پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شماره‌ها | 671 |
| تعداد مقالات | 9,744 |
| تعداد مشاهده مقاله | 69,301,727 |
| تعداد دریافت فایل اصل مقاله | 48,564,535 |
Design and Validation of a Pressure-Based Insole for the Quantitative Assessment of Gait Abnormalities | ||
| Modeling and Simulation in Electrical and Electronics Engineering | ||
| دوره 5، شماره 4 - شماره پیاپی 22، اسفند 2025، صفحه 1-8 اصل مقاله (1.11 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/mseee.2025.37831.1214 | ||
| نویسندگان | ||
| Maryam Farivar* 1؛ Hadi Soltanizadeh2؛ Mohammad Zahrayee3 | ||
| 1Technical and Vocational Training Organization, Isfahan, Iran. | ||
| 2Electrical and Computer Engineering Faculty, Semnan University, Semnan, Iran. | ||
| 3Shahid Beheshti University, Medical Science, Tehran, Iran. | ||
| تاریخ دریافت: 03 خرداد 1404، تاریخ بازنگری: 01 شهریور 1404، تاریخ پذیرش: 02 مهر 1404 | ||
| چکیده | ||
| This study presents the design and validation of a wearable in-shoe system for real-time monitoring and quantitative analysis of plantar pressure distribution during walking. The system incorporates ten force-sensitive resistor (FSR) sensors strategically placed at key anatomical regions of each foot, enabling high-resolution pressure mapping. Data acquisition and wireless transmission are managed via an ESP32 microcontroller using TCP/IP protocol, with onboard microSD storage for redundancy. A custom graphical user interface (GUI), developed in Delphi, enables live visualization and recording. It also supports signal processing techniques, including dynamic time warping (DTW) for temporal alignment and signal averaging for noise reduction. Experimental trials were conducted on four adult participants (aged 22–45), including one individual with a normal gait and three with abnormal patterns, such as internal rotation, external rotation, and supination. Each participant completed multiple walking trials on a treadmill at a constant speed for a duration of 1 minute under standardized footwear conditions. The results confirmed that the system achieved high accuracy in distinguishing gait abnormalities, validated through quantitative metrics and visual pressure profiles. The proposed system provides a low-cost, portable, and clinically relevant solution for early detection of gait disorders and long-term rehabilitation monitoring. Its modular architecture and real-time performance demonstrate its potential as an effective tool for both clinical and remote rehabilitation monitoring. | ||
| کلیدواژه‌ها | ||
| Biomechanics؛ DTW؛ FSR sensor؛ Gait Analysis؛ Plantar Pressure Distribution؛ Postural Disorders؛ Rehabilitation Monitoring؛ Wearable Systems؛ Wireless Sensor Networks؛ Motion Impairment Detection | ||
| مراجع | ||
|
[1] U. Pant, S. Baral, A. Gupta, and P. L. Shrestha, “Design of Force Sensitive Resistor (FSR) embedded insole for phase detection during human gait and its classification.”
[2] J. A. Ramirez-Bautista, J. A. Huerta-Ruelas, S. L. Chaparro-Cárdenas, and A. Hernández-Zavala, “A Review in Detection and Monitoring Gait Disorders Using In-Shoe Plantar Measurement Systems,” Aug. 30, 2017, Institute of Electrical and Electronics Engineers. doi: 10.1109/RBME.2017.2747402.
[3] A. M. Shayan, A. Khazaei, A. Hamed, A. Amralizadeh, and M. T. Masouleh, “ShrewdShoe, a smart pressure sensitive wearable platform,” in Proceedings of the 6th RSI International Conference on Robotics and Mechatronics, IcRoM 2018, Institute of Electrical and Electronics Engineers Inc., Jul. 2018, pp. 458–463. doi: 10.1109/ICRoM.2018.8657559.
[4] A. M. Shayan, A. Khazaei, A. Hamed, A. Amralizadeh, and M. T. Masouleh, “ShrewdShoe, a smart pressure sensitive wearable platform,” in Proceedings of the 6th RSI International Conference on Robotics and Mechatronics, IcRoM 2018, Institute of Electrical and Electronics Engineers Inc., Jul. 2018, pp. 458–463. doi: 10.1109/ICRoM.2018.8657559.
