Dynamic plantar loading index detects altered foot function in individuals with rheumatoid arthritis but not changes due to orthotic use

pressuRe: an R package for analyzing and visualizing biomechanical pressure distribution data

In many biomechanical analyses, the forces acting on a body during dynamic and static activities are often simplified as point loads. However, it is usually more accurate to characterize these forces as distributed loads, varying in magnitude and direction, over a given contact area. Evaluating these pressure distributions while they are applied to different parts of the body can provide effective insights for clinicians and researchers when studying health and disease conditions, for example when investigating the biomechanical factors that may lead to plantar ulceration in diabetic foot disease. At present, most processing and analysis for pressure data is performed using proprietary software, limiting reproducibility, transparency, and consistency across different studies. This paper describes an open-source software package, 'pressuRe', which is built in the freely available R statistical computing environment and is designed to process, analyze, and visualize pressure data collected on a range of different hardware systems in a standardized manner. We demonstrate the use of the package on pressure dataset from patients with diabetic foot disease, comparing pressure variables between those with longer and shorter durations of the disease. The results matched closely with those from commercially available software, and individuals with longer duration of diabetes were found to have higher forefoot pressures than those with shorter duration. By utilizing R's powerful and openly available tools for statistical analysis and user customization, this package may be a useful tool for researchers and clinicians studying plantar pressures and other pressure sensor array based biomechanical measurements. With regular updates intended, this package allows for continued improvement and we welcome feedback and future contributions to extend its scope. In this article, we detail the package's features and functionality.

The influence of population characteristics and measurement system on barefoot plantar pressures: A systematic review and meta-regression analysis

BACKGROUND

The measurement of plantar pressure distributions during gait can provide insights into the effects of musculoskeletal disease on foot function. A range of hardware, software, and protocols are available for the collection of this type of data, with sometimes disparate and conflicting results reported between individual studies. In this systematic review and meta-regression analysis of dynamic regional peak pressures, we aimed to test if 1) the system used to obtain the pressure measurements and 2) the characteristics of the study populations had a significant effect on the results.

METHODS

A systematic review of the literature was undertaken to identify articles reporting regional peak plantar pressures during barefoot walking. A mixed-effects modeling approach was used to analyze the extracted data. Initially, the effect of the system used to collect the data was tested. Following this, the effect of participant characteristics on the results were analyzed, using moderators of cohort type (defined as the primary health characteristic of the participants), age, sex, and BMI.

RESULTS

115 participant groups were included in the analysis. Sufficient cohorts were available to test those that consisted of healthy individuals, and those with diabetes and diabetic neuropathy. Significant differences were found between results reported by studies using different pressure measurement systems in 8 of the 16 regions analyzed. The analysis of participant characteristics revealed a number of significant relationships between regional peak pressures and participant characteristics, including: BMI and midfoot plantar pressures; elevated forefoot pressures as a result of diabetic neuropathy; and sex-differences in regional loading patterns.

CONCLUSIONS

At the level of the literature, we confirmed significant effects of disease status, age, BMI, and sex on regional peak plantar pressures. Researchers and clinicians should be aware that measurements of peak plantar pressure variables obtained from different collection equipment are not directly comparable.