Automated design of affordable modular custom insoles by multi-classification algorithms

• Autorzy: Khaing Hnin Phyu , Chaiprapat Supapan , Na-Rungsri Tuanjit , Yuangyai Chumpol , Jirastitsin Suriya , Chaiprapat Sumate

Identyfikatory

DOI

10.2478/mspe-2021-0020

• Języki publikacji: EN

Abstrakty

EN

Custom designed insoles are a niche product that is not always affordable to all who need them. When commercial insoles are fabricated using advanced technologies, the insoles in this study are assembled out of pre-cut modular components to keep the production cost down, hence their price. In this study, algorithms driven by a fuzzy inference were proposed in comparison with a decision tree in order to select the best component combination. One hundred and twelve subjects were recruited to collect foot data extracted from their foot images. Approximately 95% of 182 AI-designed insole pads were found in perfect agreement with the professional podiatrist’s decision with acceptable 5% deviation. Differences in the algorithms’ strength were also discussed. In addition to their superior performance, both algorithms allow the podiatrists to speed up the diagnosis and design phases. This approach, when integrated with applications of mobile devices for remotely retrieving foot data, will expand another simple yet effective customer-oriented product design service.

Słowa kluczowe

EN

foot image; modular product design; custom insole; multi-classification

• Wydawca: STE GROUP
• Czasopismo: Management Systems in Production Engineering
• Rocznik: 2021
• Tom: nr 2 (29)
• Strony: 151--161
• Opis fizyczny: Bibliogr. 29 poz., rys., tab

Twórcy

autor

Khaing Hnin Phyu

• Prince of Songkla University Faculty of Engineering Department of Industrial Engineering HatYai, Songkhla, 90112, Thailand

autor

Chaiprapat Supapan

• Prince of Songkla University Faculty of Engineering Department of Industrial Engineering HatYai, Songkhla, 90112, Thailand; Tel: [phone] Fax: [phone]

autor

Na-Rungsri Tuanjit

• Prince of Songkla University Faculty of Medicine Department of Orthopedic Surgery and Physical Therapy HatYai, Songkhla, 90112, Thailand

autor

Yuangyai Chumpol

• King Mongkut’s Institute of Technology Ladkrabang Faculty of Engineering, Department of Industrial Engineering, Bangkok, 10540, Thailand

autor

Jirastitsin Suriya

• Prince of Songkla University Faculty of Engineering Department of Industrial Engineering HatYai, Songkhla, 90112, Thailand

autor

Chaiprapat Sumate

• Prince of Songkla University Faculty of Engineering Department of Civil Engineering HatYai, Songkhla, 90112, Thailand

