Sample entropy characteristics of movement for four foot types based on plantar centre of pressure during stance phase

BioMedical Engineering OnLine

Lei Wang²  Yongjin Zhou²  Qingsong Zhu²  Yanwei Guo¹  Kamen Ivanov¹  Guoru Zhao²  Zhanyong Mei¹ 

[1]Graduate University of Chinese Academy of Sciences, Beijing 10049, PR China

[2]Shenzhen Institutes of Advanced Technology, The Shenzhen Key Laboratory for Low-cost Healthcare, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen 518055, People’s Republic of China

关键词: Biomechanics;    Foot types;    Acceleration;    Velocity;    Foot pressure;    Gait;   

Others  :  797317
DOI  :  10.1186/1475-925X-12-101

 received in 2013-05-07, accepted in 2013-09-27,  发布年份 2013

【 摘 要 】

Background

Motion characteristics of CoP (Centre of Pressure, the point of application of the resultant ground reaction force acting on the plate) are useful for foot type characteristics detection. To date, only few studies have investigated the nonlinear characteristics of CoP velocity and acceleration during the stance phase. The aim of this study is to investigate whether CoP regularity is different among four foot types (normal foot, pes valgus, hallux valgus and pes cavus); this might be useful for classification and diagnosis of foot injuries and diseases. To meet this goal, sample entropy, a measure of time-series regularity, was used to quantify the CoP regularity of four foot types.

Methods

One hundred and sixty five subjects that had the same foot type bilaterally (48 subjects with healthy feet, 22 with pes valgus, 47 with hallux valgus, and 48 with pes cavus) were recruited for this study. A Footscan® system was used to collect CoP data when each subject walked at normal and steady speed. The velocity and acceleration in medial-lateral (ML) and anterior-posterior (AP) directions, and resultant velocity and acceleration were derived from CoP. The sample entropy is the negative natural logarithm of the conditional probability that a subseries of length m that matches pointwise within a tolerance r also matches at the next point. This was used to quantify variables of CoP velocity and acceleration of four foot types. The parameters r (the tolerance) and m (the matching length) for sample entropy calculation have been determined by an optimal method.

Results

It has been found that in order to analyze all CoP parameters of velocity and acceleration during the stance phase of walking gait, for each variable there is a different optimal r value. On the contrary, the value m=4 is optimal for all variables.

Sample entropies of both velocity and acceleration in AP direction were highly correlated with their corresponding resultant variables for r>0.91. The sample entropy of the velocity in AP direction was moderately correlated with the one of the acceleration in the same direction (r≥0.673), as well as with the resultant acceleration (r≥0.660). The sample entropy of resultant velocity was moderately correlated with the one of the acceleration in AP direction, as well as with the resultant acceleration (for the both r≥0.689). Moderate correlations were found between variables for the left foot and their corresponding variables for the right foot.

Sample entropies of AP velocity, resultant velocity, AP acceleration, and resultant acceleration of the right foot as well as AP velocity and resultant velocity of the left foot were, respectively, significantly different among the four foot types.

Conclusions

It can be concluded that the sample entropy of AP velocity (or the resultant velocity) of the left foot, ML velocity, resultant velocity, ML acceleration and resultant acceleration could serve for evaluation of foot types or selection of appropriate footwear.

