A simple instrumented insole algorithm to estimate plantar flexion moments

Abstract

Background: Plantar flexion is critical for ambulatory function but there are few wearable solutions to monitor loading.

Research question: The purpose of this study was to develop and validate a method to calculate plantar flexion moment using a commercially-available instrumented insole.

Methods: Seven healthy young adults completed a battery of functional activities to characterize a range of plantar flexion loading which included single leg heel raise, step down, and drop jump as well as walking and running at comfortable speeds. Lower extremity trajectories were captured using motion capture and ground reaction forces were recorded with embedded force plates as well as the instrumented insole. We compared plantar flexion moment calculated by the instrumented insole to 'gold standard' inverse dynamics.

Results: We found that estimating plantar flexion moment using our instrumented insole algorithm compared favorably to moments calculated using inverse dynamics across all activities. Errors in the maximum plantar flexion moments were less than 10 % for all activities, averaging 4.9 %. Root mean square errors across the entire activity were also small, averaging 1.0 % bodyweight * height. Additionally, the calculated wave forms were strongly correlated with inverse dynamics (R_xy > 0.964).

Significance: Our findings demonstrate the utility and fidelity of a simple method for estimating plantar flexion moment using a commercially available instrumented insole. By leveraging this simple methodology, it is now feasible to prospectively track and eventually prescribe plantar flexion loading outside of the clinic to improve patient outcomes.

Keywords: Achilles tendon; Biomechanics; Inverse dynamics; Kinetics; Motion analysis; Wearable.