Coefficient of friction, walking speed and cadence on ...

International Journal of Occupational Safety and Ergonomics

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Coefficient of friction, walking speed and cadence on slippery and dry surfaces: shoes with different groove depths Mansour Ziaei, Hamid Reza Mokhtarinia, Farhad Tabatabai Ghomshe & Maryam Maghsoudipour To cite this article: Mansour Ziaei, Hamid Reza Mokhtarinia, Farhad Tabatabai Ghomshe & Maryam Maghsoudipour (2017): Coefficient of friction, walking speed and cadence on slippery and dry surfaces: shoes with different groove depths, International Journal of Occupational Safety and Ergonomics, DOI: 10.1080/10803548.2017.1398922 To link to this article: http://dx.doi.org/10.1080/10803548.2017.1398922

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Date: 15 November 2017, At: 22:40

Publisher: Taylor & Francis & Central Institute for Labour Protection – National Research Institute (CIOP-PIB) Journal: International Journal of Occupational Safety and Ergnomics

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DOI: 10.1080/10803548.2017.1398922

Coefficient of friction, walking speed and cadence on slippery and dry surfaces: shoes with different groove depths

Mansour Ziaei1, Hamid Reza Mokhtarinia2, Farhad Tabatabai Ghomshe2,3, Maryam Maghsoudipour2,* 1. Occupational Health Department, Boushehr University of Medical Sciences, Bushehr, Iran. 2. Ergonomics Department, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran 3. Pediatric Neuro-rehabilitation Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran *Corresponding author: Maryam Maghsoudipour Address: Department of Ergonomics, University of Social Welfare and Rehabilitation Sciences, koodakyar Ave., daneshjoo Blvd., Evin, Tehran, Iran. Postal code: 1985713834. E-mail: [email protected]

Short title: “Shoes with different groove depths”

Coefficient of friction, walking speed and cadence on slippery and dry surfaces: shoes with different groove depths

Mansour Ziaei1, Hamid Reza Mokhtarinia2, Farhad Tabatabai Ghomshe2,3, Maryam Maghsoudipour2,*


1. Occupational Health Department, Boushehr University of Medical Sciences, Bushehr, Iran. 2. Ergonomics Department, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran

3. Pediatric Neuro-rehabilitation Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran

*Corresponding author: Maryam Maghsoudipour Address: Department of Ergonomics, University of Social Welfare and Rehabilitation Sciences, koodakyar Ave., daneshjoo Blvd., Evin, Tehran, Iran. Postal code: 1985713834. E-mail: [email protected]

Short title: “Shoes with different groove depths”

There is no financial interest regarding this study.


Abstract Objective: The aim of the present study was to determine the coefficient of friction (COF), walking speed (WS), and cadence while walking on slippery and dry surfaces using shoes with different sole groove depths to predict how much it is likely to fall. Background: Design of shoe sole groove is crucial to prevent slipping during walking. Methods: 22 healthy young men (mean age: 24.5 and body mass index: 22.5) volunteered for this semiexperimental study. Six different conditions of the test (combination of three shoes and two surfaces) were defined and the condition was repeated 3 times. Totally 396 trials (22 subjects × 3 groove depths × 2 surfaces × 3 times) were obtained for data analysis. COF was recorded by force platform at 1000 Hz and walking parameters were recorded using 3D motion analysis system with six infrared cameras at 200 Hz. Results: The highest value of COF was obtained from deepest groove depth (5.0 mm) on both dry and slippery surfaces. The coefficient of friction on slippery surfaces was significantly lower in comparison with dry surfaces. Walking speed and cadence were not significantly different on dry and slippery surfaces. Conclusion: This study suggests that the deeper groove is better to prevent slipping because the COF increases by increasing the shoe sole groove depth. Walking speed did not change on dry and slippery surfaces.

