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Plantar pressure is force measured over an infinitesimally discrete area on the plantar surface of the foot. When the foot makes contact with the ground a force produced by body weight is exerted onto the ground. To prevent you from sinking through the ground, the ground must apply a force equal and opposite to body weight on to the foot, called the ground reaction force. By considering this force over an infinitesimally small area we are able to substitute force for pressure and consider how the external load is distributed over the various plantar structures of the foot. Orthopaedic surgeons [22], prosthetists [146], orthotists [133], footwear manufacturers [38] and biomechanics researchers [147] have all used plantar pressure measurement to help understand the foot and the mechanisms that affect it. This knowledge is required to improve the health of the foot and the performance of the products the foot interacts with (or is replaced by in the case of prosthetics).

There are two main components of loading experienced by the plantar surface of the foot: vertical pressure and shear. It has been confirmed that shear distribution may explain the variation between vertical peak pressure location and the location on ulceration [148]. Unfortunately, the technology available to measure shear pressure is limited and normally consist of a platform [148] and thus cannot be used to measure in shoe pressures. Instruments that are designed to be used inside footwear are currently only able to measure vertical forces and thus vertical pressures, and at discrete locations using 10 X 10 X

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2.7 mm sensors [149]. The issues with using such systems are that the location at which data is collected needs to be chosen before data collection with no guarantee that the correct location will be chosen. Even if the correct location is chosen the device may migrate during testing. Furthermore, the very act of including the sensors within the shoe will change the relationship between foot and shoe and thus the biomechanical phenomena being investigated.

There are many ways to investigate the pressure on the plantar surface of the foot. Early and crude approaches to barefoot pressure measurement include ink impressions produced using products such as a Harris mat [150] but it is now routine to use mats comprising matrices of force sensors, such as the Emed platform (Novel Gmbh, Munich, Germany) [151]. However, investigations on the effects of shoe features using devices external to the shoe, such as pressure mats, are of limited value. This is because pressure mats do not provide information on the pressure at the foot-shoe interface. They are single foot strike systems and therefore inhibit the investigator from collecting continuous steps, thus increasing the time required to collect sufficient steps to produce valid plantar pressure data, formulated from numerous steps, for each experimental condition [139].

There are many techniques for measuring the pressure inside footwear. In 1947, Schwartz and Heath [152, 153] used small capacitive disc transducers to investigate plantar loading. These where attached to six locations on the plantar surface of the foot: at the great toe, first, third and fifth metatarsals, and both the medial and lateral aspects of the heel. Following this, a number of groups investigated a range of techniques to record pressure on the plantar surface of the foot [154-158]. A full description and appraisal of the

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types of pressure measurement devices available has previously been provided by Lord 1988 [159] and more recently this has been updated Urry 1999 [160]. There are many devices that can be used to measure the pressure inside the shoe, from microcapsules full of dye to piezoelectric methods, and an appraisal of these approaches have also been reported in detail [142]. Using discrete sensors at specific anatomical sites keeps the number of sensors required low, but requires accurate locating of the sensors before testing. It assumes there is a strict hypothesis supporting such limited measurement in the surrounding areas of the foot. Also, the stiffness and thickness of the sensors will often be different to the rest of the foot bed and therefore the sensors will act as a 'foreign body' in the shoe, changing the mechanical conditions which are being measured [159]. Finally, issues related to incorrect placement of sensors can lead to poor data, often due to sensors migrating during the experiment [142].

To address these difficulties, technical advances focused on the development of matrices of sensors that cover the entire plantar surface, thereby limiting the amount of “dead space” in between sensors where loads applied would remain unmeasured. This led to the development of sensors based on two 50 µm copper foils placed either side of a sponge rubber sheet (~2mm) that covered the entire plantar surface [161]. Of the wide range of insole pressure devices available, two devices have emerged as the most popular: f-scan (Software v. 3.4, Tekscan. Boston, MA) and Pedar (Novel Gmbh, Munich, Germany). Pedar was developed based on the work of Nicol & Hennig [161] and is often reported as the better of the two devices because it has greater accuracy and a lower variability (60%, 20% and 22% lower variability at the heel, central metatarsal heads, and great toe respectively) [162], as well as its ability to verify the measurement of each sensor [147]. It

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has been shown that the Pedar system has the best accuracy and precision assuming: (1) it has been recently calibrated according to the manufactures guidelines, (2) it is operating between 50-500kPa and (3) when the data is collected within a few seconds of the pressure being applied [163] i.e. standing for long periods whilst using the insole will generate sensor drift. When these requirements are adhered to the per cent errors range is -0.6 to 2.7, which is dependent on the specific pressure loads, as well as the magnitude, found by taking the lower bound from the upper bound, of the 95% tolerance intervals between 13.5 and 18.7% [163].

