Search Results (4)

With growing interest in wearable technologies, the development of flexible sensors and products that can monitor the human body while being comfortable to wear is gaining momentum. While various textile-based strain sensors have been proposed, their implementation in practical, exercise-specific applications remains limited. In this study, we developed a knitted strain sensor that monitors elbow angles, focusing on dumbbell exercise, which is a basic exercise in sports, and verified its performance. The material of the developed knitted strain sensor with a plain stitch structure comprised a silver-coated nylon conductive yarn and an acrylic/wool blended yarn. To evaluate the electrical and physical characteristics of the developed sensor, a textile folding tester was used to conduct 100 repeated bending experiments at three angles of 30°, 60°, 90° and speeds of 10, 30, 60 cpm. The system demonstrated excellent elasticity, high sensitivity (gauge factor = 698), fast responsiveness, and reliable performance under repeated stress, indicating its potential for integration into wearable fitness or rehabilitation platforms. Full article

To avoid the critical problems of effective drugs not being carried to their targeted cancers and their quantity and location not being sensed in situ, this work presents a completely new innovative strategy to achieve both smart cancer targeting (SCT) and super-sensitive sensing (SSS), where one drug carrier works for effective drug loading and release. Herein, malignant melanoma treatment is used as an example of reliable detection and effective therapy. We report two characteristic dumbbell-like nano-micelles and spherical-like nano-micelles of hyaluronan induced by the Eu³⁺/Tb³⁺ complexes for effective drug loading and release, respectively. These special Eu³⁺/Tb³⁺-loaded nano-micelles (marked as ENM and TNM) have strong and sharp red/green luminescence that can sensitively detect the malignant melanoma drug dacarbazine through changes in fluorescence intensity. Cytotoxicity experiments confirmed that both ENM and TNM are not toxic to normal cells at very high concentrations of 4 mM. However, when loaded with cancer drugs (D-ENM and D-ENM), they both killed cancer cells with more than 40% efficacy at this concentration. The in vivo experiments confirmed that D-ENM and D-TNM can effectively target cancer cells in tissue and effectively impede cancer growth. The detection limits of ENM and TNM in sensing cancer drugs can reach 0.456 μg/mL and 0.139 μg/mL, respectively. Therefore, the reported Eu³⁺/Tb³⁺-induced hyaluronan nano-micelles (ENM and TNM) are distinguished carriers of this cancer drug and excellent in situ sensors, and they have highly therapeutic effects with extremely low toxicity to normal cells. Full article

Respiratory diseases are common in post-stroke hemiplegic patients and represent a major social problem as they worsen the quality of life and reduce the life span. As a consequence, being able to monitor respiratory parameters such as the respiratory rate (RR) and assess the presence of respiratory asynchronies could be of paramount importance to define hemiplegics’ health status. Moreover, RR is a useful parameter to investigate the level of fatigue and distress that these patients undergo during rehabilitation processes. Although motion capture systems and flowmeters are the leading instruments for respiratory pattern evaluation, smart wearable systems are gaining ever more acceptance since they allow continuous monitoring by detecting chest wall breathing displacements, ensuring reduced costs and no need for dedicated spaces. Among other sensing technologies, fiber Bragg grating (FBG) sensors have emerged thanks to their high sensitivity to strain, lightness, and multiplexing capability. In this work, a wearable system composed of four flexible dumbbell-shaped sensing modules is proposed for respiratory monitoring in hemiplegic patients. The system is light and easy to wear and can be adapted to any anthropometry thanks to the modular anchoring system. Its feasibility assessment in RR evaluation was performed on seven hemiplegic volunteers in eupnea and tachypnea breathing conditions. In addition, an explorative investigation was conducted to assess the system’s ability to detect asynchronies between torso compartments. The good results suggest that this device could be a useful instrument to support clinicians and operators in hemiplegic patients’ management. Full article

Exercise is good for health, quality of life, and maintenance of human muscles. Dumbbells are popular indoor exercise equipment with several benefits such as low cost, high flexibility in space and time, easy operation, and suitability for people of all ages. Facilitated by advances in the Internet of Things, smart dumbbells that provide automatic counting and motion monitoring functions have been developed. To perform these tasks, the key process is identification of exercise mode. This study proposes a method to identify essential muscle groups’ (biceps, triceps, and deltoids) exercise modes of a dumbbell using an inertial measurement unit to provide three-axis angular velocities and accelerations. The motion angles were estimated from the axial acceleration and angular velocity. Phase diagrams and time plots of the axial angle, angular velocity, and acceleration were used to extract significant features of each exercise. Machine Learning and weighting functions were developed to combine these features into an identification index value for accurate identification and classification of the exercise modes. An algorithm was developed to verify the exercise mode identification. The results show that the proposed method and weighting function can successfully identify the six exercise modes. The identification algorithm was 99.5% accurate. The exercise mode identification of the dumbbell is confirmed. Full article