ArticleSensors (Basel, Switzerland)2020
A Systematic Approach to the Design and Characterization of A Smart Insole for Detecting Vertical Ground Reaction Force (vGRF) in Gait Analysis.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it, 117 citations in OpenAlex.
- Deep Learning in the Detection and Diagnosis of COVID-19 Using Radiology Modalities: A Systematic Review.Journal of healthcare engineering · 2021Pooled it
- Portable electronic devices for mechanotherapy and operative treatment of osteoarthritis.Mechanobiology in medicine · 2026Review
- From Static to Dynamic: Complementary Roles of FSR and Piezoelectric Sensors in Wearable Gait and Pressure Monitoring.Sensors (Basel, Switzerland) · 2025Article
- 3D-Printed Insole for Measuring Ground Reaction Force and Center of Pressure During Walking.Sensors (Basel, Switzerland) · 2025Article
- IoT-Based Wireless System for Gait Kinetics Monitoring in Multi-Device Therapeutic Interventions.Sensors (Basel, Switzerland) · 2024Article
- Calibrating Low-Cost Smart Insole Sensors with Recurrent Neural Networks for Accurate Prediction of Center of Pressure.Sensors (Basel, Switzerland) · 2024Article
- Multifractal detrended fluctuation analysis of insole pressure sensor data to diagnose vestibular system disorders.Biomedical engineering letters · 2023Article
- Nonadditive Entropy Application to Detrended Force Sensor Data to Indicate Balance Disorder of Patients with Vestibular System Dysfunction.Entropy (Basel, Switzerland) · 2023Article
- Integration of force and IMU sensors for developing low-cost portable gait measurement system in lower extremities.Scientific reports · 2023Article
- Modeling and Calibration of Pressure-Sensing Insoles via a New Plenum-Based Chamber.Sensors (Basel, Switzerland) · 2023Article
- Optimal locations and computational frameworks of FSR and IMU sensors for measuring gait abnormalities.Heliyon · 2023Review
- Soft Electronics for Health Monitoring Assisted by Machine Learning.Nano-micro letters · 2023Review
- Effects of three-dimensional image based insole for healthy volunteers: a pilot clinical trial.Translational and clinical pharmacology · 2023Article
- Characterization of the Kinetyx SI Wireless Pressure-Measuring Insole during Benchtop Testing and Running Gait.Sensors (Basel, Switzerland) · 2023Article
- A 3D-Printed Capacitive Smart Insole for Plantar Pressure Monitoring.Sensors (Basel, Switzerland) · 2022Article
- Gait Improvement by Alerted Push-Off via Heating of Insole Tip.Healthcare (Basel, Switzerland) · 2022Article
- Design and Implementation of a Smart Insole System to Measure Plantar Pressure and Temperature.Sensors (Basel, Switzerland) · 2022Article
- Machine Learning Strategies for Low-Cost Insole-Based Prediction of Center of Gravity during Gait in Healthy Males.Sensors (Basel, Switzerland) · 2022Article
- Assessment System for Predicting Maximal Safe Range for Heel Height by Using Force-Sensing Resistor Sensors and Regression Models.Sensors (Basel, Switzerland) · 2022Article
- Estimating Ground Reaction Force and Center of Pressure Using Low-Cost Wearable Devices.IEEE transactions on bio-medical engineering · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.