Utilization of Smart Insole Technology in Gait Analysis: Towards Potential Gait Risks (original) (raw)
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Validation and reliability testing of a new, fully integrated gait analysis insole
Journal of Foot and Ankle Research, 2015
Background: A new tool (OpenGo, Moticon GmbH) was introduced to continuously measure kinetic and temporospatial gait parameters independently through an insole over up to 4 weeks. The goal of this study was to investigate the validity and reliability of this new insole system in a group of healthy individuals. Methods: Gait data were collected from 12 healthy individuals on a treadmill at two different speeds. In total, six trials of three minutes each were performed by every participant. Validation was performed with the FDM-S System (Zebris). Complete sensor data were used for a within test reliability analysis of over 10000 steps. Intraclass correlation was calculated for different gait parameters and analysis of variance performed. Results: Intraclass correlation for the validation was >0.796 for temporospatial and kinetic gait parameters. No statistical difference was seen between the insole and force plate measurements (difference between means: 36.3 ± 27.19 N; p = 0.19 and 0.027 ± 0.028 s; p = 0.36). Intraclass correlation for the reliability was >0.994 for all parameters measured. Conclusion: The system is feasible for clinical trials that require step by step as well as grouped analysis of gait over a long period of time. Comparable validity and reliability to a stationary analysis tool has been shown.
Sensors, 2020
Gait analysis is a systematic study of human locomotion, which can be utilized in various applications, such as rehabilitation, clinical diagnostics and sports activities. The various limitations such as cost, non-portability, long setup time, post-processing time etc., of the current gait analysis techniques have made them unfeasible for individual use. This led to an increase in research interest in developing smart insoles where wearable sensors can be employed to detect vertical ground reaction forces (vGRF) and other gait variables. Smart insoles are flexible, portable and comfortable for gait analysis, and can monitor plantar pressure frequently through embedded sensors that convert 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 of insoles sensors, durability, and the intelligence of insoles to monitor and control subjects’ gait by detecting various complications providing recommendation to enhance walking performance. Even though systematic sensor calibration approaches have been followed by different teams to calibrate insoles’ sensor, expensive calibration devices were used for calibration such as universal testing machines or infrared motion capture cameras equipped in motion analysis labs. This paper provides a systematic design and characterization procedure for three different pressure sensors: force-sensitive resistors (FSRs), ceramic piezoelectric sensors, and flexible piezoelectric sensors that can be used for detecting vGRF using a smart insole. A simple calibration method based on a load cell is presented as an alternative to the expensive calibration techniques. In addition, to evaluate the performance of the different sensors as a component for the smart insole, the acquired vGRF from different insoles were used to compare them. The results showed that the FSR is the most effective sensor among the three sensors for smart insole applications, whereas the piezoelectric sensors can be utilized in detecting the start and end of the gait cycle. This study will be useful for any research group in replicating the design of a customized smart insole for gait analysis.
Development of a Smart Insole for Medical and Sports Purposes
Procedia Engineering, 2015
A study was conducted to determine the performance of a low cost plantar measuring device. The aim of the device was to establish an in-shoe measurement system with high resolution and to take relatively accurate measurements. The calibration method for the smart material was established with the use of a Kistler force plate. The coefficient of determination r 2 of the force against resistance calibration curve was 0.974. The residual standard deviation amounted to 13.91 N. The r 2 value of the repetitive loading experiments amounted to 0.981. The residual standard deviation was 70.35 N for forces larger than 700 N. From the data obtained, the insole is deemed to be sufficiently accurate for quantitative analysis.
2021
The continuous, accurate and reliable estimation of gait parameters as a measure of mobility is essential to assess the loss of functional capacity related to the progression of disease. Connected insoles are suitable wearable devices which allow precise, continuous, remote and passive gait assessment. The data of 25 healthy volunteers aged 20 to 77 years were analysed in the study to validate gait parameters (stride length, velocity, stance, swing, step and single support durations and cadence) measured by FeetMe® insoles against the GAITRite® mat reference. The mean values and the values of variability were calculated per subject for GAITRite® and insoles. A t-test and Levene’s test were used to compare the gait parameters for means and variances, respectively, obtained for both devices. Additionally, measures of bias, standard deviation of differences, Pearson’s correlation and intraclass correlation were analysed to explore overall agreement between the two devices. No significa...
Smart Insole: A Wearable Sensor Device for Unobtrusive Gait Monitoring in Daily Life
IEEE Transactions on Industrial Informatics, 2016
Gait analysis is an important medical diagnostic process and has many applications in healthcare, rehabilitation, therapy, and exercise training. However, typical gait analysis has to be performed in a gait laboratory, which is inaccessible for a large population and cannot provide natural gait measures. In this paper, we present a novel sensor device, namely, Smart Insole, to tackle the challenge of efficient gait monitoring in real life. An array of electronic textile (eTextile) based pressure sensors are integrated in the insole to fully measure the plantar pressure. Smart Insole is also equipped with a low-cost inertial measurement unit including a 3-axis accelerometer, a 3-axis gyroscope, and a 3axis magnetometer to capture the gait characteristics in motion. Smart Insole can offer precise acquisition of gait information. Meanwhile, it is lightweight, thin, and comfortable to wear, providing an unobtrusive way to perform the gait monitoring. Furthermore, a smartphone graphic user interface is developed to display the sensor data in real-time via Bluetooth low energy. We perform a set of experiments in four real-life scenes including hallway walking, ascending/descending stairs, and slope walking, where gait parameters and features are extracted. Finally, the limitation and improvement, wearability and usability, further work, and healthcare-related potential applications are discussed.
