Wearable Online Freezing of Gait Detection and Cueing System.

This paper presents a real-time wearable system designed to assist Parkinson's disease patients experiencing freezing of gait episodes. The system utilizes advanced machine learning models, including convolutional and recurrent neural networks, enhanced with past sample data preprocessing to achieve high accuracy, efficiency, and robustness. By continuously monitoring gait patterns, the system provides timely interventions, improving mobility and reducing the impact of freezing episodes.

Influence of Undergarments on the Comfort Level of Scoliosis Brace Wearers.

Bracing has proven to be an effective method for the conventional treatment of scoliosis in young people. A brace, a therapeutic device, covers the upper body and promotes healing by applying pressure to specific areas. However, wearing a scoliosis brace negatively affects the user's thermo-physiological well-being and often leads to discomfort.

Human Gait Activity Recognition Machine Learning Methods.

Human gait activity recognition is an emerging field of motion analysis that can be applied in various application domains. One of the most attractive applications includes monitoring of gait disorder patients, tracking their disease progression and the modification/evaluation of drugs. This paper proposes a robust, wearable gait motion data acquisition system that allows either the classification of recorded gait data into desirable activities or the identification of common risk factors, thus enhancing the subject's quality of life.

Study on the Compression Effect of Clothing on the Physiological Response of the Athlete.

The study aimed to analyze whether the high compression of unique, tight-fitting sportswear influences the clothing physiology comfort of the athlete. Three specific sportswear with different compression were tested on four subjects while they were running on a treadmill with increasing intensity. The compression effect of the sportswear on the body of the test persons, the temperature distribution of the subjects, and the intensity of their perspiration during running were determined.

Analysis of Polygonal Computer Model Parameters and Influence on Fabric Drape Simulation.

Contemporary CAD systems enable 3D clothing simulation for the purpose of predicting the appearance and behavior of conventional and intelligent clothing in real conditions. The physical and mechanical properties of the fabric and the simulation parameters play an important role in this issue. The paper presents an analysis of the parameters of the polygonal computer model that affect fabric drape simulation.