass and centre of pressure trajectories, or
electromyography; and
3.
‘combined’ approaches that comprise subjective evaluations in combination with
objective measurements.
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The main objective of the present paper is to review the relevant literature on human-centred
approaches for the measurement of slipperiness. The role of human factors in slips and falls is
discussed, including topics such as awareness and perception of slipperiness, postural and
balance control, and adaptation to slippery environments. An overview of friction-based
criteria and thresholds for safe walking without slipping is presented, including criteria for
some specific work tasks (pushing and pulling, lifting, load carrying) and some special risk
groups (the elderly and mobility disabled).
2. The role of human factors in slipping
2.1. Primary and secondary risk factors
Injuries due to slips and falls are not purely random events, but rather predictable entities with
known risk factors that may be extrinsic (environmental factors), intrinsic (human factors) or
mixed (system factors). The primary risk factor for slipping is, by definition (cf. Grönqvist et
al. 2001), poor grip or low friction between the footwear (foot) and the underfoot surface (floor,
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pavement, etc.). Static friction is assumed to be important for preventing the initiation of
slipping, while dynamic friction would determine whether a foot slide might be recoverable
and an injury avoidable, or whether the slip might lead to an injurious fall or any other type of
injury, for instance, due to strenuous body movements for regaining balance.
Secondary risk factors (‘predisposing factors’) for slipping accidents are related to a variety of
environmental and human factors, for instance, inadequate lighting, uneven surfaces,
incomplete stairway design, non-use of handrails and vehicle exit aids, poor postural control,
ageing, dizziness, vestibular disease, diabetes, alcohol intake, and the use of anti-anxiety drugs
(Waller 1978, Honkanen 1983, Templer et al. 1985, Pyykkö et al. 1988, 1990, Sorock 1988,
Alexander et al. 1992, Malmivaara et al. 1993, Nagata 1993, Fothergill et al. 1995, Fathallah
et al. 2000). Merely the slipperiness of the shoe/floor interface may not be a sufficient
explanation for falls and other slip-related injuries. The secondary risk factors tend to
predispose persons to accidental injuries in slippery conditions and during sudden unexpected
changes in slipperiness. The multitude of risk factors and their possible cumulative effects
seem to further complicate both slipperiness measurements and the prevention of accidents
and injuries due to slipping.
2.2. Postural and balance control
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Maintaining postural balance and stability during locomotion is a complex process of position
adjustments by muscles and bones acting over joints and controlled by several sensory systems,
including vision, vestibular organ, proprioceptive receptors in joints and muscles (e.g. stretch
reflexes), and cutaneous receptors with elements such as the pressor receptors of the feet and
the velocity- and position-sensitive muscle spindles (Nashner 1983, Johansson and Magnusson
1991). These sensory systems are further controlled by the central nervous systems located in
the spinal cord, the brainstem, basal ganglia, cerebellum and cerebral cortex (Horak 1997).
Vestibular input governs typically 65% of the body sway during sudden perturbation in
standing, while 35% is accounted for by visual, proprioceptive and other input (Pyykkö et al.
1990).
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A balance perturbation due to a foot slide constitutes a risk situation, especially if a person’s
primary task is not maintaining balance. Some common dual-task situations in which
locomotion is a secondary task, include walking while reading or talking (on a cellular phone),
searching through aisles for a particular object (e.g. grocery shopping), or lifting, lowering and
carrying loads while walking. The perseverance of performance in these dual-task situations
is critically dependent upon control of the rhythm of locomotion (Danion et al. 1997) and the
rhythm of the primary task being attended to (Jones 1976). An accident may occur as a result
of a person not being focused on the locomotion, but on perceptual and cognitive processes
related to primary task performance. It may also result from a breakdown in rhythm control.
High accelerations or decelerations are frequently associated with balance loss, and may cause
high inertial forces that have to be supported by the musculoskeletal system.
The way balance is maintained and which balance strategies are sought in a particular situation
is dependent on the ability to anticipate postural demands in response to external perturbations,
and to move and control the body’s centre of mass (COM) back to a position over the base of
support (BOS) and the centre of foot support/pressure (COP). A region of stability can be
predicted based on the physical constraints of muscle strength, size of BOS, and floor surface
contact forces within an environment (Pai and Patton 1997). The alignment of body segments
over the BOS must be kept such that the projection of the body COM falls within the boundaries
of stability. However, movement termination during a foot slide also depends on the presence
of an external braking force that allows the stability region to extend beyond the anterior limit
of the BOS in the direction of slipping (Pai and Iqbal 1999). It appears that an increasing friction
force might provide such an external braking force, eventually enabling a recovery of stability.
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Three strategies for co-ordinating legs and trunk to maintain the body in equilibrium with
respect to gravity during standing have been presented (Nashner 1985, Winter 1995): the ankle
and hip strategies, and the combined strategy (figure 2). For compensation of antero-posterior
sway displacements, the head and the body COM moves in the same direction backwards or
forwards during the ankle strategy. This strategy helps to correct small perturbations by using
the ankle plantar- and dorsiflexors. During the hip strategy in more perturbed situations or
when the ankle muscles cannot act, the body COM moves backwards or forwards opposite to
the head movement by means of muscle responses that either flex or extend the hip (Winter
1995). Allum et al. (1998) questioned the major role of lower-leg proprioceptive control of
posture, especially the dominant ankle strategy, and concluded that postural and gait
movements are centrally organized at two levels. The first level involves the generation of a
directionally-specific response pattern based primarily on hip or trunk proprioceptive input
and secondarily on vestibular input. The second level is involved in the shaping of centrally
set multi-sensorial activation patterns, so that movements can adapt to different task conditions.
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A sufficient muscle tonus—high enough to maintain postural stability but low enough to
facilitate movement—is another prerequisite for the co-ordination of posture and gait. The
potential advantage of the stiffness control was recently discussed by Winter et al. (1998)
during perturbed standing. Their inverted pendulum model assumed that muscles act as springs
to cause the COP to move in phase with the COM as the body sways. The COM-COP
difference, on the contrary, has been reported to be proportional to the horizontal component
of the ground reaction force captured by plantar cutaneous receptors located in the foot sole
(Morasso et al. 1999). Following latencies in muscle activation after tripping and slipping
perturbations have been reported: 120 – 200 ms for visual control and 60 –140 ms for
proprioceptive control (Pyykkö et al. 1990, Eng et al. 1994, Tang et al. 1998). However, other
studies have claimed that a stiffness control may act almost immediately as the ankle joint
angle is changed, causing the COP to move in the same direction as the COM (Winter et al.
1998, cf. Redfern et al. 2001).
2.3. Unexpected changes in slipperiness
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The question of whether the risk of slipping injuries is more related to a constantly poor shoe/
floor traction or an unexpected, sudden loss of grip due to frictional variation still remains
unsolved. The latter case might be the more likely possibility. Precipitation, temperature and
snowfall, and the presence of contaminants or lubricants on the contact surface are important
risk factors for occupational and non-occupational slips and falls according to several studies
(Honkanen 1982, Merrild and Bak 1983, Lund 1984, Strandberg 1985, Manning et al. 1988,
Grönqvist and Roine 1993, Leclercq 1999). Slip-related injuries often seem to occur on wet,
dirty, oily, greasy, snowy, icy, or other contaminated walking surfaces. Nevertheless, weak
inverse relationships between, for example, seasonal effects (precipitation and cold
temperatures) and occupational slips and falls injuries have been reported (Leamon and
Murphy 1995).