Bibliografia

• [1] M. Ingaldi and R. Ulewicz, “Evaluation of Quality of the eCommerce Service,” Int. J. Ambient Comput. Intell. IJACI, vol. 9, no. 2, pp. 55-56, Apr. 2018.
• [2] A. Kuwabara, S. Su, and J. Krauss, “Utilizing Digital Health Technologies for Patient Education in Lifestyle Medicine,” Am. J. Lifestyle Med., vol. 14, no. 2, pp. 137-142, Apr. 2020, DOI:10.1177/1559827619892547.
• [3] G. Fabry, “Clinical practice. Static, axial, and rotational deformities of the lower extremities in children,” Eur. J. Pediatr., vol. 169, no. 5, pp. 529-534, May 2010, DOI:10.1007/s00431-009-1122-x.
• [4] S. C. Cobb, C. R. James, M. Hjertstedt, and J. Kruk, “A Digital Photographic Measurement Method for Quantifying Foot Posture: Validity, Reliability, and Descriptive Data,” J. Athl. Train., vol. 46, no. 1, pp. 20-30, 2011, DOI:10.4085/1062- 6050-46.1.20.
• [5] C.-H. Lin, Z.-H. Qiu, and C.-C. Yeh, “Image processing for rear foot image evaluating leg and foot angles,” Measurement, vol. 126, pp. 168-183, Oct. 2018, DOI:10.1016/j.measurement.2018.05.054.
• [6] C. P. Hurt et al., “Assessing a novel way to measure step count while walking using a custom mobile phone application,” PLoS ONE, vol. 13, no. 11, Nov. 2018, DOI:10.1371/journal.pone.0206828.
• [7] M. A. Kamizi, L. H. Negri, J. L. Fabris, and M. Muller, “A Smartphone Based Fiber Sensor for Recognizing Walking Patterns,” IEEE Sens. J., vol. 19, no. 21, pp. 9782-9789, Nov. 2019, DOI:10.1109/JSEN.2019.2927456.
• [8] H. Tamura, K. Sakurai, and K. Tanno, “A Study on High Accuracy Stride Estimation on Smartphone Combining Acceleration Sensor and Gyro Sensor,” J. Robot. Netw. Artif. Life, vol. 5, no. 2, pp. 83-88, Sep. 2018, DOI:10.2991/jrnal.2018.5.2.2.
• [9] “FitMyFoot | Comfort you need in shoes you love,” FitMyFoot. https://fitmyfoot.com/ [accessed Jan. 10, 2021].
• [10] “Doc Sols - Digital Podiatry App,” Doc Sols. https://docsols.com.au/ [accessed Jan. 10, 2021].
• [11] J. Niu, J. Liu, Y. Zheng, L. Ran, and Z. Chang, “Are arch-conforming insoles a good fit for diabetic foot? Insole customized design by using finite element analysis,” Hum. Factors Ergon. Manuf. Serv. Ind., vol. 30, no. 4, pp. 303-310, 2020, doi: https://DOI.org/10.1002/hfm.20841.
• [12] L. Tang et al., “Functional gradient structural design of customized diabetic insoles,” J. Mech. Behav. Biomed. Mater., vol. 94, pp. 279-287, Jun. 2019, DOI:10.1016/j.jmbbm.2019.03.003.
• [13] P. W. Anggoro et al., “CNC milling of EVA foam with varying hardness for custom orthotic shoe insoles and process parameter optimization,” J. Mech. Eng. Sci., vol. 13, no. 3, Art. no. 3, Sep. 2019, DOI:10.15282/ jmes.13.3.2019.10.0436.
• [14] B. Bawono, P. W. Anggoro, A. P. Bayuseno, J. Jamari, and M. Tauviqirrahman, “Milling strategy optimized for orthotics insole to enhance surface roughness and machining time by Taguchi and response surface methodology,” J. Ind. Prod. Eng., vol. 36, no. 4, pp. 237-247, May 2019, DOI:10.1080/21681015.2019.1646327.
• [15] P. Watasuntonpong, M. Pimsarn, and A. Tantrapiwat, “Dynamic feed rate in multiple independent spindles CNC milling machine for orthotic insole manufacturing,” Int. J. Innov. Comput. Inf. Control, vol. 15, pp. 2149-2163.
• [16] S. Xiong, J. Zhao, Z. Jiang, and M. Dong, “A computer-aided design system for foot-feature-based shoe last customization,” Int. J. Adv. Manuf. Technol., vol. 46, no. 1, pp. 11-19, Jan. 2010, DOI:10.1007/s00170-009-2087-7.
• [17] M. Davia-Aracil, J. J. Hinojo-Pérez, A. Jimeno-Morenilla, and H. Mora-Mora, “3D printing of functional anatomical insoles,” Comput. Ind., vol. 95, pp. 38-53, Feb. 2018, DOI:10.1016/j.compind.2017.12.001.
• [18] Z. Liu, P. Zhang, M. Yan, Y. M. Xie, and G. Z. Huang, “Additive manufacturing of specific ankle-foot orthoses for persons after stroke: A preliminary study based on gait analysis data,” Math. Biosci. Eng. MBE, vol. 16, no. 6, pp. 8134- 8143, Sep. 2019, DOI:10.3934/mbe.2019410.
• [19] G. Jarl and L. M. N. Hermansson, “A modified walk-in clinic for shoe insoles: Follow-up of non-attendants,” Prosthet. Orthot. Int., vol. 43, no. 6, pp. 597-600, Dec. 2019, DOI:10.1177/0309364619879285.
• [20] M. A. Pourhoseingholi, M. Vahedi, and M. Rahimzadeh, “Sample size calculation in medical studies,” Gastroenterol. Hepatol. Bed Bench, vol. 6, no. 1, pp. 14-17, 2013.
• [21] D. Kelaher, G. A. Mirka, and K. Q. Dudziak, “Effects of semirigid arch-support orthotics: an investigation with potential ergonomic implications,” Appl. Ergon., vol. 31, no. 5, pp. 515-522, Oct. 2000, DOI:10.1016/s0003- 6870(00)00018-1.
• [22] A. C. Redmond, J. Crosbie, and R. A. Ouvrier, “Development and validation of a novel rating system for scoring standing foot posture: The Foot Posture Index,” Clin. Biomech., vol. 21, no. 1, pp. 89-98, Jan. 2006, DOI:10.1016/j.clinbiomech.2005.08.002.
• [23] M. K. Nilsson, R. Friis, M. S. Michaelsen, P. A. Jakobsen, and R. O. Nielsen, “Classification of the height and flexibility of the medial longitudinal arch of the foot,” J. Foot Ankle Res., vol. 5, p. 3, Feb. 2012, DOI:10.1186/1757-1146-5-3.
• [24] T. Davenport and R. Kalakota, “The potential for artificial intelligence in healthcare,” Future Healthc. J., vol. 6, no. 2, pp. 94-98, Jun. 2019, DOI:10.7861/futurehosp.6-2-94.
• [25] L. Skrzypczak, E. Skrzypczak-Pietraszek, E. LamerZarawska, and B. Hojden, “Micropropagation of Oenothera biennis L. and an assay of fatty acids,” Acta Soc. Bot. Pol., vol. 63, no. 2, Art. no. 2, 1994, DOI:10.5586/asbp.1994.023.
• [26] E. Skrzypczak-Pietraszek and A. Hensel, “Polysaccharides from Melittis melissophyllum L. herb and callus,” Pharm., vol. 55, no. 10, pp. 768-771, Oct. 2000.
• [27] W. B. Lee, H. Lau, Z. Liu, and S. Tam, “A fuzzy analytic hierarchy process approach in modular product design,” Expert Syst., vol. 18, no. 1, pp. 32-42, 2001, https://DOI.org/10.1111/1468-0394.00153.
• [28] Jei-Zheng Wu, Kuo-Sheng Lina, and Chiao-Ying Wub, “Integration of Scenario Planning and Decision Tree Analysis for New Product Development: A Case Study of a Smartphone Project in Taiwan,” Int. J. Ind. Eng., vol. 22, no. 1, pp. 171- 182, Jan. 2015.
• [29] M. Sokolova and G. Lapalme, “A systematic analysis of performance measures for classification tasks,” Inf. Process. Manag., vol. 45, no. 4, pp. 427-437, Jul. 2009, DOI:10.1016/j.ipm.2009.03.002.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).