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Methodology for Calculating Shock Loads on the Human Foot

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Methodology for Calculating Shock Loads on the Human Foot

Volume 6, Issue 2, Page No 58–64, 2021

Author’s Name: Valentyn Tsapenko* 1Email, Mykola Tereschenko 1, Vadim Shevchenko 1, Ruslan Ivanenko 2
1 Faculty of Instrumentation Engineering, National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, 03056, Ukraine
2 The Ukrainian Scientific and Forensic Expertise of the Security Service of Ukraine, Kyiv, 03113, Ukraine
*whom correspondence should be addressed. E-mail: capenko.valik@ukr.net

Adv. Sci. Technol. Eng. Syst. J. 6(2), 58–64 (2021); crossref symbol DOI: 10.25046/aj060208

Keywords: Foot, Musculoskeletal System, Step Cycle, Locomotion, Biomechanical Parameters, Support, Elastic Characteristics, Coefficients of Capacity, Shock Load

Received: 24 December 2020, Accepted: 14 February 2021, Published Online: 10 March 2021
(This article belongs to the SP10 (Special Issue on Multidisciplinary Sciences and Engineering 2020-21) & Section Biomedical Engineering (EBI))
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Abstract

The leading place among diseases of the musculoskeletal system is occupied by various feet deformations. Clinical movement analysis and posturological examination are required to objectively assess the distribution for load caused by the weight of human body on the feet and its locomotion effect. In normal conditions, the foot is exposed to elastic deformations. When analyzing the foot loads, it`s necessary to consider shock loads as one of dynamic load types. The foot is the first to perceive the shock impulse by support reaction, and the further nature for interaction with the environment directly depends on its functional capabilities. However, the foot supporting properties haven`t been fully researched. The purpose for this research is to increase the accuracy of estimating the human foot biomechanical parameters, by assessing the dynamic impact, namely short-term shock loads by step cycle relevant phases. This goal is solved by developing a method of static-dynamic load analysis, which allows to estimate dynamic and shock loads on foot and is reduced to determining the capacity coefficients, dynamic and shock loads. In the course of studies, conducted in this research, it was found that the maximum contact per unit time has front section (repulsion phase), then – the rear section (landing phase) and the smallest – the foot middle section (rolling phase), the greater speed and length step – so the greater shock loads coefficient, and their peak falls on the front and rear sections. The practical significance of the obtained results is to improve the existing methods of researching biomechanical parameters by comprehensively assessing by standing and gait features, foot step cycle and support properties.

References (12)