The role of human factors in the measurement of slipperiness is significant. Strandberg
(1985) presented some interesting results from psychophysical walking experiments performed
on a continuously slippery triangular path (circumference 12 m). Twelve equally trained
healthy male and female subjects were advised to walk as fast as possible over a smooth vinyl
(PVC) floor wearing four different shoe types. Other shoe/floor conditions were assessed also,
but will not be discussed here. Each test comprised five laps to be walked as fast as possible
without slipping and falling. Since cornering was involved in these tests, a higher walking
speed required greater friction utilization. The vinyl floor surface was contaminated and the
viscosity of the lubricants was adjusted to either 0.001 N s m−2 (water and detergent), 0.01 N
s m−2 (diluted glycerol) or 0.2 N s m−2 (concentrated glycerol). The falling frequencies during
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five laps were counted and compared to an average time-based friction utilization (TFU) value
during the complete trial and an average force plate-based friction utilization (FFU) value over
one step in the 90° corner of the triangular path ( Lanshammar and Strandberg 1985, Strandberg
et al. 1985). The results were surprising especially with two of the tested shoe types, Bovinide
and Studded (table 1): the test condition with medium TFU (and FFU) caused the highest
number of falls (20) while the high and the low TFU (and FFU) conditions caused less falls (6
falls each). The average friction utilization values showed, as expected, that slipperiness
increased as the viscosity of the lubricant increased. However, the medium friction utilization
values in the range 0.20 to 0.25, obtained with the lubricant of medium viscosity (0.01 N s
m−2), were surprisingly linked to the highest number of falls during these experiments. (Note:
The ‘Bovinide’ sole was linked to a higher falling risk over the ‘Studded’ sole, which was
associated with a greater variation in friction utilization within steps and over consecutive steps.
Thus, the smooth, non-patterned and stiff surface of the ‘Bovinide’ sole may have reduced the
effective contact area in comparison with the flexible and patterned ‘Studded’ sole.)
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One possible explanation for this apparent discrepancy between friction utilization and
frequency of falls might be that the subjects were not able to walk as fast during the slippery,
low friction condition (TFU about 0.1) as during the medium friction condition (TFU about
0.2). By adopting a slower ‘protective’ gait strategy in the low friction condition (i.e. less risktaking) the subjects were thus able to reduce the number of falls. Then the next question is
‘why were the subjects not able to adapt their gait safely during the medium friction condition’?
Perhaps because it was a borderline safe/unsafe and deceptive condition, and was hence more
di cult to anticipate, which resulted in a greater number of falls. Then why did the high friction
condition (TFU about 0.3) cause just as many falls as the low friction condition? This apparent
contradiction might be explained by the fact that the subjects were able to walk more quickly
over the high friction floor condition, thus challenging their balance more (i.e. taking a higher
risk) than during the low friction condition.
2.4. Postural adjustments and adaptation to slipping risks
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Under constant low-friction conditions, humans typically adopt a protective gait strategy,
which involves the combined effect of force and postural changes of the early stance. The
subjects take shorter steps and increase their knee flexion, which reduces the vertical
acceleration and the forward velocity of the body (Llewellyn and Nevola 1992). As a
consequence, the foot impact against the ground should reduce during early stance.
Theoretically this strategy should, in the presence of lubricants, minimize the hydrodynamic
pressure generation in the lubricant film and the load support between the interacting surfaces
(Moore 1972). Hence, a better true contact between the shoe and the underfoot surface should
be achieved, which can result in an increased grip and traction (a higher friction coefficient)
and a lesser risk for slipping and falling.
A stepping response to a foot slide may have a unique importance in balance recovery and fall
prevention (Maki and McIlroy 1997, McIlroy and Maki 1999, Pai and Iqbal 1999). However,
it is still unclear what factors might determine the success rate of recovery during a stepping
response after the onset of a slip perturbation. These responses can be volitional, involving
conscious efforts and/or they can be automatic reflexive reactions. To deal with the risk of
falling and injury, the body integrates voluntary movements with so-called ‘associated postural
adjustments’. These adjustments are involuntary and smoothly organized into the movement
repertoire to ensure accurate and harmonious motion. Based on the timing relative to the event
of perturbation, the adjustments can be arbitrarily classified into two postural control systems
—adaptation and anticipation (Redfern et al. 2001)—which in turn may be linked to situation
awareness, perception and comprehension of the environment and the ability to project future
states. Endsley (1995) gives a thorough definition of situation awareness; one class is concerned
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with the physical capacity to avoid or accommodate the environmental (ecological) challenges;
another class is concerned with the competence to recognize them. Adaptation is reactive in
nature and involves the co-ordination of the neuromusculoskeletal system, while anticipation
is proactive and entails navigating through complex and often cluttered environments by using
multiple sensory inputs to assist in the control and adaptation of gait. The level of situation
awareness persons can achieve in a particular environment may dictate whether they anticipate
state changes potentially leading to loss of balance. A poor situation awareness may be
indicative of adaptive postural adjustments due to perturbations.
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Following the above discussion, one might anticipate that it is much easier to adapt one’s gait
properly when the slippery condition is steady than when rapid and unexpected variation in
slipperiness occur. There may not be sufficient injury statistics to confirm this statement, but
a study by Merrild and Bak (1983) showed that certain high-risk winter days characterized by
drastic temperature changes, precipitation and snowfall, can cause an enormous increase in
pedestrian injuries due to falls initiated by slipping. Merrild and Bak (1983) also reported that
the proportion of fractures especially in the lower extremities, increased during the high-risk
days, and led to a redistribution of injuries in the lower extremities towards their proximal ends.
Fractures of the femoral neck and pelvis became more frequent and sprained ankles less
frequent than during normal winter days. A recent fall-study made in Norway (Bulajic-Kopiar
2000) confirmed that season affects the incidence of all types of fractures in elderly people,
and that slipping on ice or snow seems to be a causal mechanism behind this seasonal effect.
In Finland, Honkanen (1982) concluded that the causative role of slippery weather conditions
in falls was likely to be more important than any other single factor. He estimated that falls
due to slipping during winter months, as compared to summer months, formed 25% ‘excess’
of all falls on the same level and 47% ‘excess’ of slip-related falls.
2.5. Protective movements during falling
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A fall by definition is to descend freely by the force of gravity. A fall occurs when human
balance is perturbed beyond a certain recoverable point. When examining forward falls on an
outstretched hand from low heights, Chiu and Robinovitch (1998) predicted that fall heights
greater than 0.6 m carry significant risk for wrist fractures to the distal radius (the most common
type of fracture in the under-75 population). Robinovitch et al. (1996) and Hsiao and
Robinovitch (1998) studied common protective movements that govern unexpected falls from
standing height. They measured body segment movements when young subjects were standing
on a mattress and attempted to prevent themselves from falling after the mattress was made to
translate abruptly. The subjects were more than twice as likely to fall after anterior translations
of the feet (posterior fall) when compared to lateral or posterior translations (anterior falls) of
the feet. Since a posterior fall would most likely follow a foot slide during early stance, this
study may give us some hints on possible fall mechanisms and protective movements due to
slip-induced falls as well. The results by Hsiao and Robinovitch (1998) suggested that body
segment movements during falls, rather than being random and unpredictable, involved a
repeatable series of responses facilitating a safe landing. Posterior falls involved pelvic impact
in more than 90% of their experiments, but only in 23% of the lateral falls and in none of the
anterior falls. In the falls that resulted in impact to the pelvis, a complex sequence of upper
extremity movements allowed subjects to impact their wrist at nearly the same instant as the
pelvis, suggesting a sharing of contact energy between the two body parts. Hsiao and
Robinovitch (1999) predicted—using experimental and mathematical models of balance
recovery by stepping—that a successful recovery of falling perturbations was governed by a
coupling between step length, step execution time, and leg length (cf. Redfern et al. 2001).
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3. Measurement of slipperiness and falling risks
3.1. Perception of slipperiness
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During walking one is often unaware of the fact that sliding or creep between the footwear and
the floor occurs on contaminated surfaces and even on dry ‘non-slippery’ surfaces in the very
beginning of the heel contact phase (Perkins 1978, Strandberg and Lanshammar 1981, Perkins
and Wilson 1983). In fact, Lanshammar and Strandberg (1983) showed that there typically
exists an initial spike in the fore-aft component of the ground reaction force immediately after
heel strike. The existence of this spike was explained by a small but detectable non-zero
backward horizontal motion of the rear edge of the shoe heel. Lanshammar and Strandberg
(1983) concluded that since the foot must be strongly decelerated shortly before heel strike an
overshoot reaction of the human locomotor system could explain this behaviour.
