Journal: Frontiers in Bioengineering and Biotechnology

Article Title: In-silico techniques to inform and improve the personalized prescription of shoe insoles

doi: 10.3389/fbioe.2024.1351403

Figure Lengend Snippet: Overview schematic of the workflow from data collection (Motion Capture), musculoskeletal model personalization (Model Scaling), estimation of joint kinematics from each condition (Inverse Simulations), calibration of the insole model stiffness values (Insole Calibration), and the combination of forward simulation outputs (i.e, from shod without insole condition) with the calibrated insole model to estimate individual patient responses (Predictive Model).

Article Snippet: To achieve this goal, we first estimated the joint moments required to produce the measure joint kinematics (using in-built OpenSim tools for moment-driven froward simulations).

Techniques:

Journal: Frontiers in Bioengineering and Biotechnology

Article Title: In-silico techniques to inform and improve the personalized prescription of shoe insoles

doi: 10.3389/fbioe.2024.1351403

Figure Lengend Snippet: Example of calibration results from a single participant where blue lines indicate the average measured insole condition for selected degrees of freedom from inverse kinematics. Red lines show the kinematics from the optimal calibration solution. Note the dotted black vertical lines indicate where error was calculated within the calibration and correspond to the stage where the foot is flat on the ground.

Article Snippet: To achieve this goal, we first estimated the joint moments required to produce the measure joint kinematics (using in-built OpenSim tools for moment-driven froward simulations).

Techniques:

Journal: Frontiers in Bioengineering and Biotechnology

Article Title: In-silico techniques to inform and improve the personalized prescription of shoe insoles

doi: 10.3389/fbioe.2024.1351403

Figure Lengend Snippet: Predicted Insole kinematics (red), measured insole (green), and reference (blue) conditions for two participants (A, B) . Note the reason the predicted kinematics are in a smaller range compared to the other conditions is because we focused on a time where the foot was flat on the ground which is representative of this period.

Article Snippet: To achieve this goal, we first estimated the joint moments required to produce the measure joint kinematics (using in-built OpenSim tools for moment-driven froward simulations).

Techniques:

Journal: Frontiers in Bioengineering and Biotechnology

Article Title: In-silico techniques to inform and improve the personalized prescription of shoe insoles

doi: 10.3389/fbioe.2024.1351403

Figure Lengend Snippet: Shown are the errors between the measured and predicted kinematics for all participants for each of the joints of interest. From left to right, on the X axis is the Chopart obliquity, chopart anterior-posterior, tarsometatarsal first ray and finally the tarsometatarsal fifth ray. Each star represents a different participant were red are flatfeet patients and black are healthy participants. This distinction allowed us to further analyse if the relationship is biased by the population.

Article Snippet: To achieve this goal, we first estimated the joint moments required to produce the measure joint kinematics (using in-built OpenSim tools for moment-driven froward simulations).

Techniques: