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Advanced version of DAid® Pressure Sock System (DPSS) for walking/running gait monitoring is proposed. The system enables to study in details time –related parameters of gait, such as foot strike time, stride/swing time, gradients of plantar loading/unloading, etc. both indoor and outdoor. A new method of data processing, analysis and representation is developed for such systems with limited quantity of sensors and implemented in DPSS software. The method considers the foot loading as a propagation of the plantar pressure wave, where separate sensors record amplitudes of pressure waves as reference points. Data processing includes scaling procedure that is based on application of sample entropy as the measure of sensors activity. Processed data are represented in the form of loading wave plots (WPs). WPs show load propagation across the sensors during the gait/stance. Developed system and method were tested for different types of walk/run and corresponding WPs were constructed and evaluated by sport medicine doctors. Good agreement between WPs – based analysis and diagnoses made by direct observation during walk/run tests confirms system efficacy and validity of results. Proposed method essentially simplifies gait studies and interpretation of the results.

Movement retraining has proven to be a reliable way of treating compensatory movement faults, however, it is time-consuming and requires a lot of attention from a physiotherapist. Reliable movement retraining assistance system could enable patients to perform retraining exercises at home, thus increasing the possible exercise performance frequentness and consequently hasten the improvement. This paper describes a smart shirt system for movement retraining assistance. The smart shirt system is based on textile stretch sensors that are positioned over the typical movement fault sites for movement detection and monitoring. The information from the textile stretch sensors is used as visual feedback by the wearer for movement corrections. To verify the feasibility of the retraining assistance system, it was tested with a set of compensatory movement tests and retraining exercises. Each exercise was performed in a correct and incorrect manner, and the sensor measurement was analyzed to confirm the difference in measured signals between both cases. In total 11 exercises were performed to cover all of the typical compensatory movement sites, and for each retraining exercise, at least one sensor was identified, whose measurement could be used as feedback for the particular exercise.