The lengths of such small slip incidents (also termed micro-slips) on dry, nonslippery surfaces
were less than 1 cm, according to Leamon and Son (1989). The tendency of human subjects
to such movement on a slippery surface was determined by Leamon and Li (1990), who
redefined the term micro-slip to cover a range from zero to 3 cm. Their data indicated that any
slip distance less than 3 cm would be detected in only 50% of the occasions, and that a slip
distance in excess of 3 cm would be perceived as a slippery condition.
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Vision seems to be the only sensory mode that proactively allows a person to identify a slippery
floor surface before stepping over it. The other postural control systems may require that one
already has walked over a slippery surface for getting the feedback to properly adapt one’s
gait. Visual control of locomotion has been classified into both avoidance and accommodation
strategies (Patla 1991). Avoidance strategies include, for instance, changing the foot placement,
increasing ground clearance, changing the direction of gait, and controlling the velocity of the
swing foot. Redfern and Schuman (1994) emphasized that temporal control is as critical as
spatial control in placement of the foot to maintain balance during gait. Accommodation
strategies involve longer term modifications, such as reducing step length on a slippery surface.
3.2. Biomechanically-oriented approaches
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Ground reaction forces and sagittal plane body movements have been investigated in slippery
conditions (as well as in non-slippery baseline conditions) during walking on level and inclined
surfaces as well as during load carrying (Perkins 1978, Strandberg and Lanshammar 1981,
Morach 1993, Hirvonen et al. 1994, McVay and Redfern 1994, Redfern and Rhoades 1996,
Myung and Smith 1997, Redfern and DiPasqale 1997). In these studies, researchers especially
focused on measuring leg and heel kinematics, normal and shear forces in the shoe/floor
contact surface, and friction usage (or required friction) as well as joint angles for the ankle,
knee and hip. The effects of ramp angle to forces at the shoe/floor interface were measured
while walking up and down ramps (McVay and Redfern 1994, Redfern and DiPasqale 1997).
Also protective responses and hand/arm or trunk movements for restoring balance after
slipping, falling frequencies, and/or slip/fall probabilities were examined (Strandberg and
Lanshammar 1981, Strandberg 1985, Hanson et al. 1999). Some investigators focused on
measuring slip distances and micro-slipping during walking as indicators for slipping and
falling hazards (Leamon and Son 1989, Leamon and Li 1990).
Strandberg and Lanshammar (1981) simulated unexpected heel slips when approaching a force
platform which was lubricated with water and detergent in 76 trials (61%) out of 124. The trials
were categorized into two main groups, grips (85 trials) and skids (39 trials). The skids were
split into two categories, slip-sticks (16 trials) and falls (23 trials), while the slip-sticks were
finally differentiated into mini-, midi- and maxi-slips. The subjects were unaware of the sliding
motion in the mini-slips, in the midi-slips no apparent gait disturbances were observed, but in
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the maxi-slips compensatory swing-leg and arm motions occurred. The peak sliding velocity
was above walking speed (1 – 2 m s−1) in the skids that resulted in a fall, but did not normally
exceed 0.5 m s−1 in the remaining skids called slip-sticks, where the subjects were able to
regain balance. These slipping experiments indicated that a slip was likely to result in a fall if
the sliding exceeded 0.1 m in distance or 0.5 m s−1 in velocity. A recent study by Brady et
al. (2000) suggested that foot displacement rather than the velocity of the slipping foot would
predict the outcome of a slip, and that the threshold values for fall avoidance may be higher
than previously thought. Roughly 75% of the subjects in these bare foot slipping experiments
over an oily vinyl surface were able to recover balance, when the slip distance was 0.2 m and
the slipping foot velocity was 1.1 m s−1 (cf. Redfern et al. 2001).
Morach (1993) performed slipping experiments on contaminated floors (oil, glycerol, and
water) and found that the horizontal foot velocity in forward direction immediately (i.e. during
10 ms prior to heel contact) varied between 0.3 and 2.75 m s−1 (the average walking speed was
1.5 m s−1) depending on the type of slip, i.e. slip start after a short (more than 26 ms) static
position (106 trials), immediate (during less than 6 ms) slip start (300 trials), and unclear (6 to
26 ms) slip start (112 trials). The highest foot velocities occurred on a steel floor with oil as
lubricant, when there was an immediate slip start after heel landing.
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Winter (1991) and Lockhart (1997) reported a higher heel contact velocity in the horizontal
direction for older subjects compared with younger subjects on dry floor surfaces, even though
the walking velocity of the older subjects was slower. On a slippery floor surface (oily vinyl
tile), a higher heel contact velocity (figure 3) coupled with a slower transition of whole body
centre-of-mass velocity of older individuals significantly affected sliding heel velocity and
dynamic friction demand. Consequently, the result was longer slip distances and increased
falling frequencies for the older compared to younger individuals (Lockhart et al. 2000a, b).
Lockhart et al. (2002) conducted a laboratory study to determine how sensory changes in
elderly people affected subjective assessments of floor slipperiness and how these were
associated with friction demand characteristics and slip distance. The results indicated that
sensory changes in the elderly increased the likelihood of slips and falls more than in their
younger counterparts due to incorrect perceptions of floor slipperiness and uncompensated slip
parameters, such as slip distance and adjusted friction utilization (cf. section 5.4).
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Redfern and Rhoades (1996) reported experimental results concerning heel dynamics of
subjects during load carrying (boxes of varying weights up to 13.5 kg) at three different
walking cadences (70, 90 and 100 steps per minute). The surface condition studied was
probably dry, but some micro-slipping occurred during the experiments after heel contact. The
horizontal (forward) heel velocity decreased from a pre-heel contact maximum of 4.5 m s−1 at
the end of the swing phase to between 0.14 and 0.24 m s−1 at heel contact in the beginning of
the stance phase. The heel pitch angle at heel landing was between 20 and 25° and decreased
to foot flat within about 100 ms after initial contact. The heel came to a complete stop during
micro-slip conditions about 100 ms after the impact. Carrying loads showed, according to
Redfern and Rhoades (1996), the same dynamic qualities as normal walking. They concluded
that load carrying had only minor effects on the heel movement parameters. Recently, Myung
and Smith (1997) argued that this was true only for dry conditions while oily floors significantly
affected those parameters. They recorded for oily vinyl and plywood floors horizontal heel
landing velocities of at least 0.6 to 1.4 m s−1 during load carrying experiments with ten young
male subjects. Myung and Smith (1997) also found that stride length was reduced as floor
slipperiness and load carrying levels increased (cf. Redfern et al. 2001).
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3.3. Psychophysical and subjective approaches
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Human-centred approaches for the measurement of slipperiness may be psychophysical in
nature. A perceived magnitude of ‘slipperiness’ can be quantified on a psychophysical scale
using ‘foot movement’ or ‘postural instability’ as the physical stimulus. The stimulus can be
measured subjectively using opinions and preferences but can be measured objectively too.
Objective measures are, for instance, video filming or high-speed imaging of gait and may also
include ground reaction forces obtained with force platforms. Human-centred approaches may
involve simultaneous acquisition of objective biomechanical data and subjectively perceived
data (Strandberg 1985, Grönqvist et al. 1993). Subjective opinion data is quantitatively treated
on an ordinal (category) scale, while a nominal scale can be used for analysing motion and
force data (slip distance, slip velocity, friction usage, joint angles, etc.). Engström and Burns
(2000) spoke for psychophysical scaling (continuous ratio scales) as an alternative to common
category scaling of opinions and preferences.
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A number of ‘purely’ subjective approaches (e.g. paired comparisons) have been applied to
measure slipperiness. Human subjects seem to be capable of differentiating the slipperiness of
floors (Yoshioka et al. 1978, 1979, Swensen et al. 1992, Myung et al. 1993, Chiou et al.
