A Systematic Approach to the Design and Characterization of A Smart Insole for Detecting Vertical Ground Reaction Force (vGRF) in Gait Analysis

Overview

Journal Sensors (Basel)

Publisher MDPI

Specialty Biotechnology

Date 2020 Feb 15

PMID 32053914

Citations 31

Authors

Anas M Tahir

Muhammad E H Chowdhury

Amith Khandakar

Sara Al-Hamouz

Merna Abdalla

Sara Awadallah

Mamun Bin Ibne Reaz

Nasser Al-Emadi

Affiliations

Soon will be listed here.

Abstract

Gait analysis is a systematic study of human locomotion, which can be utilized in variousapplications, such as rehabilitation, clinical diagnostics and sports activities. The various limitationssuch as cost, non-portability, long setup time, post-processing time etc., of the current gait analysistechniques have made them unfeasible for individual use. This led to an increase in research interestin developing smart insoles where wearable sensors can be employed to detect vertical groundreaction forces (vGRF) and other gait variables. Smart insoles are flexible, portable and comfortablefor gait analysis, and can monitor plantar pressure frequently through embedded sensors thatconvert the applied pressure to an electrical signal that can be displayed and analyzed further.Several research teams are still working to improve the insoles' features such as size, sensitivity ofinsoles sensors, durability, and the intelligence of insoles to monitor and control subjects' gait bydetecting various complications providing recommendation to enhance walking performance. Eventhough systematic sensor calibration approaches have been followed by different teams to calibrateinsoles' sensor, expensive calibration devices were used for calibration such as universal testingmachines or infrared motion capture cameras equipped in motion analysis labs. This paper providesa systematic design and characterization procedure for three different pressure sensors: forcesensitiveresistors (FSRs), ceramic piezoelectric sensors, and flexible piezoelectric sensors that canbe used for detecting vGRF using a smart insole. A simple calibration method based on a load cellis presented as an alternative to the expensive calibration techniques. In addition, to evaluate theperformance of the different sensors as a component for the smart insole, the acquired vGRF fromdifferent insoles were used to compare them. The results showed that the FSR is the most effectivesensor among the three sensors for smart insole applications, whereas the piezoelectric sensors canbe utilized in detecting the start and end of the gait cycle. This study will be useful for any researchgroup in replicating the design of a customized smart insole for gait analysis.

Citing Articles

IoT-Based Wireless System for Gait Kinetics Monitoring in Multi-Device Therapeutic Interventions.

Rathke C, Pimentel V, Alsina P, Santo C, Dantas A Sensors (Basel). 2024; 24(17).

PMID: 39275710 PMC: 11398167. DOI: 10.3390/s24175799.

Calibrating Low-Cost Smart Insole Sensors with Recurrent Neural Networks for Accurate Prediction of Center of Pressure.

Choi H, Yoon S, Kim J, Seo H, Choi J Sensors (Basel). 2024; 24(15).

PMID: 39123811 PMC: 11314829. DOI: 10.3390/s24154765.

Nonadditive Entropy Application to Detrended Force Sensor Data to Indicate Balance Disorder of Patients with Vestibular System Dysfunction.

Kose H, Ikizoglu S Entropy (Basel). 2023; 25(10).

PMID: 37895507 PMC: 10606935. DOI: 10.3390/e25101385.

Multifractal detrended fluctuation analysis of insole pressure sensor data to diagnose vestibular system disorders.

Gunaydin B, Ikizoglu S Biomed Eng Lett. 2023; 13(4):637-648.

PMID: 37872983 PMC: 10590336. DOI: 10.1007/s13534-023-00285-9.

Integration of force and IMU sensors for developing low-cost portable gait measurement system in lower extremities.

Manupibul U, Tanthuwapathom R, Jarumethitanont W, Kaimuk P, Limroongreungrat W, Charoensuk W Sci Rep. 2023; 13(1):10653.

PMID: 37391570 PMC: 10313649. DOI: 10.1038/s41598-023-37761-2.

References

Dabbah M, Graham J, Petropoulos I, Tavakoli M, Malik R . Automatic analysis of diabetic peripheral neuropathy using multi-scale quantitative morphology of nerve fibres in corneal confocal microscopy imaging. Med Image Anal. 2011; 15(5):738-47. DOI: 10.1016/j.media.2011.05.016. View

Menz H, Lord S, St George R, Fitzpatrick R . Walking stability and sensorimotor function in older people with diabetic peripheral neuropathy. Arch Phys Med Rehabil. 2004; 85(2):245-52. DOI: 10.1016/j.apmr.2003.06.015. View

Sawacha Z, Spolaor F, Guarneri G, Contessa P, Carraro E, Venturin A . Abnormal muscle activation during gait in diabetes patients with and without neuropathy. Gait Posture. 2011; 35(1):101-5. DOI: 10.1016/j.gaitpost.2011.08.016. View