A matrix of sensors covering the plantar surface of the foot produces a lot of data (99 sensors per foot, each recording at 50Hz). This must be reduced into useful subsets and specific variables extracted, only then can hypotheses be tested. A common approach is to divide the pressure measurement insole data into primary level anatomical regions (masks), which can be especially useful if the research is seeking to identify changes in pressure at specific sites (e.g. under metatarsal heads). However, this "masking" approach introduces artificial boundaries into the data that whilst anatomically relevant may not exist in functional terms.

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Figure 32: comparison of regional peak pressure and region of interest taken from Pataky et al 2008 [164]

Masking also assumes that you know the location where changes in pressure will occur. It has been shown that masking the foot by anatomical region, e.g. rearfoot, midfoot, forefoot, leads to potential loss of useful information in the pressure data [165]. The two types of data analysis ( pixel and regional) can be seen in Figure 32. Using regional analysis may mask differences between individuals or experimental cases that exist at a pixel level but not at a foot region level. This occurs because data is averaged across the region (e.g. all of the forefoot), or represents just one pixel in that region (e.g. peak pressure) and thus ignores the data in all the other pixels. In the only published case addressing this concern, statistical parametric mapping, which uses individual pixel data, found positive correlation

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between peak pressure and walking speed in the midfoot and medial proximal forefoot for traditional ten region subsampling, but negative correlation in the midfoot and proximal forefoot when using pixel data [164]. So large are these effects that it has been shown that in the regional analysis, the location of the peak pressure defined by the centre of a region, will differ in location of the when using pixel data in 80% of cases. Furthermore, if the location of the peak pressure, from pixel data, falls on the location of a regional boundary, of regional data, with a probability of 65%, which means the regional mask technique cannot have reported the peak pressure location correctly [166]. These findings have led researchers to conclude that regional masks data is biased because its regionalisation scheme delineate the observed data according to the anatomy instead of the its geometric properties [166].

To overcome this problem statistical parametric mapping has been applied to plantar pressure data [164]. This produces a continuous statistical map based on individual sensor data rather than predetermined groups of sensors. These maps represent the original foot pressure data in image form and direct comparison of maps between experimental conditions can identify statistically meaningful differences (i.e. p<0.05) in pressure distributions. This has the particular advantage of making no assumptions about where under the foot the differences in pressures might occur, which might be valuable since the foot is a complex deformable structure and its interaction with the shoe is complex and perhaps highly person specific.

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Regardless of analysis approach, comparisons assume prior knowledge of the key variable to extract from the pressure data. A wide range of variables have been derived from plantar pressure data: peak pressure (e.g. at a specific sensor, or in a specific mask, at any point during the gait cycle) [167], average pressure (e.g. at a specific sensor, or in a specific mask, over the entire gait cycle) [168], pressure time integral (e.g. at a specific sensor, or in a specific mask) [91], force [169], contact area [168], force time integral [91], mean area [170], and contact time [167]. Of these the most commonly reported are the peak pressure and the pressure time integral. Peak pressure is popular since it is assumed that high loads are damaging to tissue and might cause pain or more significant destruction, leading to ulceration [16, 171]. This is of interest in this thesis because in following studies we will investigate how shoes affect comfort, and comfort is often regarded as a point on a much wider pleasure-pain scale. The peak pressure time integral recognises that instantaneous application of high pressure might not always be a critical factor, whereas application of lower pressures but over longer time periods might also cause tissue damage. Static, barefoot standing has produced average plantar pressure values of 70kPa and peak plantar pressure values of 140-175kPa [172] with peaks of over 300kPa during walking [173] which is far in excess of the required pressure shown to generate skin and nerve damage. To exceed capillary pressure and thus put the tissue at risk of ischemia, pressures averaging only 4 – 4.7kPa are required [174, 175], and that which has been shown to effect nerve impairment in rabbits [176].

A key difficulty in choosing a suitable variable is that the underlying relationship between clinical conditions and symptoms, and plantar pressure variables are not well

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understood. The assumed association between high loads or prolonged application of loads and tissue damage seems a reasonable starting point. In addition, some variables are not independent of each other. Prior work has now demonstrated that peak pressures and the pressure time integral are closely correlated and reporting both is often redundant [93]. It has also been reported that the plantar pressure parameters; peak, mean and impulse can be compared both across studies and parameters [177]. As a result it has been suggested that using a smaller set of parameters is more effective at capturing the biomechanical behaviour being observed [177].

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