Effect of 3D printed insoles for people with flatfeet: a systematic review

Flatfoot arch correction with generic 3D-printed orthoses at different body weight percentages

BACKGROUND

Flatfoot can be associated with foot pathologies and treated conservatively with foot orthoses to correct arch collapse and alleviate painful symptoms. Recently, 3D printing has become more popular and is widely used for medical device manufacturing, such as orthoses. This study aims at quantifying the effect of generic 3D-printed foot orthoses on flatfoot arch correction under different static loading conditions.

METHODS

Participants with normal and flatfeet were recruited for this cross-sectional study. Clinical evaluation included arch height, foot posture index, and Beighton flexibility score. Surface imaging was performed in different loading conditions: 1) 0% when sitting, 2) 50% when standing on both feet, and 3) 125% when standing on one foot with a weighted vest. For flatfoot participants, three configurations were tested: without an orthosis, with a soft generic 3D printed orthosis, and with a rigid 3D printed orthosis. Arch heights and medial arch angles were calculated and compared for the different loading conditions and with or without orthoses. The differences between groups, with and without orthoses, were analyzed with Kruskal-Wallis tests, and a p < 0.05 was considered significant.

RESULTS

A total of 10 normal feet and 10 flatfeet were analyzed. The 3D printed orthosis significantly increased arch height in all loading conditions, compared to flatfeet without orthosis. Wearing an orthosis reduced the medial arch angle, although not significantly. Our technique was found to have good to excellent intra and interclass correlation coefficients.

CONCLUSIONS

Generic 3D printed orthoses corrected arch collapse in static loading conditions, including 125% body weight to simulate functional tasks like walking. Our protocol was found to be reliable and easier to implement in a clinical setting compared to previously reported methods.

LEVEL OF EVIDENCE

II.

3D Printed customized diabetic foot insoles with architecture designed lattice structures - a case study

This study proposes a 3D printed, custom insole using an architectural lattice structure infill targeting diabetic patients at risk of foot ulcers. An analysis of five lattice configurations: Fluorite, Kelvin, Octet, Isotruss unit cells, and Truncated Octahedron was conducted to identify the most effective insole infill for plantar pressure and weight redistribution. The Kelvin lattice demonstrated minimal stiffness, suggesting its superiority in balancing plantar pressure and weight. Such lattice-structured insoles offer enhanced foot support and cushioning, crucial for ulcer-prone individuals. This research innovatively employs architectural lattice structures in designing insoles for diabetic patients, offering an insightful comparison of lattice designs for optimized foot care.

Can a shoe-mounted IMU identify the effects of orthotics in ways comparable to gait laboratory measurements?

BACKGROUND

Footwear and orthotic research has traditionally been conducted within laboratories. With increasing prevalence of wearable sensors for foot and ankle biomechanics measurement, transitioning experiments into the real-world is realistic. However wearable systems must effectively detect the direction and magnitude of response to interventions to be considered for future usage.

METHODS

RunScribe IMU was used simultaneously with motion capture, accelerometers, and force plates during straight-line walking. Three orthotics (A, B, C) were used to change lower limb biomechanics from a control (SHOE) including: Ground reaction force (GRF) loading rate (A), pronation excursion (A and B), maximum pronation velocity (A and B), and impact shock (C) to test whether RunScribe detected effects consistent with laboratory measurements. Sensitivity was evaluated by assessing: 1. Significant differences (t-test) and effect sizes (Cohen's d) between measurement systems for the same orthotic, 2. Statistical significance (t-test and ANOVA) and effect size (Cohen's d & f) for orthotic effect across measurement systems 3. Direction of orthotic effect across measurement systems.

RESULTS

GRF loading rate (SHOE: p = 0.138 d = 0.403, A: p = 0.541 d = 0.165), impact shock (SHOE: p = 0.177 d = 0.405, C: p = 0.668 d = 0.132), pronation excursion (A: p = 0.623 d = 0.10, B: p = 0.986 d = 0.00) did not significantly differ between measurement systems with low effect size. Significant differences and high effect sizes existed between systems in the control condition for pronation excursion (p = 0.005 d = 0.68), and all conditions for pronation velocity (SHOE: p < 0.001 d = 1.24, A: p = 0.001 p = 1.21, B: p = 0.050 d = 0.64). RunScribe (RS) and Laboratory (LM) recorded the same significant effect of orthotic but inconsistent effect sizes for GRF loading rate (LM: p = 0.020 d = 0.54, RS: p = 0.042 d = 0.27), pronation excursion (LM: p < 0.001 f = 0.31, RS: p = 0.042 f = 0.15), and non-significant effect of orthotic for impact shock (LM: p = 0.182 d = 0.08, RS: p = 0.457 d = 0.24). Statistical significance was different between systems for effect of orthotic on pronation velocity (LM: p = 0.010 f = 0.18, RS: p = 0.093 f = 0.25). RunScribe and Laboratory agreed on the direction of change of the biomechanics variables for 69% (GRF loading rate), 40%-70% (pronation excursion), 47%-65% (pronation velocity), and 58% (impact shock) of participants.

CONCLUSION

The RunScribe shows sensitivity to orthotic effect consistent with the laboratory at the group level for GRF loading rate, pronation excursion, and impact shock during walking. There were however large discrepancies between measurements in individuals. Application of the RunScribe for group analysis may be appropriate, however implementation of RunScribe for individual assessment and those including pronation may lead to erroneous interpretation.

3D Printing of Individual Running Insoles - A Case Study

Purpose

The study's starting point is to find a low-cost and best-fit solution for comfortable movement for a recreational runner with knee pain using an orthopedic device. It is a case study. The research aims to apply digitization, CAD/CAM tools, and 3D printing to create an individual 3D running insole. The objective is to incorporate flexible shape optimization would provide comfort reductions in foot plantar pressures in one subject with knee pain while running. The test hypothesis was if it is possible to make it from one material. For this purpose, we created a new digital workflow based on the Decision Tree method and analyzed pain and comfort scores during user testing of prototypes.

Patient and Methods

The input data were obtained during a professional examination by a specialist doctor in the orthopedic outpatient clinic in the motion laboratory (DIERS 4D Motion Lab, Germany) with the output of data on the proband's complex movement stereotype. Surface and volumetric data were obtained in the biomedical laboratory with the 3D scanner. We modified the digital 3D foot models in 3D mesh software, developed the design in SW Gensole (Gyrobot, UK), and finally incorporated the internal structure and the surface layer of the insole data of the knowledge from the medical examination, comfort analyses, and scientific studies findings.

Results

Four complete 3D-printed prototypes (n=4) with differences in density and correction elements were designed. All of them were fabricated on a 3D printer (Prusa i3 MK3S, Czech Republic) with flexible TPU material suitable for skin contact. The Participant tested each of them five times in the field during a workout and final insoles three months on the routine training.

Conclusion

A novel workflow was created for designing, producing, and testing full 3D-printed insoles. The product is fit for immediate use.