1996) and footwear (Strandberg et al. 1985, Tisserand 1985, Nagata 1989, Grönqvist et al.
1993) in dry, wet, or contaminated conditions. Cohen and Cohen (1994a, b) pointed out that
tactile sliding resistance cues are the most sensitive predictors of the coefficient of friction
under various experimental conditions but particularly on wet surfaces. Leamon and Son
(1989) and Myung et al. (1992) suggested that measuring micro-slip length or slip distance
during slipping incidents might be a better means to estimate slipperiness than the apparatusbased friction measurement techniques. Recently Chiou et al. (2000) reported findings of
workers’ perceived sense of slip during standing task performance (e.g. a lateral reach task)
and further related their sensory slipperiness scale to subjects’ postural sway and instability.
They found that workers who were cautious in assessing surface slipperiness had less postural
instability during task performance.
Skiba et al. (1986), Jung and Schenk (1989, 1990) and Jung and Rütten (1992) evaluated
walking test methods used for measuring the slipperiness of floor coverings and safety footwear
on an inclined plane on dry, wet and oily surfaces in the laboratory. The inclination angle at a
point when walking down the ramp became unsafe gave the subjective estimate for slip
resistance by transforming it geometrically to a friction value. These papers also discussed the
validity and reliability of such tests, use of standard reference materials and separation
characteristics for choosing a limited number of test subjects for standardized slipperiness
measurements.
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Subjective and combined human-centred approaches have been utilized to assess footwear
friction on ice. At least two test rigs have been developed by Bruce et al. (1986) and Manning
et al. (1991): the first test rig consists of a tubular metal frame with four legs, fitted with large
castor action wheels. A test subject, standing on both feet on an icy surface, is dragged across
the substrate. Bruce et al. (1986) conducted tests at an ice skating rink and the horizontal
(frictional) force in the shoe/ice interface was measured by a load cell (spring balance) at a low
sliding velocity. The frame of the rig prevented the subject from falling. The second technique,
by Manning et al. (1991), can be applied to measure the slipperiness of a footwear/ice interface
as well as a footwear/floor interface. In this method, a subject is walking (backward steps) on
a surface to be assessed while pulling against a spring and supported by a fall-arrest harness.
The subject is also protected by two handles suspended from a pulley that moved freely on an
overhead rail. The load cell is positioned between the harness belt of the subject and a rigid
base (e.g. a wall). Manning and Jones (1993) modified this walking traction rig for mobile field
use as well. Since the resisting force is not measured in the shoe/floor interface, the load cell
measures indirectly the maximum frictional force before feet will slip. Scheil and Windhövel
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(1994), who criticized the validity and precision of this method, evaluated the latter mobile
version of the above method on various floor surfaces attached to a force platform. The walking
action was abnormal and the friction readings were biased by inertial forces that increased the
load cell reading (horizontal force) compared to the measured friction force in the shoe/floor
interface.
3.4. Rating scales for balance and walking safety
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3.4.1.Balance and functional abilities—Rating scales, for example Bohannon’s ordinal
scale for standing balance (Bohannon and Leary 1997) and the ‘Timed Up and Go’ test
(Podsiadlo and Richardsson 1991) have been used to assess balance capabilities of the
individuals, but no perfect standard exists among these methods. An objective test often used
today is the Berg balance test (Berg 1989, Berg et al. 1992a). Combined with a test of walking
speed the Berg balance test shows a high sensitivity and specificity as a screening method
(Berg et al. 1992a). Berg’s balance scale is an instrument for quantitative evaluation of balance,
a scale with 14 moments, testing static and dynamic balance with increasing difficulty. All
moments are described in a manual with grades from 0 to 4 with a maximum of 56 points. The
test takes 20 min to perform. The Berg balance scale has good concurrent validity with many
other methods used in this area; the Bartel Index for activities of daily life, Tinetti’s sub-scale
for balance (Tinetti et al. 1986), the Fugl-Meyer scale for isolated movements and balance
(Fugl-Meyer et al. 1975), the `Get-up and Go’ test (Mathias et al. 1986), the ‘Timed Up and
Go’ test (Podsiadlo and Richardson 1991) and a test of functional mobility (Berg et al.
1992b).
The test ‘Get-up and Go’ measures a person’s risk of falling according to a 5-grade scale;
normal, very slightly abnormal, mildly abnormal, moderately abnormal and severely abnormal
(Mathias et al. 1986). A person is observed while raising from a chair with armrests, walking
3 m and then returning to the chair. The test focuses on many basic functional aspects and is
easy to perform. The `Timed Up and Go’ (Podsiadlo and Richardsson 1991) is a balance test
focusing on walking speed and functional ability. The time to perform the test from leaving
the chair until sitting on the chair again is measured by a stop-watch.
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A functional perspective is important when dealing with balance problems in a test situation.
Basic functional abilities for people of all ages are the ability to go and rise from bed, sit down
and rise from a chair or toilet, and to walk a few steps (Isaacs 1985). These abilities are
prerequisites for elderly people to live independently in their own home or in open home care
without assistance. Functional abilities are important for the evaluation of rehabilitation effects
in patient groups. For that purpose, an index of muscle function and a battery of functional
performance tests for the lower extremities have been developed. The total index can be divided
into four separate areas: pre-tests of general functioning; muscle strength; muscular endurance;
and balance and co-ordination (Ekdahl et al. 1989).
3.4.2. Evaluation of icy surfaces and anti-skid devices—Methods to describe
functional problems in walking on different slippery surfaces during winter conditions have
been developed by Gard and Lundborg (2000) as rating scales for evaluating walking safety
and balance, and as observation scales to observe posture and movements during walking. The
methods were then used to investigate functional problems when wearing different anti-skid
devices (attached to shoes) for slip and fall protection. First, rating scales for perceived walking
safety and balance were developed and tested for reliability. Inter-reliability tests of these scales
were done from video-recordings of walking with different anti-skid devices on a number of
surfaces in experiments done by two experienced physical therapists. The percentage of
agreement between the physical therapists was 86% (walking safety) and 88% (walking
balance). Second, four rating scales for evaluation of observed walking movements were
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developed by a physical therapist, trained in movement analysis. The dimensions evaluated
were:(1) walking posture and movements including normal muscle function in the hip and
knee; (2) walking posture and movements in the rest of the body (head, shoulders and arms);
(3) heel strike; and (4) toe-off. All four dimensions were evaluated by observation scales
ranging from 0 to 3. The inter-reliability of these four observation scales were measured as the
percentage of agreement between the physical therapists and was 85, 80, 86 and 85%,
respectively (Gard and Lundborg 2000).
Abeysekera and Gao (2001) performed practical walk tests using a 5-point rating scale to
evaluate slipping risks on a number of icy and snowy surfaces when wearing different types
of footwear. Such walk tests may be used to assess the performance of footwear, or anti-skid
devices, but also to study the human responses involved in slipping accidents. Gard and
Lundborg (2001) carried out practical tests of 25 different anti-skid devices on the Swedish
market, on different icy surfaces with gravel, sand, salt or snow on ice, and with pure ice. The
anti-skid devices were described according to each subject’s perception of walking safety,
walking balance and priority for own use. The posture and movements during walking were
analysed by an expert physical therapist. One of the tested anti-skid devices was judged to be
good regarding walking safety and balance and was chosen by subjects for their own preferred
use (Gard and Lundborg 2001).