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  3. Radwan Qasrawi, Stephanny VicunaPolo, Diala Abu Al-Halawa, Sameh Hallaq, Ziad Abdeen, "Predicting School Children Academic Performance Using Machine Learning Techniques", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 5, pp. 08–15, 2021. doi: 10.25046/aj060502
  4. Saichon Sinsomboonthong, "Efficiency Comparison in Prediction of Normalization with Data Mining Classification", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 4, pp. 130–137, 2021. doi: 10.25046/aj060415
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  29. Tlija Amira, Istrate Dan, Badii Atta, Gattoufi Said, Bennani Az-eddine, Wegrzyn-Wolska Katarzyna, "Stress Level Classification Using Heart Rate Variability", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 3, pp. 38–46, 2019. doi: 10.25046/aj040306
  30. Yuhei Tanizaki, Felix Jimenez, Tomohiro Yoshikawa, Takeshi Furuhashi, Masayoshi Kanoh, "Effects of Educational Support Robots using Sympathy Expression Method with Body Movement and Facial Expression on the Learners in Short and Long-term Experiments", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 2, pp. 183–189, 2019. doi: 10.25046/aj040224
  31. Tamarafinide Victory Dittimi, Ching Yee Suen, "Modified HOG Descriptor-Based Banknote Recognition System", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 5, pp. 354–364, 2018. doi: 10.25046/aj030541
  32. Shin-ichi Ito, Momoyo Ito, Minoru Fukumi, "An Electroencephalogram Analysis Method to Detect Preference Patterns Using Gray Association Degrees and Support Vector Machines", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 5, pp. 105–108, 2018. doi: 10.25046/aj030514
  33. Rasel Ahmmed, Md. Asadur Rahman, Md. Foisal Hossain, "An Advanced Algorithm Combining SVM and ANN Classifiers to Categorize Tumor with Position from Brain MRI Images", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 2, pp. 40–48, 2018. doi: 10.25046/aj030205
  34. Marwa Farouk Ibrahim Ibrahim, Adel Ali Al-Jumaily, "Auto-Encoder based Deep Learning for Surface Electromyography Signal Processing", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 1, pp. 94–102, 2018. doi: 10.25046/aj030111
  35. Diego Peluffo-Ordóñez, Paul Rosero-Montalvo, Ana Umaquinga-Criollo, Luis Suárez-Zambrano, Hernan Domínguez-Limaico, Omar Oña-Rocha, Stefany Flores-Armas, Edgar Maya-Olalla, "Theoretical developments for interpreting kernel spectral clustering from alternative viewpoints", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1670–1676, 2017. doi: 10.25046/aj0203208
  36. Kornkanok Phoksawat, Massudi Mahmuddin, "Hybrid Ontology-based knowledge with multi-objective optimization model framework for Decision Support System in intercropping", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1363–1371, 2017. doi: 10.25046/aj0203172
  37. Alexey Golubev, Maxim Shcherbakov, "Public transportation network design: a geospatial data-driven method", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1298–1306, 2017. doi: 10.25046/aj0203164
  38. Muhammad Asif Manzoor, Yasser Morgan, "Support Vector Machine based Vehicle Make and Model Recognition System", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1080–1085, 2017. doi: 10.25046/aj0203137
  39. Jawad Ahmad, Ammar Mohsin Butt, Muhammad Tanveer Riaz, Shoaib Bhutta, Muhammad Zeeshan Khan, Inam-Ul-Haq, "Multiclass Myoelectric Identification of Five Fingers Motion using Artificial Neural Network and Support Vector Machine", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1026–1033, 2017. doi: 10.25046/aj0203130
  40. Muhammad Asif Manzoor, Yasser Morgan, "Network Intrusion Detection System using Apache Storm", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 812–818, 2017. doi: 10.25046/aj0203102
  41. Mohammed Elhenawy, Hesham Rakha, "Spatiotemporal Traffic State Prediction Based on Discriminatively Pre-trained Deep Neural Networks", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 678–686, 2017. doi: 10.25046/aj020387
  42. Veena Divya K, Anand Jatti, Revan Joshi P, Sabah Meharaj, "Computer Aided Classification using Support Vector Machines in Detecting Cysts of Jaws", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 674–677, 2017. doi: 10.25046/aj020386
  43. Mazen Ghandour, Hui Liu, Norbert Stoll, Kerstin Thurow, "Human Robot Interaction for Hybrid Collision Avoidance System for Indoor Mobile Robots", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 650–657, 2017. doi: 10.25046/aj020383
  44. Marwa Farouk Ibrahim Ibrahim, Adel Ali Al-Jumaily, "Self-Organizing Map based Feature Learning in Bio-Signal Processing", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 505–512, 2017. doi: 10.25046/aj020365
  45. Turgay Yalcin, Muammer Ozdemir, "Computational Intelligence Methods for Identifying Voltage Sag in Smart Grid", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 412–419, 2017. doi: 10.25046/aj020353
  46. Sara Belarouci, Mohammed Amine Chikh, "Medical imbalanced data classification", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 116–124, 2017. doi: 10.25046/aj020316
  47. Adewale Opeoluwa Ogunde, Ajibola Rasaq Olanbo, "A Web-Based Decision Support System for Evaluating Soil Suitability for Cassava Cultivation", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 1, pp. 42–50, 2017. doi: 10.25046/aj020105
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  28. Ilya Vasilyevich Germashev, Tatyana Petrovna Mashihina, Evgeniya Vyacheslavovna Derbisher, Vyacheslav Evgenyevich Derbisher, Mikhail Alexeevich Kharitonov, "Analysis of Fuzzy Data for the Selection of Ingredients of the Polymer Composition by Technical Functions in Quality Management", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 3, pp. 88–99, 2019. doi: 10.25046/aj040313
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  30. Yuhei Tanizaki, Felix Jimenez, Tomohiro Yoshikawa, Takeshi Furuhashi, Masayoshi Kanoh, "Effects of Educational Support Robots using Sympathy Expression Method with Body Movement and Facial Expression on the Learners in Short and Long-term Experiments", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 2, pp. 183–189, 2019. doi: 10.25046/aj040224
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  32. Shin-ichi Ito, Momoyo Ito, Minoru Fukumi, "An Electroencephalogram Analysis Method to Detect Preference Patterns Using Gray Association Degrees and Support Vector Machines", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 5, pp. 105–108, 2018. doi: 10.25046/aj030514
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  34. Marwa Farouk Ibrahim Ibrahim, Adel Ali Al-Jumaily, "Auto-Encoder based Deep Learning for Surface Electromyography Signal Processing", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 1, pp. 94–102, 2018. doi: 10.25046/aj030111
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  38. Muhammad Asif Manzoor, Yasser Morgan, "Support Vector Machine based Vehicle Make and Model Recognition System", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1080–1085, 2017. doi: 10.25046/aj0203137
  39. Jawad Ahmad, Ammar Mohsin Butt, Muhammad Tanveer Riaz, Shoaib Bhutta, Muhammad Zeeshan Khan, Inam-Ul-Haq, "Multiclass Myoelectric Identification of Five Fingers Motion using Artificial Neural Network and Support Vector Machine", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1026–1033, 2017. doi: 10.25046/aj0203130
  40. Muhammad Asif Manzoor, Yasser Morgan, "Network Intrusion Detection System using Apache Storm", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 812–818, 2017. doi: 10.25046/aj0203102
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  42. Veena Divya K, Anand Jatti, Revan Joshi P, Sabah Meharaj, "Computer Aided Classification using Support Vector Machines in Detecting Cysts of Jaws", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 674–677, 2017. doi: 10.25046/aj020386
  43. Mazen Ghandour, Hui Liu, Norbert Stoll, Kerstin Thurow, "Human Robot Interaction for Hybrid Collision Avoidance System for Indoor Mobile Robots", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 650–657, 2017. doi: 10.25046/aj020383
  44. Marwa Farouk Ibrahim Ibrahim, Adel Ali Al-Jumaily, "Self-Organizing Map based Feature Learning in Bio-Signal Processing", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 505–512, 2017. doi: 10.25046/aj020365
  45. Turgay Yalcin, Muammer Ozdemir, "Computational Intelligence Methods for Identifying Voltage Sag in Smart Grid", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 412–419, 2017. doi: 10.25046/aj020353
  46. Sara Belarouci, Mohammed Amine Chikh, "Medical imbalanced data classification", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 116–124, 2017. doi: 10.25046/aj020316
  47. Adewale Opeoluwa Ogunde, Ajibola Rasaq Olanbo, "A Web-Based Decision Support System for Evaluating Soil Suitability for Cassava Cultivation", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 1, pp. 42–50, 2017. doi: 10.25046/aj020105
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