Keywords: shoes, coefficient of friction, walking speed, cadence, shoes sole groove depth


1. Introduction The shoe is the first and the only point of contact between foot and ground during walking. Any changes in the shoe have clearly affected the gait parameters. The various features of the shoe (material, sole hardness, heel height, shoe sole tread shape, and size) have direct effects on balance control and body stability. Fall accidents caused by slipping represent a high proportion of all accidents in the industry as well as in the private sphere [1]. The risk of slipping is related to the materials of footwear and floor, floor condition and geometric design of the sole [2]. When the shear forces applied to the floor surface exceed the utilized foot-floor interface friction, a slip occurs [3, 4]. On the other hand, when the available friction at foot-floor interface exceeds the utilized friction, no slip will happen. Slips have been found as one of the most common causes of occupational accidents and are significant causes of falls [5]. Adequate friction at the foot-floor interface is necessary to prevent a slip. [6] The foot-floor coefficient of friction (COF) is an important parameter related to slipping. There is a complex interaction among the shoe/floor/contaminant reflected on available friction [7, 8]. Prevention of a potentially injurious fall depends on the ability of a person to make a recovery response and also is affected by the COF of the foot-floor interface. [9]

The mechanisms and adaptation to low friction have been a focus of research for many investigators, to show how to prevent potential falls and injuries [10]. Tsai and Powers suggested that it might be beneficial to discover footwear characteristics that are able to limit slip distance or improve the ability of a person to make an effective recovery response [9]. Footwear


contributes to the available friction of foot-floor interface and affects the walking patterns of participants [6, 11]. The design of a slip-resistant shoe can prevent or reduce the slipping in the different floors. Shoe sole tread groove is one of the important factors on friction coefficient between the shoe and surface during walking. Li et al suggested that tread groove should be deep enough to accommodate the liquids at the foot-floor interface. [2] Walking speed has been proposed to be related to utilized COF (COF U). Also, walking speed had a statistically significant effect on the available coefficient of friction (ACOF) [12]. However, some studies have shown that faster walking speed leads to increased peak COF U [13, 14], but another study reported that walking speed is not related to COF U [15]. Differences in walking speed can result in changes in the minimum required coefficient of friction necessary to maintain foot contact stability [10, 16]. To minimize energy cost at different walking velocities, individuals normally adopt a gait that varies in both step length and step frequency [17]. Walking speed can be increased by increasing of stride length, cadence, and or a combination of both, but the former had a greater effect than the latter [18]. Some researchers suggest that individuals who increase stride length to achieve a faster walking velocity may experience greater increases in COFU compared to those who increase cadence to achieve a faster walking speed. [14, 18] Human factors causing falls and their complex interaction with environmental factors can be investigated by biomechanical analysis; e.g. analysis of walking [19, 20]. Friction measurements on level surfaces, both in the laboratory and in work environments have been reported in

previous studies [21-23]. As a matter of fact, COF may be depended on walking speed; so, walking speed and related factors such as stride length and cadence should be measured too. To achieve this goal, it seems necessary to analyze walking parameters of people who are wearing standard shoes. The aim of this study was to measure the effect of different groove depths on the


coefficient of friction, walking speed and cadence of 22 men during walking on slippery and dry surfaces in order to know more about the possibility of the fall in different conditions. Indeed, what depth of shoe sole groove is better to prevent from slip? 2. Method 2.1.Participants Twenty-two healthy male students from University of Social Welfare and Rehabilitation Sciences (Iran) volunteered for this study. Mean (SD) age of them was 24.5 (3.43) years and body mass index (BMI) was 22.5 (1.27). Subjects were selected randomly and the competency of enrolling to this survey was evaluated by biomechanics specialist and physiotherapist. Exclusion criteria were: having a history of musculoskeletal disorders, impairment of lower limbs, using foot orthotics, lower extremity surgery, flat foot, and cross feet. The subjects had put on exercise clothes and stretch pants. They had socks during the test. It could prevent sliding feet in shoes. Written informed consents were obtained from the subjects that were approved by the Ethics Committee of the University of Social Welfare and Rehabilitation Sciences. 2.2 Materials and Equipment The experiment shoes were Oxford shoes with three different groove depths (1.0, 2.5 and 5.0 mm), but the groove width was the same and it was 3.0 mm. Also, heel height of all shoes was 3.0 cm. In other words, all shoes were exactly similar except that groove depths were different.

The reference shoe sole was made of the same polymer as the rest of the shoes but without tread pattern. The upper compartments and sole of the shoes were made from leather and polyurethane respectively (Fig. 1). It is necessary to mention that the shoes were exactly fitted to the subjects' feet and were approved by the examinee.


Kinematic data were recorded at 200 Hz using three-dimensional motion analysis system (Vicon460, Oxford, UK). Six infrared cameras were located around the walkway. The Infrared reflective markers (diameter: 14.0 mm) were attached to the skin overlying the following landmarks: left and right lateral ankle, toe and heel. The coefficient of friction (COF) was recorded at 1000 Hz by two force platforms (Kistler 9286AB, Zurich, Switzerland). Length of test walkway was three meters. Measurement values were recorded with Bioware software version 4.0.1.2. 2.3.Procedure This study was a semi-experimental study with a repeated-measures design. To start the experiment, the examinee wore the stretch pants and the standard Oxford shoes. Then reflective markers were attached to the subject and he was asked to walk with free-speed walking on the walkway during the test. After this preparation phase, the examinee walked along a three-meter walkway in six different subsets and data were collected. Each subset of trial with different conditions was repeated three times. A trial was considered successful if the subject’s right foot landed on the force plate. In order to prevent fatigue and to have the same condition in all trials, the subjects took five-minute intervals between trials. Test conditions included shoes with three different groove depths (1.0, 2.5 and 5.0 mm) and two different surfaces (dry and slippery). We used a certain amount of soapy water for making the slippery surface. In dry condition, we did not use soapy water and it was just dry, or we dried the surface completely. All tests were

performed in the Ergonomics Laboratory of the University of Social Welfare and Rehabilitation Sciences. Table 1 shows the abbreviations used in this study. 2.4.Measurements The coefficient of friction, walking speed and cadence were measured using motion analysis


system and force plate sets. 2.4.1.The coefficient of friction: the ratio of horizontal force (FZ) to vertical force (FG) while walking, calculated by Bioware software. [1, 14] 2.4.2.Walking speed (m/s): the ratio of stride length (SL) or distance between heel markers during two alternate heel strikes to walking cycle time or stride duration (SD), (Equation 1). [24, 25] Equation 1: walking speed = stride length ÷ stride duration 2.4.3.Cadence: the number of strides (two steps) per minute during walking. [25] 2.5.Data analysis Generally, 396 trials (22 subjects × 3 groove depths × 2 surfaces × 3 trials) were obtained. Analysis of variance (ANOVA) and Friedman were performed to assess the effects of groove depth and surface condition on the COF, SL, SD, and cadence. Where: COF=coefficient of friction, WS=walking speed, SL=stride length, and SD= stride duration. An α level of 0.05 was accepted as significant for all tests in this study. 3. Results Table 2 shows the mean and standard deviation of coefficient of friction (COF), walking speed (WS), stride length (SL), stride duration (SD) and cadence in 6 different conditions of the test.

3.1.Coefficient of friction Table 3 shows ANOVA (Tukey's post hoc) results of coefficient of friction on slippery and dry surfaces (p=0.014). Results depict that COF on dry surface was more than slippery surface. In addition, COF between the shoe and the contact surface would increase by increasing the groove


depth of shoe sole on both dry and slippery floors (see fig. 2). The highest COF was related to the deepest tread groove (5.0 mm) on the dry surface. 3.2.Walking velocity and cadence Table 4 shows Friedman analysis of walking speed (WS), stride length (SL) and stride duration (SD), and cadence on both slippery and dry surfaces. Results depict that there were no statistical difference among (WS), (SD), and cadence using different groove depths on dry and slippery surfaces (p≥0.05). It is necessary to mention that the highest SL was related to deepest tread groove (5.0 mm) on the dry surface. 4. Discussion 4.1.Coefficient of friction In our study COF (measured in the mid-stance phase of gait) was increased by increasing groove depth of the shoe sole, so that the highest value of COF was correlated to the deepest groove depth (5.0 mm) on both dry and slippery surfaces. In a previous paper published by Ziaei et all [26], the COF was measured at heel strike and toe-off phases of gait, in that paper COF again, was increased by increasing shoe sole tread groove depth. Another study showed that higher friction values were recorded for footwear pads with deeper tread grooves on wet and water-detergent-contaminated floors [2]. Shoe sole tread groove is recognized as one of the most important factors affecting slip prevention during walking [27] and it is crucial for safe walking on liquid-contaminated floors. [28]

In this study, the coefficient of friction on the dry floor surface was significantly higher than the slippery floor surface. The foot-floor contact area is one of the most important predictors of fall risks so that higher fall risk is associated with lower contact area [29]. When stepping on a wet or lubricated floor, the liquid between floor and sole separates two contact surfaces and