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3.5. Measurement of sudden movements
Slipping may involve rapid movements resulting from a person’s effort to regain balance. A
method has been developed to detect such movements by measuring trunk acceleration during
walking (Hirvonen et al. 1994). By attenuating normal movement signals by band-pass
filtering, it became possible to discriminate signals caused by unexpected movements. The
portable equipment consisted of a small acceleration transducer, a pre-amplifier and a pocket
computer (Hirvonen et al. 1994). Unexpected trunk movements during slipping of 20 male
volunteers who walked at two speeds, normal and race walking, along a horizontal track were
monitored. The peak acceleration levels of the trunk increased significantly in slipping
incidents compared to normal or race walking without slipping, both in the antero-posterior
and medio-lateral directions. The peak accelerations varied from 0.5 to 4.5 g (1 g = 9.81 m
s−2) during slipping, while the accelerations were less than 0.5 g during walking without
slipping. The mean peak accelerations of the trunk during slipping incidents were of the order
1.3 g for the antero-posterior and 1.0 g for the medio-lateral directions, respectively. The levels
were significantly higher than during reference non-slipping conditions. The seriousness of
these slip incidents was observed using video filming: no observable slip; controlled slip;
vigorous slip; extremely vigorous slip. Most experiments resulted in either controlled or
vigorous slips.
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Questionnaires can be used to study the risk of accidents and the role of sudden movements at
work (Hirvonen et al. 1996). Workers were asked to subjectively rate the risk of accidents in
their work tasks associated with walking on slippery or untidy surfaces, on uneven surfaces,
and on stairs. For each question four alternatives of the risk were given: not at all (score 1); a
little (score 2); moderately (score 3); much (score 4). Based on these four questions, a sum
score of the risk of accident was calculated and classified into three categories: low (score 4 –
8); moderate (score 9 – 12); high (score 13 – 16). In a follow-up intervention at the workplace,
a total of 297 unexpected incidents occurred during which the trunk acceleration level exceeded
1.0 g. The number of alarms (i.e. acceleration levels exceeding 1.0 g) was significantly greater
for the high risk compared to the low risk category. However, the intensity of sudden
movements, measured as the peak acceleration of the trunk, did not differ between the three
self-assessed categories of accident risk.
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3.6. Comparative evaluations of test methods
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At least two studies have reported comparative evaluations of test procedures involving human
subjects (Jung and Fischer 1993, deLange and Grönqvist 1997). The objective of the first study
was to investigate the validity of mechanical laboratory-based test methods for measuring slip
resistance of safety footwear when the same test protocol and procedure was applied in each
participating laboratory. The second study aimed at bridging the gap between human-centred
test procedures and mechanical slip test methods.
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Ten subjective and combined human-centred test procedures were compared in the first study
(Jung and Fischer 1993). Male subjects (4 to 8 depending on the test) wore five different types
of safety footwear and walked over a smooth stainless steel surface contaminated with viscous
glycerol or a mixture of water and wetting agent. The walking tests were performed on a straight
level surface (3 paired comparison methods) or an inclined surface (7 walk-test methods down
or up a ramp). The paired comparison methods yielded either a subjective scoring, a friction
usage value, or a slip and fall frequency as the outcome (footwear rating). The outcomes of the
ramp tests were either an average maximum inclination angle for safe walking (6 methods) or
a paired comparison scoring using two fixed inclination angles (1 method). The rank correlation
coefficients between the footwear ratings obtained with these seven human-centred test
methods varied from 0.90 to −0.70. Of all the 44 comparisons only six correlation coefficients
(14%) between test methods were statistically significant at the 95% probability level. Only
two of these significant results were obtained between different types of walking tests, one
level surface test and two similar ramp tests. A major limitation of this inter-laboratory
experiment was that the assessed footwear did not exhibit large differences in terms of their
slip resistance. The validity of the mechanical slip tests could not be confirmed in this study.
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Three subjective and combined test procedures were compared in the second study (deLange
and Grönqvist 1997). All three tests were also involved in the first study by Jung and Fischer
(1993): an inclined surface (walking down a ramp) applying ramp angle as safety criterion
(Jung and Schenk 1990) and two level surface test procedures applying subjective scorings
based on paired comparisons of footwear as safety criteria. The level surface test methods used
two different approaches. The first method was based on human action while walking, stopping
and accelerating on a slippery surface (Tisserand 1985) and the second method was based on
the heel landing phase when the subject stepped from a slip-resistant surface onto a slippery
surface (Grönqvist et al. 1993). Male subjects (2 to 7 depending on the test) were wearing six
different types of footwear for professional use and walked over a smooth stainless steel surface
or a rough vinyl flooring contaminated with viscous glycerol or a mixture of water and
detergent. The water and detergent conditions were assessed only with the ramp test method,
so that no comparative data between the methods was available for this condition. The results
of the two level surface test methods differed significantly for test condition steel/ glycerol,
probably due to differences in performing the tasks (walking at a constant pace vs. accelerating,
etc.). However, the ratings for two test conditions (steel/ glycerol, PVC/glycerol) between the
second level surface method and the ramp test method were similar despite the two different
approaches (walking on a level vs. inclined surface).
4. Modelling slip recovery and fall avoidance
4.1. Difference between static and kinetic friction
Tisserand (1985) suggested using a simple biomechanical model (considering a mechanical
equilibrium of forces at the moment the foot strikes the ground) that the slipping velocity (v)
is a function of the difference between the static (Fs) and kinetic (Fk) friction forces:
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where M is the mass of the body parts in motion and t is the time.
Hence, Tisserand (1985) concluded that for a given coefficient of kinetic friction the
seriousness of the fall would be directly proportional to the coefficient of static friction.
Tisserand also presented experimental subjective evaluation data in support of his reasoning.
In fact, Tisserand went even further in his analysis allowing him to assume that this relationship
is valid even if there is no initial static phase as the heel strikes the ground. Tisserand (1985:
1030) completed the analysis with the following statement that ‘preventing initial slipping of
the foot requires a high or sufficient static friction force, while limiting slip velocity to avoid
loss of balance requires a small difference between static and kinetic friction forces and that
the latter is always required to prevent falling and injury’.
4.2. Critical slip distance
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Strandberg and Lanshammar (1981) estimated that the critical sliding velocity leading to falling
after a heel slip was about 0.5 m s−1, and that the required minimum kinetic friction coefficient
was about 0.2 during normal level walking. If the above figures are accepted as critical for a
hazardous slip and fall, then the boundary slip distance s between an avoidable and an
unavoidable fall would be about 6 cm (Grönqvist et al. 1999), since:
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The above equation, where g is the acceleration of gravity, v is the velocity of sliding, and μ
is the coefficient of friction, is derived from the work done by the frictional force. This equation,
which governs the distance required to bring a moving object to a stop by friction, is based on
the assumption of a constant initial sliding velocity. Nevertheless, it indicates that if the
coefficient of friction increases for example to 0.4, then the boundary slip distance would be
reduced to 3 cm, which would be perceived to be slippery by only 50% of the subjects in a
slipping experiment (cf. section 3.1). Obviously, an increasingly safer situation from the point
of view of balance recovery would follow. On the contrary, if the critical values (s = 0.2 m and
v = 1.1 m s−1) for slip distance and velocity suggested by Brady et al. (2000) would be applied
in this equation, then the minimum coefficient of friction in the interface would need to be
about 0.3 for a fall recovery.
4.3. Walking speed and step length
Gait and anthropometric parameters such as length of stride may, however, affect the above
critical sliding velocity of the heel. In fact, Strandberg (1985) presented a falling criterion based
on the biomechanical skidding data by Strandberg and Lanshammar (1981), using a simple
biomechanical inverted pendulum model of the human body during a single stance phase. The
model predicted that the maximum permissible (without falling) sliding velocity (vs) increases
with walking speed (vw) and decreases with step length (L).
The model’s falling criterion is:
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where k and c are constants and M is the mass of the inverted pendulum, centred the distance
h above the heel/floor contact point, and with J the mass moment of inertia about this contact
point.
A higher walking speed (vw) may be favourable, if the step length (L) is kept constant and if
no cornering forces are required. The horizontal velocity of the body COM must be sufficiently
greater than the sliding velocity of the BOS. Otherwise, the COM velocity relative to the BOS
velocity will become negative before COM has reached a position above the BOS, and a
backwards falling motion will begin. This gait pattern with short steps in comparison to the
walking speed will also result in a reduction of the body’s COM vertical acceleration, whether
it is the primary aim or not. The relationship between walking speed, step length and friction
demand has been investigated by Lindberg and Stalhandske (1981). Recently, You et al.
