GAIT PARTITIONING WITH SMART SOCKS SYSTEM

Gait is a very complex movement, involving the central nervous system and a significant part of the skeletomuscular system. Any disease that is affecting one or more of the involved parts will reflect in the gait. Therefore, gait analysis has been studied extensively in the context of early disease diagnostics, post-operation rehabilitation monitoring, and sports injury prevention. Gait cycle phase partitioning is one of the most common gait characteristic analysis methods, which utilizes the cyclical nature of human gait. Pressure sensitive mats and insoles are considered the gold standard, but some inherent limitations of these methods urge researchers to seek for alternatives. One of the proposed alternatives is Smart Sock systems, which contain textile pressure sensors. The main limitation of Smart Sock systems is the limited number of sensors, thus complicating gait phase partitioning by these systems. The present paper describes gait phase partitioning using plantar pressure signal obtained by a Smart Sock system. Six-phase partitioning was achieved, including such gait phases as initial contact, loading response, mid stance, terminal stance, pre-swing and swing phase. Mean gait cycle time values obtained from the experimental data were in accordance with the ones found in the literature.

SMART GLOVE USAGE POSSIBILITY FOR BASKETBALL TRAINING: PROOF OF CONCEPT

Nowadays, basketball is one of the most entertaining and popular sports. In the last years, the number of people that are dedicating themselves to basketball has grown rapidly. The increasing number of sportsmen defines the increasing demand to monitor and analyse their performance, hereby granting the possibility to review and evaluate mistakes made within different game phases, which, in turn, would be useful for future training. The present research is the first step to develop a wireless system (Smart Basketball Glove (SBG)) for basketball shot analysis and training. SBG system is based on knitted tension and pressure sensors that were already successfully used in Smart Socks and Smart Shirt applications. These sensors, while embedded into the proposed system’s textile part, showed high tactile sensitivity and speed of response and, therefore, demonstrates potential abilities to analyse the wrist and fingers movement and estimate the forces with which fingers interact with the ball during basketball shot. Necessary requirements for data acquisition and transition device of SBG are formulated for further system’s development as well.

Improving the recovery of patients with subacromial pain syndrome with the daid smart textile shirt

Funding Information: Funding: This work has been supported by the European Regional Development Fund within the Activity 1.1.1.2 “Post‐doctoral Research Aid” of the Specific Aid Objective 1.1.1 “To increase the research and innovative capacity of scientific institutions of Latvia and the ability to attract external financing, investing in human resources and infrastructure” of the Operational Program “Growth and Employment” (No. 1.1.1.2/VIAA/1/16/153). Publisher Copyright: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Wearable technologies provide many possibilities for applications in medicine, and especially in physiotherapy, where tracking and evaluation of body motion are of utmost importance. Despite the existence of multiple smart garments produced for applications in physiotherapy, there is limited information available on the actual impact of these technologies on the clinical outcomes. The objective of this paper is to evaluate the impact of the Double Aid (DAid) smart shirt, a purely textile‐based system, on the training process of patients with subacromial pain syndrome. A randomized controlled trial was performed where patients with subacromial pain syndrome had to perform the assigned training exercises while employing the DAid smart shirt system. The core point of each exercise was to perform a movement while holding the shoulders stationary. The smart shirt was designed to sense even slight shoulder motion thus providing the patient with feedback on the accuracy of the motion, and allowing the patient to adjust the movement. The appropriate muscles should be strengthened through an increased effort to control the shoulder motion. The recovery of patients using the feedback system at the end of the treatment was compared to that of a reference group through standardized tests—the Disabilities of the Arm, Shoulder, and Hand score (DASH score), Closed Kinetic Chain Upper Extremity Stability test (CKCUES test), and internal/external rotation ratio. The test group that used the DAid system demonstrated significantly better results of the performed tests for all applied outcome measures compared to the reference group (p <0.001). An overall positive impact on the patient recovery was observed from the DAid smart shirt system when applied for rehabilitation training of patients with subacromial pain syndrome.Peer reviewe