Sengupta D, Pei Y, Kottapalli A . Ultralightweight and 3D Squeezable Graphene-Polydimethylsiloxane Composite Foams as Piezoresistive Sensors. ACS Appl Mater Interfaces. 2019; 11(38):35201-35211. PMC: 6767363. DOI: 10.1021/acsami.9b11776. View

Howell A, Kobayashi T, Hayes H, Foreman K, Bamberg S . Kinetic Gait Analysis Using a Low-Cost Insole. IEEE Trans Biomed Eng. 2013; 60(12):3284-90. DOI: 10.1109/TBME.2013.2250972. View

Bamberg S, Benbasat A, Scarborough D, Krebs D, Paradiso J . Gait analysis using a shoe-integrated wireless sensor system. IEEE Trans Inf Technol Biomed. 2008; 12(4):413-23. DOI: 10.1109/TITB.2007.899493. View

Akashi P, Sacco I, Watari R, Hennig E . The effect of diabetic neuropathy and previous foot ulceration in EMG and ground reaction forces during gait. Clin Biomech (Bristol). 2008; 23(5):584-92. DOI: 10.1016/j.clinbiomech.2007.11.015. View

Watari R, Sartor C, Picon A, Butugan M, Amorim C, Ortega N . Effect of diabetic neuropathy severity classified by a fuzzy model in muscle dynamics during gait. J Neuroeng Rehabil. 2014; 11:11. PMC: 3922253. DOI: 10.1186/1743-0003-11-11. View

Abdul Razak A, Zayegh A, Begg R, Wahab Y . Foot plantar pressure measurement system: a review. Sensors (Basel). 2012; 12(7):9884-912. PMC: 3444133. DOI: 10.3390/s120709884. View

10.

Kowalski E, Catelli D, Lamontagne M . Side does not matter in healthy young and older individuals - Examining the importance of how we match limbs during gait studies. Gait Posture. 2018; 67:133-136. DOI: 10.1016/j.gaitpost.2018.10.008. View

11.

Lee W, Hong S, Oh H . Characterization of Elastic Polymer-Based Smart Insole and a Simple Foot Plantar Pressure Visualization Method Using 16 Electrodes. Sensors (Basel). 2018; 19(1). PMC: 6338897. DOI: 10.3390/s19010044. View

12.

Sacco I, Amadio A . Influence of the diabetic neuropathy on the behavior of electromyographic and sensorial responses in treadmill gait. Clin Biomech (Bristol). 2003; 18(5):426-34. DOI: 10.1016/s0268-0033(03)00043-3. View

13.

Sacco I, Amadio A . A study of biomechanical parameters in gait analysis and sensitive cronaxie of diabetic neuropathic patients. Clin Biomech (Bristol). 2000; 15(3):196-202. DOI: 10.1016/s0268-0033(99)00060-1. View

14.

Shu L, Hua T, Wang Y, Li Q, Feng D, Tao X . In-shoe plantar pressure measurement and analysis system based on fabric pressure sensing array. IEEE Trans Inf Technol Biomed. 2010; 14(3):767-75. DOI: 10.1109/TITB.2009.2038904. View

15.

Heng W, Pang G, Xu F, Huang X, Pang Z, Yang G . Flexible Insole Sensors with Stably Connected Electrodes for Gait Phase Detection. Sensors (Basel). 2019; 19(23). PMC: 6928953. DOI: 10.3390/s19235197. View

16.

England J, Gronseth G, Franklin G, Carter G, Kinsella L, Cohen J . Practice Parameter: evaluation of distal symmetric polyneuropathy: role of laboratory and genetic testing (an evidence-based review). Report of the American Academy of Neurology, American Association of Neuromuscular and Electrodiagnostic Medicine,.... Neurology. 2008; 72(2):185-92. DOI: 10.1212/01.wnl.0000336370.51010.a1. View

17.

Zhu H, Wertsch J, Harris G, Loftsgaarden J, Price M . Foot pressure distribution during walking and shuffling. Arch Phys Med Rehabil. 1991; 72(6):390-7. View

18.

De Rossi S, Lenzi T, Vitiello N, Donati M, Persichetti A, Giovacchini F . Development of an in-shoe pressure-sensitive device for gait analysis. Annu Int Conf IEEE Eng Med Biol Soc. 2012; 2011:5637-40. DOI: 10.1109/IEMBS.2011.6091364. View

19.

Farahpour N, Jafarnezhad A, Damavandi M, Bakhtiari A, Allard P . Gait ground reaction force characteristics of low back pain patients with pronated foot and able-bodied individuals with and without foot pronation. J Biomech. 2016; 49(9):1705-1710. DOI: 10.1016/j.jbiomech.2016.03.056. View

20.

Dyck P, Overland C, Low P, Litchy W, Davies J, Dyck P . Signs and symptoms versus nerve conduction studies to diagnose diabetic sensorimotor polyneuropathy: Cl vs. NPhys trial. Muscle Nerve. 2010; 42(2):157-64. PMC: 2956592. DOI: 10.1002/mus.21661. View