The effects of railroad ballast surface and slope on rearfoot motion in walking

Closing the Wearable Gap-Part VII: A Retrospective of Stretch Sensor Tool Kit Development for Benchmark Testing

This paper presents a retrospective of the benchmark testing methodologies developed and accumulated into the stretch sensor tool kit (SSTK) by the research team during the Closing the Wearable Gap series of studies. The techniques developed to validate stretchable soft robotic sensors (SRS) as a means for collecting human kinetic and kinematic data at the foot-ankle complex and at the wrist are reviewed. Lessons learned from past experiments are addressed, as well as what comprises the current SSTK based on what the researchers learned over the course of multiple studies. Three core components of the SSTK are featured: (a) material testing tools, (b) data analysis software, and (c) data collection devices. Results collected indicate that the stretch sensors are a viable means for predicting kinematic data based on the most recent gait analysis study conducted by the researchers (average root mean squared error or RMSE = 3.63°). With the aid of SSTK defined in this study summary and shared with the academic community on GitHub, researchers will be able to undergo more rigorous validation methodologies of SRS validation. A summary of the current state of the SSTK is detailed and includes insight into upcoming experiments that will utilize more sophisticated techniques for fatigue testing and gait analysis, utilizing SRS as the data collection solution.

Closing the Wearable Gap—Part IV: 3D Motion Capture Cameras Versus Soft Robotic Sensors Comparison of Gait Movement Assessment

The purpose of this study was to use 3D motion capture and stretchable soft robotic sensors (SRS) to collect foot-ankle movement on participants performing walking gait cycles on flat and sloped surfaces. The primary aim was to assess differences between 3D motion capture and a new SRS-based wearable solution. Given the complex nature of using a linear solution to accurately quantify the movement of triaxial joints during a dynamic gait movement, 20 participants performing multiple walking trials were measured. The participant gait data was then upscaled (for the SRS), time-aligned (based on right heel strikes), and smoothed using filtering methods. A multivariate linear model was developed to assess goodness-of-fit based on mean absolute error (MAE; 1.54), root mean square error (RMSE; 1.96), and absolute R2 (R2; 0.854). Two and three SRS combinations were evaluated to determine if similar fit scores could be achieved using fewer sensors. Inversion (based on MAE and RMSE) and plantar flexion (based on R2) sensor removal provided second-best fit scores. Given that the scores indicate a high level of fit, with further development, an SRS-based wearable solution has the potential to measure motion during gait- based tasks with the accuracy of a 3D motion capture system.

Biomechanical Effect of Foot Orthoses on Rearfoot Motions and Joint Moment Parameters in Patients with Flexible Flatfoot

Background

The effect of foot orthoses in terms of kinematics and kinetics during walking could be affected on different geometrical designs. Therefore, the purpose of this study was to compare the biomechanical and clinical effects of 3 different insoles on rearfoot motion (RFM) and ankle joint moment parameters.

Material/Methods

Twenty eight university students with flexible flatfoot were recruited for this study, and each participant was asked to wear 3 different insoles: normal insole without arch support function, type A insole with only arch support function, and type B insole with both arch support and cushion pads for shock absorbing functions. Three-dimensional motion analysis was performed to compute the ranges and peak orientation angles of RFM and ankle joint moment parameters.

Results

The type A and type B insoles exhibited significantly smaller peak everted position and evertor moment than the normal insole. Also, the type A insole showed significantly smaller range of rearfoot motion in the longitudinal axis and the length of MA (moment arm) in the mediolateral axis than the normal insole.

Conclusions

The use of the type A insole using arch support function was induced to promote a cautious gait pattern associated with a relatively lower potential risk compared to the normal insole. The type A and type B insoles could be important to positively reduce the possibility of injury. Also, the smaller length of MA in the type A insole might have a contribution to the decrease of ankle joint evertor moment.