Estimation of foot joint kinetics in three and four segment foot models using an existing proportionality scheme: Application in paediatric barefoot walking.

Recent studies which estimated foot segment kinetic patterns were found to have inconclusive data on one hand, and did not dissociate the kinetics of the chopart and lisfranc joint. The current study aimed therefore at reproducing independent, recently published three-segment foot kinetic data (Study 1) and in a second stage expand the estimation towards a four-segment model (Study 2). Concerning the reproducibility study, two recently published three segment foot models (Bruening et al., 2014; Saraswat et al., 2014) were reproduced and kinetic parameters were incorporated in order to calculate joint moments and powers of paediatric cohorts during gait. Ground reaction forces were measured with an integrated force/pressure plate measurement set-up and a recently published proportionality scheme was applied to determine subarea total ground reaction forces. Regarding Study 2, moments and powers were estimated with respect to the Instituto Ortopedico Rizzoli four-segment model. The proportionality scheme was expanded in this study and the impact of joint centre location on kinetic data was evaluated. Findings related to Study 1 showed in general good agreement with the kinetic data published by Bruening et al. (2014). Contrarily, the peak ankle, midfoot and hallux powers published by Saraswat et al. (2014) are disputed. Findings of Study 2 revealed that the chopart joint encompasses both power absorption and generation, whereas the Lisfranc joint mainly contributes to power generation. The results highlights the necessity for further studies in the field of foot kinetic models and provides a first estimation of the kinetic behaviour of the Lisfranc joint.

A Novel Method of Quantifying Gait Deviations Using Plantar Pressure Patterns.

BACKGROUND: Comparing the dynamic pedobarographic patterns of individuals is common practice in basic and applied research. However, this process is often time-consuming and complex, and commercially available software often lacks powerful visualization and interpretation tools. METHODS: We propose a simple method for displaying pixel-level pedobarographic deviations over time relative to a so-called reference pedobarographic pattern. This novel method contains four distinct automated preprocessing stages: 1) normalization of pedobarographic fields (for foot length and width), 2) temporal normalization, 3) a pixel-level z-score-based calculation, and 4) color coding of the normalized pedobarographic fields. Group and patient-level comparisons were illustrated using an experimental data set including diabetic and nondiabetic patients. RESULTS: The automated procedure was found to be robust and quantified distinct temporal deviations in pedobarographic fields. CONCLUSIONS: The advantages of the novel method cover several domains, including visualization, interpretation, and education.

Efficacy measures associated to a plantar pressure based classification system in diabetic foot medicine.

AIMS: The concept of 'classification' has, similar to many other diseases, been found to be fundamental in the field of diabetic medicine. In the current study, we aimed at determining efficacy measures of a recently published plantar pressure based classification system. METHODS: Technical efficacy of the classification system was investigated by applying a high resolution, pixel-level analysis on the normalized plantar pressure pedobarographic fields of the original experimental dataset consisting of 97 patients with diabetes and 33 persons without diabetes. Clinical efficacy was assessed by considering the occurence of foot ulcers at the plantar aspect of the forefoot in this dataset. Classification efficacy was assessed by determining the classification recognition rate as well as its sensitivity and specificity using cross-validation subsets of the experimental dataset together with a novel cohort of 12 patients with diabetes. RESULTS: Pixel-level comparison of the four groups associated to the classification system highlighted distinct regional differences. Retrospective analysis showed the occurence of eleven foot ulcers in the experimental dataset since their gait analysis. Eight out of the eleven ulcers developed in a region of the foot which had the highest forces. Overall classification recognition rate exceeded 90% for all cross-validation subsets. Sensitivity and specificity of the four groups associated to the classification system exceeded respectively the 0.7 and 0.8 level in all cross-validation subsets. CONCLUSIONS: The results of the current study support the use of the novel plantar pressure based classification system in diabetic foot medicine. It may particularly serve in communication, diagnosis and clinical decision making.

A color-code based method for the interpretation of plantar pressure measurements in clinical gait analysis.

Comparing plantar pressure measurements (PPM) of a patient following an intervention or between a reference group and a patient-group is common practice in clinical gait analysis. However, this process is often time consuming and complex, and commercially available software often lacks powerful visualization and interpretation tools. In this paper, we propose a simple method for displaying pixel-level PPM deviations relative to a so-called reference PPM pattern. The novel method contains 3 distinct stages: (1) a normalization of pedobarographic fields (for foot length and width), (2) a pixel-level z-score based calculation and, (3) color coding of the normalized pedobarographic fields. The methodological steps associated to this novel method are precisely described and clinical output illustrated. We believe that the advantages of the novel method cover several domains. The strongest advantage of the novel method is that it provides a straightforward visual interpretation of PPM without decreasing the resolution perspective. A second advantage is that it may guide the selection of a local mapping technique (data reduction technique). Finally, it may be easily used as education tool during the therapist-patient interaction.