reduces the friction between them [2]. The liquid between the shoe and the ground acts as a barrier that decreases the contact area leading to instability that results in slipping and probably fall. While walking on the slippery surface, deeper groove of shoe sole is more efficient to extract the liquid under the shoe and increases the contact area. Thus, COF is increased between the shoe and the surface, which improves stability while walking. It might be assumed that by designing a completely smooth and groove-less shoe sole, the foot-floor contact area and COF would be increased, but indeed, this design could lead to slipping more, because of a lack of space between shoes and floor to extract the liquid between them. Therefore, COF will be increased by increasing the shoe sole tread groove depth and consequently slipping and fall on the slippery surfaces can be prevented. In this study, among three different groove depths chosen for trials (1.0, 2.5 and 5.0 mm), it appears that deepest groove (5.0 mm) led to more efficient COF. 4.2.Walking speed The present study showed that WS, SD, and cadence are not significantly increased or decreased by changing groove depths of shoe sole on both dry and slippery surfaces. Although SL was significantly higher using deepest tread groove (5.0 mm) on the dry surface compared to other conditions, although it seems that shoe sole tread groove depth is not an important factor on WS and its related parameters.

One study showed that while walking on an uneven surface, subjects did not alter their speed; however, they walked with a significantly slower cadence and longer step length, compared to the smooth surface [30]. The relationship between the amplitude and frequency of the rhythmic leg movements has remained stable irrespective of changes in walking speed [31]. In other


studies, when walking on slippery surfaces versus dry surfaces, the subjects showed reductions in walking speed [24], step length [24, 32-34] and cycle duration [34]. These strategies are probably intended to decrease the risk of initiating a slip by lowering the required coefficient of friction [32, 35], as well as minimizing the potential slip severity by reducing slipping distance and sliding velocity. [19] There are at least two major mechanisms of adjustment during walking on slippery surfaces. One of them is a step-by-step modification or optimization of normal gait that might involve various sensory mechanisms. The other one is adoption of an appropriate intrinsic strategy. Individuals may adopt specific strategies for walking on the slippery surfaces in the form of special gaits or modes of locomotion. [36, 37] In this study, although cadence and WS were not statistically different between dry and slippery surfaces, however as a possible locomotor strategy, the subjects decreased the cadence and WS by perception of the possibility of slipping and falling on the slippery surface. 4.3.Correlation between COF and WS Differences in walking speed can lead to changes of required coefficient of friction that is necessary to maintain foot contact stability [10, 16]. However, some studies showed that utilized COF (COFU) increases with faster walking speeds [14, 38], but another study demonstrated that walking speed is not associated with COFU [15]. Some researchers reported that those who

increase stride length to achieve a faster walking speed may experience greater increases in COFU compared to individuals who increase cadence to attain a faster walking speed. [14, 18] In this study, although the subjects did not increase WS using shoes with deepest tread groove (5.0 mm) on the dry surface, they increased the SL due to the existence of sufficient COF, as


well as higher stability gait pattern. So, the COF and SL had the highest value using the deepest tread groove on the dry surface. On the other hand, subjects decreased the SL during walking on the slippery surface due to insufficient friction coefficient, as well as fear of slipping and falling. The limitations of the present study should be noted; the sample size was small, the length of force plate was short, and this research was only performed on men. This may result in the insufficient statistical power to detect the differences between test conditions. 5. Conclusion One of the major findings of this study was that the cadence and WS did not change on the dry surface compared to the slippery surface. The COF and SL had the highest value using the deepest tread groove on dry surface. Tread groove depth significantly affected the COF on dry and slippery surfaces, so that increasing shoe sole tread groove depth would increase COF. This study suggests that the deeper groove is better for slip prevention and more stable walking. 6. Acknowledgments

This project was performed in Ergonomics Department Lab of University of Social Welfare and Rehabilitation Sciences, and authors thank Mrs. Seyed Hoda Nabavi for technical help.


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31. Sekiya N, Nagasaki H. Reproducibility of the walking patterns of normal young adults: test-retest reliability of the walk ratio(step-length/step-rate). Gait & posture. 1998;7(3):225-7. 32. Cham R, Redfern MS. Changes in gait when anticipating slippery floors. Gait & posture. 2002;15(2):159-71. 33. Lockhart TE, Spaulding JM, Park SH. Age-related slip avoidance strategy while walking over a known slippery floor surface. Gait & posture. 2007;26(1):142-9. 34. Cappellini G, Ivanenko YP, Dominici N, Poppele RE, Lacquaniti F. Motor patterns during walking on a slippery walkway. Journal of neurophysiology. 2010;103(2):746-60. 35. Hanson JP, Redfern MS, Mazumdar M. Predicting slips and falls considering required and available friction. Ergonomics. 1999;42(12):1619-33. 36. Golubitsky M, Stewart I, Buono PL, Collins JJ. Symmetry in locomotor central pattern generators and animal gaits. Nature. 1999;401(6754):693-5. 37. Ivanenko YP, Cappellini G, Poppele RE, Lacquaniti F. Spatiotemporal organization of alphamotoneuron activity in the human spinal cord during different gaits and gait transitions. The European journal of neuroscience. 2008;27(12):3351-68. 38. Burnfield J, Powers C. Influence of age and gender on utilized coefficient of friction during walking at different speeds. Metrology of pedestrian locomotion and slip resistance: ASTM International; 2003. p. 3-16.