【 授权许可】

   
2013 Mei et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Burzykowski T, Molenberghs G, Abeck D, Haneke E, Hay R, Katsambas A, Roseeuw D, van de Kerkhof P, van Aelst R, Marynissen G: High prevalence of foot diseases in Europe: results of the Achilles Project. Mycoses 2003, 46:496-505.
• [2]Simkin A, Leichter I, Giladi M, Stein M, Milgrom C: Combined effect of foot arch structure and an orthotic device on stress fractures. Foot Ankle Int 1989, 10(1):25-29.
• [3]Saro C, Andrén B, Felländer-Tsai L, Lindgren U, Arndt A: Plantar pressure distribution and pain after distal osteotomy for hallux valgus. Foot 2007, 17:84-93.
• [4]Lorei TJ, Kinast C, Klärner H, Rosenbaum D: Pedographic, clinical and functional outcome after scarf osteotomy. Clin Orthop Relat Res 2006, 451:161-166.
• [5]Future of podiatric medicine: an international perspective. 2013. https://podiatry.com/ezines/index.php?action=viewPublication&nopopout=true&confirmOff=true&SearchText=&id=543&keepThis=true&TB_iframe=true&height=700&width=768&full=true webcite
• [6]Hohmann E, Reaburn P, Imhoff A: Runner’s knowledge of their foot type: do they really know? Foot (Edinb) 2012, 22:205-210.
• [7]Salles AS, Gyi DE: An evaluation of personalised insoles developed using additive manufacturing. J Sports Sci 2013, 31:442-450.
• [8]Praet SF, Louwerens JW: The influence of shoe design on plantar pressure in Neuropathic Feet. Diabetes care 2003, 26:441-445.
• [9]Pataky TC, Mu T, Bosch K, Rosenbaum D, Goulermas JY: Gait recognition: highly unique dynamic plantar pressure patterns among 104 individuals. J R Soc Interface 2012, 9:790-800.
• [10]Giacomozzi C, Martelli F, Nagel A, Schmiegel A, Rosenbaum D: Cluster analysis to classify gait alterations in rheumatoid arthritis using peak pressure curves. Gait Posture 2009, 29:220-224.
• [11]Chuckpaiwong B, Nunley JA, Mall NA, Queen RM: The effect of foot type on in-shoe plantar pressure during walking and running. Gait Posture 2008, 28:405-411.
• [12]Ledoux WR, Hillstrom HJ: The distributed plantar vertical force of neutrally aligned and pes planus feet. Gait Posture 2002, 15:1-9.
• [13]Burns J, Crosbie J, Hunt A, Ouvrier R: The effect of pes cavus on foot pain and plantar pressure. Clin Biomech (Bristol, Avon) 2005, 20:877-882.
• [14]Mickle KJ, Munro BJ, Lord SR, Menz HB, Steele JR: Gait, balance and plantar pressures in older people with toe deformities. Gait Posture 2011, 34:347-351.
• [15]Wen J, Ding Q, Yu Z, Sun W, Wang Q, Wei K: Adaptive changes of foot pressure in hallux valgus patients. Gait Posture 2012, 36:344-349.
• [16]Hillstrom HJ, Song J, Kraszewski AP, Hafer JF, Mootanah R, Dufour AB, Chow BS, Deland JT: Foot type biomechanics part 1: Structure and function of the asymptomatic foot. Gait Posture 2013, 37(3):445-451.
• [17]De Cock A, Vanrenterghem J, Willems T, Witvrouw E, De Clercq D: The trajectory of the centre of pressure during barefoot running as a potential measure for foot function. Gait Posture 2008, 27:669-675.
• [18]Bertani A, Cappello A, Benedetti MG, Simoncini L, Catani F: Flat foot functional evaluation using pattern recognition of ground reaction data. Clinical Biomechanics 1999, 14:484-493.
• [19]Xu S, Zhou X, Sun YN: A novel gait analysis system based on adaptive neuro-fuzzy inference system. Expert Syst Appl 2010, 37:1265-1269.
• [20]De Cock A, Willems T, Witvrouw E, Vanrenterghem J, De Clercq D: A functional foot type classification with cluster analysis based on plantar pressure distribution during jogging. Gait Posture 2006, 23:339-347.
• [21]Cavanaugh JT, Guskiewicz KM, Stergiou N: A nonlinear dynamic approach for evaluating postural control, new directions for the management of sport-related cerebral concussion. Sports Med 2005, 35:935-950.
• [22]Richman JS, Joshua JR: Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol 2000, 278:2039-2048.
• [23]Ramdani S, Bouchara F, Lagarde J: Influence of noise on the sample entropy algorithm. Chaos 2009, 19(1):031231-031236.
• [24]Ramdani S, Seigle B, Lagarde J, Bouchara F, Bernard PL: On the use of sample entropy to analyze human postural sway data. Med Eng Phys 2009, 31:1023-1031.
• [25]Roerdink M, De Haart M, Daffertshofer A, Donker SF, Geurts AC, Beek PJ: Dynamical structure of center-of-pressure trajectories in patients recovering from stroke. Exp Brain Res 2006, 174:256-269.
• [26]Miller CA, Verstraete MC: A mechanical energy analysis of gait initiation. Gait Posture 1999, 9:158-166.
• [27]Lindemann U, Najafi B, Zijlstra W, Hauer K, Muche R, Becker C, Aminian K: Distance to achieve steady state walking speed in frail elderly persons. Gait Posture 2008, 27:91-96.
• [28]Pham TD: GeoEntropy: A measure of complexity and similarity. Pattern Recogn 2010, 43:887-896.
• [29]Yentes JM, Hunt N, Schmid KK, Kaipust JP, McGrath D, Stergiou N: The appropriate use of approximate entropy and sample entropy with short data sets. Ann Biomed Eng 2013, 41:349-365.
• [30]Aboy M, Cuesta-Frau D, Austin D, Mico-Tormos P: Characterization of Sample Entropy in the Context of Biomedical Signal Analysis. Lyon, France: presented at the IEEE EMBS; 2007.
• [31]Ramdani S, Seigle B, Varoqui D, Bouchara F, Blain H, Bernard PL: Characterizing the dynamics of postural sway in humans using smoothness and regularity measures. Ann Biomed Eng 2011, 39:161-171.
• [32]Lake DE, Richman JS, Griffin MP, Moorman JR: Sample entropy analysis of neonatal heart rate variability. Am J Physiol Regul Integr Comp Physiol 2002, 283:R789-R797.
• [33]Pearson’s Correlation Coefficient. http://www.statisticssolutions.com/academic-solutions/resources/directory-of-statistical-analyses/pearsons-correlation-coefficient/ webcite
• [34]Hunt AE, Smith RM: Mechanics and control of the flat versus normal foot during the stance phase of walking. Clin Biomech (Bristol, Avon) 2004, 19:391-397.
• [35]Powell DW, Long B, Milner CE, Zhang S: Frontal plane multi-segment foot kinematics in high- and low-arched females during dynamic loading tasks. Hum Mov Sci 2011, 30:105-114.
• [36]Ledoux WR, Willianm HJ: Acceleration of the calcaneus at heel strike in neutrally aligned and pes planus feet. Clinical Biomechanics 2001, 16:608-613.
• [37]Sadeghi H, Allard P, Prince F, Labelle H: Symmetry and limb dominance in able-bodied gait: a review. Gait Posture 2000, 12:34-45.