Feasibility of a combined video-based and instrumented insoles approach for assessing biomechanics outside the laboratory

The objective of this study is to evaluate the feasibility of alternative measurement systems for gait analysis by comparing OpenCap, a video-based motion capture system, and OpenGo Sensor Insoles, instrumented insoles capable of capturing plantar pressures, against force plates, the gold standard for measuring ground reaction force (GRF) and center of pressure (COP). The main aim is to determine how accurately these systems can estimate key biomechanical parameters, including stance times, ground reaction force, and center of pressure, under controlled conditions. The experimental protocol involved multiple trials conducted on healthy subjects walking over a force plate while simultaneously being recorded with OpenCap and wearing the instrumented insoles. Data were collected in a synchronized manner to enable a direct comparison among the different systems. After data collection, all the acquired signals were processed and analyzed using dedicated Matlab scripts, developed specifically for this study. These scripts were designed to compute stance times, extract ground reaction force and center of pressure values, and perform statistical analyses to compare the different measurement systems. For stance time analysis, the study revealed that the velocity-based detection method, implemented in the Matlab scripts for OpenCap data, resulted in significant discrepancies compared to the force-based detection methods used by both force plates and insoles. Statistical analyses, including one-way ANOVA and root mean square deviation (RMSD) calculations, confirmed that these differences were statistically significant. In the analysis of ground reaction force and center of pressure, the instrumented insoles provided measurements that generally followed the trend of the force plate data, although some discrepancies persisted, especially during dynamic phases of the gait cycle. Key sources of error for the insoles were identified as sensor drift, variations in foot positioning, and limitations in the pressure-to-force reconstruction algorithms. Statistical parametric mapping (SPM) was used to assess time-series differences in ground reaction force and center of pressure trajectories, highlighting specific phases of the gait cycle where the insole measurements deviated significantly from the force plate reference. Additional efforts were made to improve force estimation capabilities by adapting Python scripts available on OpenCap’s GitHub repository. These scripts were modified to extract ground reaction force and center of pressure values and to enhance synchronization between OpenCap and the insoles. However, this approach proved to be computationally expensive, requiring several hours to process a single trial while analyzing only a limited portion of the available data, and the synchronization remained inconsistent. Consequently, the force and pressure data derived from OpenCap were not sufficiently reliable for inclusion in the final comparative analysis. The findings of this study highlight both the potential and the limitations of alternative gait measurement systems. While OpenCap offers an accessible, markerless solution for motion capture, the reliance on custom velocity-based algorithms for stance time extraction introduces significant errors, limiting its applicability for precise temporal analysis. In contrast, the instrumented insoles show promise as a portable force measurement tool, although further refinement in their force estimation algorithms is needed to improve agreement with force plate data. This thesis provides an in-depth evaluation of these alternative gait analysis systems and contributes valuable insights into their performance under controlled conditions. The results demonstrate that, for the parameters investigated, force plates remain the most accurate method for measuring ground reaction force and center of pressure, serving as a benchmark for evaluating alternative approaches.