Fig. 1: Standard Oxford shoes with three different groove depths (a) 1.0 mm, (b) 2.5 mm and (c) 5.0 mm; (d) upper section of shoes


Fig. 2: Coefficient of friction in six different conditions of test; shoes with groove depths 1.0, 2.5 and 5.0 mm on both slip and dry floors.


(a)

(b)

(c)

(d)

Fig. 1: Standard Oxford shoes with three different groove depths (a) 1.0mm, (b) 2.5mm and (c) 5.0mm; (d) upper section of shoes

Table 1: The abbreviations of test conditions that used in this study


Abbreviation 1.0dry 1.0slip 2.5dry 2.5slip 5.0dry 5.0slip

Independent variable Groove depth 1.0 mm on the dry surface Groove depth 1.0 mm on the slippery surface Groove depth 2.5 mm on the dry surface Groove depth 2.5 mm on the slippery surface Groove depth 5.0 mm on the dry surface Groove depth 5.0 mm on the slippery surface

Table 2: Mean and standard deviation M (SD) of COF, WS (m/s), cadence (stride/min), SL (m), SD (s) in six different condition of test; (N=22; trials=396)


Condition

M (SD) COF

WS

Cadence

SL

SD

1.0dry

0.202 (0.02)

1.03 (0.30)

51.37 (9.95)

1.20 (0.24)

1.20 (0.16)

1.0slip

0.152 (0.03)

0.98 (0.26)

49.28 (9.80)

1.19 (0.24)

1.25 (0.19)

2.5dry

0.209 (0.02)

1.05 (0.33)

52.94 (15.36)

1.19 (0.23)

1.19 (0.21)

2.5slip

0.162 (0.02)

1.01 (0.27)

50.63 (7.19)

1.19 (0.23)

1.21 (0.14)

5.0dry

0.217 (0.01)

1.03 (0.29)

50.07 (8.91)

1.23 (0.28)

1.22 (0.15)

5.0slip

0.173 (0.02)

0.96 (0.23)

49.22 (7.65)

1.17 (0.24)

1.24 (0.17)

Note: COF = Coefficient of Friction; WS = Walking Speed; SL = Stride Length; SD = Stride

Duration.

Table 3: ANOVA (Tukey's post hoc) for coefficient of friction in six different condition of test; (N=22; trials=396)

Coefficient of Friction (COF) dry vs. dry

dry vs. slip


Condition 1.0dry 1.0slip 2.5dry 2.5slip 5.0dry 5.0slip

slip vs. slip

M

p-value

Condition

M

p-value

Condition

M

p-value

0.202 0.152 0.209 0.162 0.217 0.173

0.001

1.0dry 2.5dry 1.0dry

0.202 0.209 0.202

0.090

1.0slip 2.5slip 1.0slip

0.152 0.162 0.152

0.001

5.0dry 2.5dry 5.0dry

0.217 0.209 0.217

5.0slip 2.5slip 5.0slip

0.173 0.162 0.173

0.004 0.006

*

: significantly different between condition (p < 0.05). : significantly different between condition (p < 0.01).

**

Note: ANOVA = analysis of variance

0.012 0.027

0.001 0.001

Table 4. Friedman analysis of WS (m/s), SL (m), SD (s), and cadence (stride/min) in six different conditions of test


condition 1.0dry 1.0slip 2.5dry 2.5slip 5.0dry 5.0slip

WS M 1.03 0.98 1.05 1.01 1.03 0.96

p-value 0.153

SL M 1.20 1.19 1.19 1.19 1.23 1.17

p-value 0.028*

SD M 1.20 1.25 1.19 1.21 1.22 1.24

p-value 0.109

Cadence M 51.37 49.28 52.94 50.63 50.07 49.22

p-value 0.109

*

: significantly different between condition (p < 0.05)

Note: COF = Coefficient of Friction; WS = Walking Speed; SL = Stride Length; SD = Stride Duration.






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