Kinetic Gait Analysis Using a Low-Cost Insole
IEEE Transactions on Biomedical Engineering, 2000
Abnormal gait caused by stroke or other pathological reasons can greatly impact the life of an individual. Being able to measure and analyze that gait is often critical for rehabilitation. Motion analysis labs and many current methods of gait analysis are expensive and inaccessible to most individuals. The low-cost, wearable, and wireless insole-based gait analysis system in this study provides kinetic measurements of gait by using lowcost force sensitive resistors. This paper describes the design and fabrication of the insole and its evaluation in six control subjects and four hemiplegic stroke subjects. Subject-specific linear regression models were used to determine ground reaction force plus moments corresponding to ankle dorsiflexion/plantarflexion, knee flexion/extension, and knee abduction/adduction. Comparison with data simultaneously collected from a clinical motion analysis laboratory demonstrated that the insole results for ground reaction force and ankle moment were highly correlated (all >0.95) for all subjects, while the two knee moments were less strongly correlated (generally >0.80). This provides a means of cost-effective and efficient healthcare delivery of mobile gait analysis that can be used anywhere from large clinics to an individual's home.
Validation of the wearable sensor system - MoveSole® smart insoles
2021
Biomechanical analysis of gait is commonly used in physiotherapy. Ground reaction forces during phases of gait is one element of kinetic analysis. In this article, we analyze if the MoveSole® smart insole is valid and accurate equipment for measuring ground reaction forces in clinical physiotherapy. MoveSole® StepLab is a mobile measurement system for instant underfoot force measurements during gait. Unique electromagnetic film (EMFI) based sensor technology and printed electronics production technology is integrated in the MoveSole® StepLab measurement system. The MoveSole® StepLab measures plantar ground reaction force distribution over the sensors and provides an estimation of the maximum total ground reaction force. We developed a two phase validation process to extract relevant parameters and compared the results to a Kistler force plate using the BioWare® analyzing program as a reference method. Our results show that MoveSole® smart insoles reach the strong level of accuracy n...
Journal of the American Podiatric Medical Association, 2018
Background:There is a lack of data that could address the effects of off-the-shelf insoles on gait variables in healthy people.Methods:Thirty-three healthy volunteers ranging in age from 18 to 35 years were included to this study. Kinematic and kinetic data were obtained in barefoot, shoe-only, steel insole, silicone insole, and polyurethane insole conditions using an optoelectronic three-dimensional motion analysis system. A repeated measures analysis of variance test was used to identify statistically significant differences between insole conditions. The alpha level was set at P < .05Results:Maximum knee flexion was higher in the steel insole condition (P < .0001) compared with the silicone insole (P = .001) and shoe-only conditions (P = .032). Reduced maximum knee flexion was recorded in the polyurethane insole condition compared with the shoe-only condition (P = .031). Maximum knee flexion measured in the steel insole condition was higher compared to the barefoot conditio...
Stridalyzer Insight Smart Insoles: a Clinical Grade Gait Analysis System
2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU), 2019
Gait analysis is crucial in the medical sphere, sports and research. It can facilitate prevention of diseases having gaitrelated symptoms, alleviation of pain with posture correction and performance improvement. It is being simplified and made more accessible with the development of sensor insoles combined with intelligent analytics. Stridalyzer INSIGHT is a smart insole system which offers ubiquitous clinical-grade gait analysis. In this paper, we present an overview of the device and the embedded sensor network, and evaluation of the data results. Weight distribution, vertical ground reaction force (GRF) and ground contact time (GCT) data has been evaluated using statistical metrics, with the pressure plate as the gold standard. The percentage difference in weight distribution data between the insoles and pressure plate were found to be 7.75(0.78) and-3.85(5.87) for left and right respectively. The correlation between the insoles and pressure plate vertical GRF data for dynamic gait (walking) was found to be 0.65(0.07) and 0.9 for left and right respectively. The percentage difference in GCT data between the insoles and pressure plate were found to be 0 and 12.4(1.8) for left and right respectively. The accuracy of the data can be improved by reducing the capacitance of the sensors and the circuit, compensating for the temporal and magnitudinal effects of capacitance while processing data and increasing the sensor area. Stridalyzer INSIGHT smart insoles can provide out-of-clinic gait analysis to complement the clinical systems, but the data needs to be validated for more varied anthropometric measurements.
Journal of Sensor and Actuator Networks
A SmartInsoles Cyber-Physical System (CPS) is designed and implemented for the purpose of measuring gait parameters of multiple users in a restriction-free environment. This CPS comprises a master software installed on a computer and numerous multi-sensory health devices in the form of smart insoles. Each of these insoles contains 12 Force-Sensitive Resistor (FSR) sensors, an Inertial Measurement Unit (IMU), a WiFi-enabled microcontroller and a battery to power all components. A validation pilot study was completed in collaboration with the Interdisciplinary School of Health Sciences at the University of Ottawa by performing 150 trials on 15 healthy subjects. Each subject performed 10 walks on the Tekscan Strideway gait mat system, while simultaneously wearing the designed SmartInsoles CPS. Spatiotemporal data for over 450 unique steps were collected by both systems. These data were analyzed carefully, and a thorough comparison was performed between the results from the two systems....