(2001) confirmed that the displacement and velocity of the COM with respect to the BOS can
be used to discriminate slip/non-slip incidents of the heel in barefoot walking over a slippery
soap patch. During the critical double-support period from heel strike to contra-lateral toe-off,
a smaller displacement and a faster velocity of the COM were important for regaining balance.
5. Criteria for safe friction
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This section will bring some insight to basic safety criteria, frictional demands, and minimum
friction thresholds proposed for a number of activities and work tasks including walking,
running, and manual exertion. The criteria for some special risk groups (mobility disabled and
the elderly) are also discussed. Frictional demands are related to either a baseline non-slip
‘required friction’ or a more global ‘friction usage’ (i.e. ‘utilized friction’) criterion, which is
independent of whether a slip occurs or not (cf. Grönqvist et al. 2001a).
5.1. Level walking
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The frictional demand, based on human experiments during normal level walking, has been
found to vary between 0.15 and 0.30 (Perkins 1978, James 1980, Strandberg and Lanshammar
1981, Bring 1982, Skiba et al. 1983). See also Redfern et al. (2001) who discusses the role of
safety criteria based on ground reaction forces during locomotion without slipping and during
slips. The significance of the horizontal (shear) to vertical ground reaction force ratio (FH/
FV) is that it indicates where in the step cycle a slip would most probably start (figure 4).
However, if a foot slide starts, the evolution of frictional shear forces in the shoe/floor interface
would determine whether the slip can be retarded or stopped and balance recovered. Hence,
the measured friction coefficient should always be greater than the utilized or the required
friction coefficient (cf. Grönqvist et al. 2001a, Redfern et al. 2001). Hanson et al. (1999)
applied the difference between measured and required friction as safety criterion instead of the
friction ratio, which was proposed by Carlsöö (1962).
Grönqvist et al. (2001b) found that the contact time related variation in utilized friction in the
presence of a slippery contaminant was large (possibly due to gait adaptations) in response to
the reduced available (measured) friction between the interacting surfaces. In this case, a single
safety limit for the friction coefficient, such as the maximum peak value after heel contact,
may not be an appropriate discriminator between safe and dangerous conditions. The evolution
of the friction coefficient over contact time seems to be at least equally important.
Perkins (1978) reported both ‘maximum’ and ‘average’ peak values for the frictional demand.
Strandberg and Lanshammar (1981) measured the friction usage peak, FH/FV, approximately
0.1 s after heel strike. The peak value in their experiments was on the average 0.17 when there
was no skidding (grip), 0.13 when the subject was unaware of the sliding motion or regained
balance (slip-stick), and 0.07 when the skid resulted in a fall. Kinetic friction properties
appeared to be more important than static ones, because in most of their walking experiments
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the heel slid upon first contact even without a lubricant. On the other hand, Strandberg et al.
(1985) and Grönqvist et al. (1993) also reported stance time-averaged friction usage values for
estimating frictional demands during walking over continuously and unexpectedly slippery
surfaces, respectively. The values reported by Strandberg et al. (1985) were based on the mean
stance time for one step (approximately 0.5 – 0.7 s). These values were of the order 0.25 for
the safest experiments on a smooth steel surface with glycerol as contaminant. In comparison,
the mean FH/FV ratios during time-interval 100 – 150 ms after heel contact, for the safest
experiments without falling, reported by Grönqvist et al. (1993) were much lower (between
0.11 and 0.13) in the same test condition (steel/ glycerol).
Strandberg (1983) favoured 0.20 as a safe limit for the coefficient of kinetic friction in level
walking, indicating that he added a safety margin to the measured frictional demand (cf. peak
ratios of the ‘grip’ and ‘slip-stick’ trials above). Nevertheless, he pointed out that the adequate
value was depending greatly on anthropometric and gait characteristics as well as the method
of measurement. He found that friction properties were most important for preventing falls at
sliding velocities below 0.5 m s−1. In contrast, static friction values proposed in the USA in
the mid-1970s used 0.40 to 0.50 as lower limits for safe walking (Brungraber 1976). These
values are not in line with the actual frictional demands based on human walking on level
surfaces, and thus may be more an indication of practical eligibility for the test methods in
question.
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5.2.Other modes of locomotion
In general, minimum coefficient of friction limit values should be correlated to normal
variability of human gait, since walking speed, stride length and anthropometric parameters
may greatly affect the frictional demands during locomotion (Carlsöö 1962, James 1983,
Andres et al. 1992, Myung et al. 1992). McVay and Redfern (1994) found that the mean across
subjects of the peak required friction increased from about 0.25 to 0.50 as ramp angle increased
from 0° in level walking to 20° on an inclined surface. Their study indicated that geometric
predictions based on ramp inclination angles did not fully explain the actual changes in
frictional demands and resulted in excessively high values for the required friction limit.
Walking up the ramp produced greater frictional demands than walking down the ramp. Ground
reaction forces on inclined surfaces are discussed extensively by Redfern et al. (2001).
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Depending on the type of movement (walking on a ramp or on stairs) James (1980) referred
to limit values between 0.15 and 0.40. Harper et al. (1967) and Skiba et al. (1983) referred to
limit values between 0.30 and 0.60 during stopping of motion, curving and walking on a
slope. Later Skiba (1988) defined that the safety limit for the kinetic friction coefficient, based
on the forces measured during human walking and the social acceptance of the risk of slipping,
would be 0.43 at sliding speeds of at least 0.25 m s−1. At heel strike in running gait the peak
FH/FV is typically slightly greater (about 0.30) compared to walking, and this difference is
even greater at toe-off when the force ratio peak is about 0.45 (Vaughan 1984). Jumping during
exiting commercial tractors, trailers and trucks can produce large impact forces in the shoe/
ground interface (Fathallah and Cotnam 2000) and may increase the friction demand as well
as the risk of slipping (Fathallah et al. 2000). The average peak required friction range was
from 0.13 to 0.33 depending on the vehicle type, jumping height, and the use of safety aids
such as steps and grab-rails.
Skiba et al. (1985) reported that the peak friction usage at foot contact during stair ascent was
lower than during normal level walking (0.17 versus 0.21). During stair descent, the peak
friction usage at foot strike was lower than during normal level walking (0.12 versus 0.21) but
higher during the push-off phase (0.34 versus 0.20) according to the same study. Christina et
al. (2000) found that the peak frictional demand at foot strike during stair descent was
remarkably similar to level walking (i.e. between 0.30 and 0.32) but that the required friction
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was lower during the push-off (0.26). Note that the reported friction usage values were
contradictory in these two studies. Redfern et al. (2001) also discusses ground reaction forces
during stair ambulation.
5.3. Manual exertion
Kroemer (1974) measured horizontal push and pull forces when subjects were standing in
working positions on various surfaces. Forces exerted while braced against a footrest or wall
were compared against the forces exerted while standing on high, medium and low traction
surfaces. The mean push and pull forces exerted were reduced considerably depending on the
slipperiness of the surfaces: the forces exerted were roughly 500 – 750 N for the braced
situation, 300 N for the high traction surface (static friction coefficient μ>0.9), 200 N for the
medium traction surface (μ∼0.6), and 100 N for the low traction surface (0.2<μ<0.3). Ciriello
et al. (2001) investigated maximum acceptable horizontal and vertical forces of dynamic
pushing on high and low friction floors. They found that the ‘required’ friction coefficient (i.e.
the horizontal to vertical shoe/floor force ratio required to sustain a push-cart movement) was
0.32 for the high friction floor but only 0.19 for the low friction floor. However, push duration
on the low friction floor was significantly longer and slip potential greater than on the high
friction floor.
