Design of a low-cost, portable electronic device for the estimation of reaction forces generated during walking from foot-ground contact
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Keywords

Fuerzas de reacción del suelo
plantillas de fuerza
sensores piezo-resistivos
ESP32
bajo costo Ground reaction forces
force insoles
force sensing resistors
ESP32
Low-Cost

How to Cite

Guevara, N. E., Bolaños Muñoz, Y. H., Caicedo Rodríguez, P. E., Sierra Arévalo, W. A., & Rodríguez Cheu, L. E. (2024). Design of a low-cost, portable electronic device for the estimation of reaction forces generated during walking from foot-ground contact. Vía Innova, 11(1), 73–104. https://doi.org/10.23850/2422068X.5870

Abstract

This paper presents a low-cost electronic system designed to estimate ground reaction forces (GRF). The system consists of a master node and two slave nodes. The master node sends instructions to its slave nodes, and each slave node consists of two electronic boards that sample and store data from two force templates. These templates are equipped with 14 FlexiForce A301 piezo-resistive sensors (FSR). To capture the movements, slave nodes are attached to the feet of each participant. Subsequently, the "Start" command is transmitted via the master node, which is connected to the USB port of a personal computer (PC). Once the walking session is over, the information collected by the slave nodes can be downloaded by accessing the Access Point generated by these devices via Wi-Fi connection. The proposed system for GRF estimation was validated using force platforms (BTS Bioengineering P6000, Italy), giving an error equal to 15.04 %.

https://doi.org/10.23850/2422068X.5870
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References

Burkhart, K., Grindle, D., Bouxsein, M., & Anderson, D. (2020). Between-session reliability of subject-specific musculoskeletal models of the spine derived from optoelectronic motion capture data. *Journal of Biomechanics, 112*. http://doi.org/10.1016/j.jbiomech.2020.110044

Caicedo, P., Rengifo, C., Rodriguez, L., Sierra, W., & Gómez, M. (2020). Dataset for gait analysis and assessment of fall risk for older adults. *Data in Brief, 33*. http://doi.org/10.1016/j.dib.2020.106550

Choi, H., Lee, C., Shim, M., Han, J., & Baek, Y. (2018). Design of an artificial neural network algorithm for a low-cost insole sensor to estimate the ground reaction force (GRF) and calibrate the center of pressure (CoP). *Sensors (Switzerland), 18*(12). http://doi.org/10.3390/s18124349

Ciniglio, A., Guiotto, A., Spolaor, F., & Sawacha, Z. (2021). The design and simulation of a 16-sensors plantar pressure insole layout for different applications: From sports to clinics, a pilot study. *Sensors, 21*(4), 1–24. http://doi.org/10.3390/s21041450

Company, T. (2020). Takscan calibration quick start guide for FlexiForce™ sensors. Retrieved from https://www.tekscan.com/sites/default/files/FLX-QS-Calibration-RevG.pdf

Guo, R., Cheng, X., Hou, Z.-C., Ma, J.-Z., Zheng, W.-Q., Wu, X.-M., ... Ren, T.-L. (2021). A shoe-integrated sensor system for long-term center of pressure evaluation. *IEEE Sensors Journal, 21*(23), 27 037–27 044. http://doi.org/10.1109/JSEN.2021.3116249

Kumada, H., Takada, K., Terunuma, T., Aihara, T., Matsumura, A., Sakurai, H., & Sakae, T. (2020). Monitoring patient movement with boron neutron capture therapy and motion capture technology. *Applied Radiation and Isotopes, 163*. http://doi.org/10.1016/j.apradiso.2020.109208

Langeard, A., Desjardins-Crépeau, L., Lemay, M., Payette, M.-C., Bherer, L., & Grenier, S. (2021). Cognitive performances better identify fallers than mobility assessment among older adults with fear of falling. *Aging Clinical and Experimental Research, 33*(10), 2709–2714. http://doi.org/10.1007/s40520-019-01338-9

Leal-Junior, A., Frizera, A., Avellar, L., Marques, C., & Pontes, M. (2018). Polymer optical fiber for in-shoe monitoring of ground reaction forces during the gait. *IEEE Sensors Journal, 18*(6), 2362–2368. http://doi.org/10.1109/JSEN.2018.2797363

O’Brien, M., Hidalgo-Araya, M., Mummidisetty, C., Vallery, H., Ghaffari, R., Rogers, J., ... Jayaraman, A. (2019). Augmenting clinical outcome measures of gait and balance with a single inertial sensor in age-ranged healthy adults. *Sensors (Switzerland), 19*(20). http://doi.org/10.3390/s19204537

Omaña, H., Bezaire, K., Brady, K., Davies, J., Louwagie, N., Power, S., ... Hunter, S. (2021). Functional reach test, single-leg stance test, and Tinetti performance-oriented mobility assessment for the prediction of falls in older adults: A systematic review. Physical Therapy, 101(10). http://doi.org/10.1093/ptj/pzab173

Oubre, B., Lane, S., Holmes, S., Boyer, K., & Lee, S. (2021). Estimating ground reaction force and center of pressure using low-cost wearable devices. *IEEE Transactions on Biomedical Engineering*. http://doi.org/10.1109/TBME.2021.3120346

Park, C., Kim, B., Kim, Y., Eum, Y., Song, H., Yoon, D., ... Han, J. (2022). Carved turn control with gate vision recognition of a humanoid robot for giant slalom skiing on ski slopes. *Sensors, 22*(3). http://doi.org/10.3390/s22030816

Park, H. Y., Kim, J. H., & Yamamoto, K. (2022). A new stability framework for trajectory tracking control of biped walking robots. *IEEE Transactions on Industrial Informatics, 18*(10), 6767–6777. http://doi.org/10.1109/TII.2021.3139909

Paz, J., & West, M. P. (1994). Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering.

Schlenstedt, C., Brombacher, S., Hartwigsen, G., Weisser, B., Möller, B., & Deuschl, G. (2015). Comparing the fullerton advanced balance scale with the mini-BESTest and Berg balance scale to assess postural control in patients with Parkinson disease. *Archives of Physical Medicine and Rehabilitation, 96*(2), 218–225. http://doi.org/10.1016/j.apmr.2014.09.002

Sebastião, E., Sandroff, B., Learmonth, Y., & Motl, R. (2016). Validity of the Timed Up and Go Test as a measure of functional mobility in persons with multiple sclerosis. *Archives of Physical Medicine and Rehabilitation, 97*(7), 1072–1077. http://doi.org/10.1016/j.apmr.2015.12.031

Seiberl, W., Jensen, E., Merker, J., Leitel, M., & Schwirtz, A. (2018). Accuracy and precision of loadsol® insole force-sensors for the quantification of ground reaction force-based biomechanical running parameters. *European Journal of Sport Science, 18*(8), 1100–1109. http://doi.org/10.1080/17461391.2018.1477993

Vukobratovic, M., & Branislav, B. (2004). Zero-moment point - thirty five years of its life. *International Journal of Humanoid Robotics, 1*, 157–173. https://doi.org/10.1142/S0219843604000083

Whitney, S., Poole, J., & Cass, S. (1998). A review of balance instruments for older adults. *American Journal of Occupational Therapy, 52*(8), 666–671. http://doi.org/10.5014/ajot.52.8.666

Zarzar, P. G. (2014). Force sensing insole for a balance enhancement system (Master’s thesis). Carleton University.

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