Nowadays stroke remains the second-leading cause of death and the third-leading cause of death and disability combined . In almost all cases poststroke patients will need rehabilitation under physiotherapist guidelines to handle motor disorders . The role of the physiotherapist includes provision of feedback to the patient to prevent the formation of incorrect movement habits. The alternative approach to provide such feedback, especially for at-home exercises, is based on the use of the smart garment that integrates textile pressure and stretch sensors. To realize this approach a prototype of DAid (Double Aid) leggings system for post-stroke rehabilitation exercises on the lower extremities and a data processing method has been developed. An original method for determining the reference ranges (RR) of exercises for the lower extremities used in post-stroke rehabilitation was proposed, and the corresponding RRs were determined. The classification rules, enabling both the real-time detection of errors of the individual motion of lower extremities during execution of post stroke exercises, as well as estimation of the performance of the entire series, were formulated. The effectiveness of the proposed classification method was demonstrated in a series of test exercises, by comparison of the classification, made using the developed system, with estimation, made by qualified expert - physiotherapist. Depending on the type of exercises, the developed system discovered from 84% to 100% of the errors, identified by the physiotherapist.