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Grieve (1979, 1983) examined limitations of performance due to friction and static friction
limits for avoiding slipping during manual exertion (lifting, pushing and pulling). Grieve found
that static manual exertion can create unavoidable slips due to high frictional requirements
(even >1) in some conditions, and concluded that more efforts should be concentrated on the
events that follow the foot slide. Zhao et al. (1987) showed that the determination of slipping
risks associated with lifting on inclined surfaces should not be based solely on the slope angle.
Dynamic lifting increases the ratio of tangential (shear) to normal forces compared to the static
condition. Consequently, Zhao et al. (1987) suggested that slope angle must be smaller than
the friction angle of the shoe/ground interface. For example, for a slope angle α of 15° the peak
force ratio of shear to normal forces would be 0.27 (= tan α) for the static case but in the range
of 0.30 to 0.36 for dynamic lifting.
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Kinoshita (1985) examined the effects of light and heavy loads on certain gait parameters and
found that the shear and normal components of the ground reaction force significantly increased
compared to habitual walking. However, the frictional requirements in terms of their ratio did
not seem to change due to different loads and carrying systems (double-pack and back-pack).
Analysis of spatial and temporal parameters of the gait patterns revealed that only the double
and single support periods of stance were affected by the changes in load. The double support
period, expressed as a percentage of the total support period, lengthened and the single support
period shortened significantly as the load increased.
5.4. Mobility disabled and the elderly
Buczek et al. (1990) emphasized that the slip resistance needs for mobility disabled may be
greater than for able-bodied persons. Their study indicated that the required coefficient of
friction near touch-down for the unaffected side of the mobility disabled person was
significantly higher (average 0.64) than for the able-bodied (average 0.31) regardless of the
speed (slow or fast) of walking, whereas no difference was observed for the push-off phase.
Christina et al. (2000) found in stair descent that the frictional demand at foot touch-down was
lower for the elderly (0.27 – 0.28) than for the younger subjects (0.30 – 0.32), indicating a safer
stair descent strategy chosen by the elderly (cf. section 5.2).
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On a dry level-walking surface (outdoor carpet), Lockhart et al. (2000a), found no statistically
significant differences in required coefficient of friction characteristics between young (0.176),
middle-aged (0.188), and elderly (0.192) adults. Lockhart et al. (2000b) also reported dynamic
frictional demand characteristics between these three age groups on a slippery floor surface
(oily vinyl tile) during slip-grip responses (i.e. slip recovery) by measuring adjusted friction
utilization (AFU). A typical kinetic and kinematic profile of a slip-grip response starting from
heel contact point on the oily vinyl tile floor surface is shown in figure 5. Heel contact was
defined as the point where vertical foot force exceeded 10 N. Initially, as indicated by the
horizontal heel position (figure 5(c)), the heel does not slip forward. The horizontal heel
velocity decreases (figure 5(b)) as the heel quickly decelerates (figure 5(a)), and both the
vertical downward force (figure 5(d)) and the horizontal forward force (figure 5(e)) increase.
Shortly after heel contact (approx. 60 ms), the heel begins to slip forward (SD1, figure 5(c)).
Afterwards, the sliding heel reaches Peak Sliding Heel Velocity (PSHV, figure 5(b)). During
this slipping period, the heel accelerates reaching the maximum (figure 5(a)) near the midpoint of the sliding heel velocity profile (figure 5(b)). At this time, both the vertical and the
horizontal foot forces decrease. After reaching the maximum heel velocity (approx. 180 ms
after heel contact), the sliding heel velocity decreases to a minimum, halting further slipping
(figure 5 (b)).
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AFU is the measured ratio of the horizontal to vertical foot force at the peak sliding heel velocity
point (figure 5(f)) and represents the subject’s ability to adjust to dynamic frictional
requirements during slipping. The significance of this ratio is that it indicates where in the gait
profile compensation for a slip is most likely to occur. The AFU of younger individuals (0.074)
was adjusted within the dynamic friction requirements (0.08) of the oily vinyl tile floor surface.
However, the AFU of middle age (0.10) and older individuals (0.12) was not adjusted within
the dynamic friction requirements. Consequently, the result was longer slip distances and
increased frequency of falls for these groups.
6. Conclusions
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Why do we need to measure slipperiness? Do not current theories on friction mechanisms and
biomechanical slip and fall models satisfactorily predict the risks associated with slipperiness?
In fact, the underlying mechanisms of slips and falls are not yet fully understood and, therefore,
we are not capable of measuring the risks properly. Nevertheless, human-centred approaches
for slipperiness measurement do already have many applications. In particular, they are utilized
to develop research hypotheses and models to predict workplace risks due to slipping and
falling. They are equally important as alternatives to and as means to validate apparatus-based
friction measurements, and as practical tools for routine control of slip resistance properties of
footwear, anti-skid devices, and floor surfaces.
6.1. Strengths and weaknesses of human-centred approaches
•
Strengths of human-centred approaches over mechanical measurement
methodologies are given below:
•
the methods are inherently valid for the situation being examined, because human
subjects are involved in the experiment, while individual behaviour affects the
outcome measures;
•
the human factor aspect is included in the analysis and can be partly controlled (e.g.
walking speed and cadence, anticipation versus unexpectedly slippery surfaces);
•
they allow combining biomechanical measurement data with observations of
performance and/or subjective ratings (Strandberg 1985, Strandberg et al. 1985, Jung
and Schenk 1989, 1990, Hanson et al. 1999).
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One major concern is that the results obtained with different human-centred methodologies
may vary to a great extent, and although it may be a true effect it is sometimes caused by
experimental bias; Jung and Fischer (1993) reported in an inter-laboratory study that the
outcome of two similar ramp test methods was significantly different for the same test
conditions. A possible underlying reason may have been the design of the experimental
protocol. Obviously one must strictly control all relevant measurement parameters—such as
walking speed and cadence, anticipation of slipperiness, use of safety harness, test
environment, sample properties and pre-treatment—in human-centred trials as one needs to do
during mechanical friction tests.
Weaknesses of human-centred approaches compared to mechanical slipperiness measurements
include the following:
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•
human-centred experiments are time-consuming and expensive;
•
they are mostly suitable for the laboratory environment (field applications are rare,
cf. Manning and Jones 1993, Hirvonen et al. 1996);
•
inter- and intra-individual variation in gait due to anticipation and adaptation to
hazards may limit their use (Grönqvist et al. 1993);
•
learning can affect the measured outcomes, such as magnitude of friction usage and
ramp inclination angle or EMG activity changes over repeated trials (Skiba et al.
1986, Tang et al. 1998);
•
a safety harness used to protect subjects from falling can be a confounding factor in
many experimental set-ups and may affect the measured outcomes, such as ground
reaction forces, required friction, slip velocity and/or distance (Lockhart et al.
2000a, b).
6.2. differentiation between slipping and falling
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Various definitions of slipping and falling have been used in published studies (cf. Strandberg
and Lanshammar 1981, Grönqvist et al. 1993, Hirvonen et al. 1994, Hanson et al. 1999). More
precise definitions are needed to discriminate between different outcomes of a slip, for instance,
when does a controlled slip (that can be terminated) turn into an uncontrolled slip and fall? The
sliding distance of the foot was applied as discriminator between recoverable slips and likely
falls by Grönqvist et al. (1993). Hanson et al. (1999) defined a slip or fall based on each
subject’s perception; the subjects were asked after each trial whether they subjectively felt ‘no
slip’, ‘slip and recovery’ or ‘slip and fall’. The subjects were also instructed to define a trial as
a ‘slip and fall’ if they required support from a safety harness used to protect them against
falling, or if they slid to the end of the force platform that measured the ground reaction force.
Novel experiments are needed to model effective slip recovery and fall avoidance strategies.
Pai and Patton (1997) and Pai and Iqbal (1999) used an inverted pendulum model with a foot
segment to simulate centre of mass velocity-position constraints and movement termination
for balance recovery. In fact, recent studies suggest that in addition to foot displacement during
slipping (Brady et al. 2000), the movement of the body’s centre of mass over the base of support
plays a significant role in slip recovery and fall termination (Pai and Patton 1997, Pai and Iqbal
1999, You et al. 2001).