[5] J. Pacheco-Chérrez, J. C. Tudon-Martinez, and J. J. de Lozoya-Santos, “Recent Advances in Pediatric Wearable Lower-Limb Exoskeletons for Gait Rehabilitation: A Systematic Review,” 2025, Institute of Electrical and Electronics Engineers Inc. doi: 10.1109/ACCESS.2025.3552757.
[6] M. Muñoz-Organero, C. Littlewood, J. Parker, L. Powell, C. Grindell, and S. Mawson, “Identification of walking strategies of people with osteoarthritis of the knee using insole pressure sensors,” IEEE Sens J, vol. 17, no. 12, pp. 3909–3920, Jun. 2017, doi: 10.1109/JSEN.2017.2696303.
[7] A. H. Abdul Razak, A. Zayegh, R. K. Begg, and Y. Wahab, “Foot plantar pressure measurement system: A review,” Jul. 2012. doi: 10.3390/s120709884.
[8] A. Jor, S. Das, A. S. Bappy, and A. Rahman, “Foot Plantar Pressure Measurement Using Low Cost Force Sensitive Resistor (FSR): Feasibility Study,” Journal of Scientific Research, vol. 11, no. 3, pp. 311–319, Sep. 2019, doi: 10.3329/jsr.v11i3.40581.
[9] W. C. Hsu, T. Sugiarto, J. W. Chen, and Y. J. Lin, “The design and application of simplified insole-based prototypes with plantar pressure measurement for fast screening of flat-foot,” Sensors (Switzerland), vol. 18, no. 11, 2018, doi: 10.3390/s18113617.
[10] N. K. Madzhi, A. Asraf, B. Muhamad, @ Mhd, and E. Abdullah, “Preliminary Investigation on the Effect of Speed Variation to Pressure Distribution for Flat, Medium and High Foot Arch.” [Online]. Available: https://www.tarjomano.com
[11] D. Price, “Midfoot pressure analysis in individuals with flat feet while climbing stairs using a pressure sensing system,” American Journal of Student Research, 2025.
[12] M. J. Domínguez-Morales, F. Luna-Perejón, L. Miró-Amarante, M. Hernández-Velázquez, and J. L. Sevillano-Ramos, “Smart footwear insole for recognition of foot pronation and supination using neural networks,” Applied Sciences (Switzerland), vol. 9, no. 19, Oct. 2019, doi: 10.3390/app9193970.
[13] P. ; P. V. B. ; R. M. ; M. B. ; K. R. S. ; R. J. R. F. Vigneshwaran, “Development of an expert system for advanced podiatric treatments and ergonomics,” 2025, pp. 924–930.
[14] Z. ; L. Y. ; C. X. ; W. H. ; L. J. Zhang, “Insole systems for disease diagnosis and rehabilitation: A review,” 2023.
[15] Y. ; W. X. ; L. H. ; C. Y. ; Z. L. Zhao, “A deep learning method for foot-type classification using plantar pressure images,” vol. 11, 2023.
[16] S. ; W. Y. ; L. Z. ; X. L. Wu, “Toward automated foot type diagnosis: A deep learning approach with attention mechanism and Grad-CAM interpretability,” Institute of Electrical and Electronics Engineers (IEEE), 2024.
[17] A. S. ; M. R. K. ; D. S. V. Patel, “i-Shoe: A Smart Insole System for Gait Imbalance Detection Using FSR Sensors and Mobile Integration,” Springer, 2024, pp. 245–258.
[18] J. A. Ramirez-Bautista, J. A. Huerta-Ruelas, S. L. Chaparro-Cárdenas, and A. Hernández-Zavala, “A Review in Detection and Monitoring Gait Disorders Using In-Shoe Plantar Measurement Systems,” Aug. 30, 2017, Institute of Electrical and Electronics Engineers. doi: 10.1109/RBME.2017.2747402.
[19] J. ; B. J. M. Perry, Gait Analysis: Normal and Pathological Function, 2nd ed. SLACK Incorporated, 2010.
[20] M. Adnan et al., “IDC pressure sensors enabled smart footwear system for in vitro detection and monitoring of diabetic foot ulcer,” Sens Actuators A Phys, vol. 388, Jul. 2025, doi: 10.1016/j.sna.2025.116489.
| ||
|
آمار تعداد مشاهده مقاله: 4 تعداد دریافت فایل اصل مقاله: 2 |
||