6.3. Safety criteria and thresholds
Since frictional demands and thresholds for safe friction have been defined differently in
different studies, the implications for discriminating safe conditions from potentially hazardous
conditions do vary owing to methodological reasons. However, the requirements do also vary
by task, subject and gait characteristics as well as by criterion for safe friction such as maximum
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peak or time-averaged utilized or required friction coefficient. Rarely have suggested frictional
demands been related to duration of friction force during stance, which is surprising, since any
contact-time-related variation of the utilized or required friction will be omitted, if a maximum
peak value is used as the only safety criterion. Consequently, this may lead to misinterpretation
of frictional demands that do vary as a function of contact time, particularly in the presence of
contaminants between shoes and floor surfaces (Strandberg 1985, Grönqvist et al. 2001).
Current criteria and thresholds for safe friction are still incomplete. Frictional demands and
their relation to availability of friction need to be better understood. Environmental consistency
(i.e. sufficiently high and steady friction conditions) might be one key factor for improved slip
and fall prevention. Perhaps much less can be done to improve human performance or to change
work tasks for reducing the frictional demands in the workplace.
7. Future directions of research
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For improving the validity and reliability of current risk assessment methods for slips and falls,
one must better understand how foot/floor interactions are involved during the events leading
to occupational injury and how slip and fall incidents should be simulated. Future directions
of research must deal with modelling of basic tribophysical, biomechanical and postural control
processes involved in slipping and falling. Slip/fall mechanisms need to be studied for a number
of usual and high-risk tasks from walking to manual materials handling, and for different age
groups. Events that trigger foot slides and subsequent events during which balance recovery
is feasible should be examined in particular. Hypothetical injury mechanisms of falls on the
same level and from a higher to a lower level should be tested. The role of slipperiness in the
onset and causation of unexpected loading on the musculoskeletal system (especially the low
back) is an area of research that has not received sufficient attention.
Objectives for future slips, trips and falls research are detailed below.
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1.
To document how anticipated postural controls develop—when does a person predict
a potential slipping or tripping condition based on a priori knowledge about
themselves and the environment, such as proprioceptive and kinesthetic cues, internal
situation models characterizing spatial relationships of objects, changes in lighting,
shadows, floor arrangement, etc? For example, psychophysically, what magnitude of
change in lighting intensity constitutes a slip-and-fall warning?
2.
To develop an understanding of how dual-task situations may impede anticipation
and adaptation controls—in particular, we want to explain how a person’s situation
model may influence judgements on temporal and spatial perturbations.
3.
To document how adaptive postural controls develop—what kind of sensory feedback
is used in the adaptation—visual, vestibular and proprioceptive feedback? (How do
people process information in fall situations?) What kind of feedback makes a person
decide to co-activate certain muscles to, for example, gain more leg joint stiffness and
maintain an upright torso (i.e. to fight a fall)? What makes a person decide to lower
his body for a better fall position to counteract the potential negative consequences
of an impending impact?
4.
To understand how postural adjustments associated with voluntary movements are
organized for various dual-task situations—how do harmonious motions develop to
support primary task performance and balance of gait simultaneously? (This has been
labelled physical mode-locking.)
5.
To test the hypothesis that mode-locking between the primary task and gait control
facilitates better anticipation and adaptation—if postural adjustments can be made
that satisfy both primary and secondary task performance naturally, are cognitive
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Grönqvist et al.
Page 20
resources off-loaded for improving sensory perception and situation model
development to better avoid or address fall events?
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6.
To explore mode-locking ability in a younger and an elderly population of healthy
subjects and its influence on locomotion under perturbations.
For further exploration of the aetiology of slip and fall accidents on icy surfaces, in particular,
and for providing the basis for their prevention, Abeysekera and Gao (2001) presented a
systems model, which focuses on an improved understanding of the roles of contributing factors
to slip and fall accidents.
The following systems factors were identified.
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1.
Footwear (sole) properties including sole material, hardness, roughness, worn/
unworn, tread (geometry) design, centre of gravity, anti-slip devices, wearability
(weight, height, flexibility, ease of walking, comfort).
2.
Road surface characteristics, covered with ice, snow, contaminants, anti-slip
materials, uneven, ascending/descending slope.
3.
Footwear (sole)/road surface interface—the tribological aspect and friction (static,
transitional and dynamic friction coefficients).
4.
Human gait biomechanics: muscle strength, postural control, musculoskeletal
function, postural reflex and sway, balance capability, acceleration, deceleration,
stride length, step length, heel velocity, vertical and horizontal forces.
5.
Human physiological and psychological aspects, i.e. the so-called intrinsic factors,
including declines in visual, vestibular, and proprioceptive systems, ageing,
perception of slipperiness, information processing, experience, training,
diabetes,drug and alcohol usage, unsafe behaviour (rush, reading while walking).
6.
Environment (extrinsic factors): temperature, humidity, snowfall, warm stream,
lighting condition, warning and road signs.
Acknowledgments
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The authors are grateful to the ‘opponent’ group members (Mark Redfern, Rakie Cham, Mikko Hirvonen, Håkan
Lanshammar, Mark Marpet and Christopher Powers) for their review of the preliminary manuscript presented at the
Measurement of Slipperiness symposium in Hopkinton, MA (27 – 28 July 2000), as well as to all the other reviewers
of the draft manuscripts during this process (Gordon Smith, Dal-Ho Son, Chien-Chi Chang and Vincent Ciriello).
David A. Winter is gratefully acknowledged for his kind permission to use the figure 2. The authors also wish to thank
Lennart Strandberg for valuable amendments to sections 2.3 and 4.3, and Patti Boelsen for her assistance in preparing
and proof-reading the manuscript. This manuscript was completed in part during Dr. Grönqvist’s tenure as a researcher
at the Liberty Mutual Research Center for Safety and Health.
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Figure 1.
Objective, combined and subjective human-centred approaches for the measurement of
slipperiness.
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Figure 2.
Strategies for co-ordinating legs and trunk to maintain body in equilibrium with respect to
gravity during standing (adapted from Winter 1995, figure 2.15).
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Figure 3.
Composite pattern of young and older individual’s heel velocity 117 ms before heel contact
(HV = heel velocity) and 117 ms after heel contact (SHV = sliding heel velocity) on an oily
vinyl floor surface; heel contact (HC) was defined as the time when the vertical ground reaction
force exceeded 10 N; the darker line expresses the average pattern of the heel velocities
(Lockhart 1997).
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Figure 4.
Gait phases in normal level walking with typical horizontal (FH) and vertical force (FV) ground
reaction components and their ratio, FH/FV, for one step (right foot). Critical from the slipping
point of view are the heel contact (peaks 3 and 4) and the toe-off (peaks 5 and 6) phases
(Grönqvist et al. 1989).
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Figure 5.
Composite view of the heel dynamics (kinetics and kinematics) during a typical slip-grip
response, including adjusted friction utilization (AFU) on an oily vinyl tile floor surface
(Lockhart et al. 2000b).
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Table 1
Shoe types
Parameters
Bovinide &
Studded
Bovinide &
Studded
Astral &
Bovinide &
Studded
Bovinide &
Studded
Grönqvist et al.
Viscosity of lubricant, average TFU and FFU, and falling frequency in psychophysical walking experiments on a continuously slippery triangular path
covered with a smooth PVC floor (adpated from Strandberg 1985).
Astral &
Bovinide &
Studded
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Viscosity N s m−2
0.001
0.01
0.01
0.2
0.2
Average TFU
0.300
0.205
0.203
0.093
0.078
Average FFU
0.331
0.250
0.248
0.099
0.087
Falling frequency
6
20
26
6
12
Average TFU=average time-based friction utilization during five laps of the triangular path;
Average FFU=average force plate-based friction utilization during one step in the 90° corner of the triangular path.
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