Trampoline Stiffness Estimation by Using Robotic System for Quantitative Evaluation of Jumping Exercises.

Trampolines are recognized as a valuable tool in exercise and rehabilitation due to their unique properties like elasticity, rebound force, low-impact exercise, and enhancement of posture, balance, and cardiopulmonary function. To quantitatively assess the effects of trampoline exercises, it is essential to estimate factors such as stiffness, elements influencing jump dynamics, and user safety. Previous studies assessing trampoline characteristics had limitations in performing repetitive experiments at various locations on the trampoline. Therefore, this research introduces a robotic system equipped with foot-shaped jigs to evaluate trampoline stiffness and quantitatively measure exercise effects. This system, through automated, repetitive movements at various locations on the trampoline, accurately measures the elastic coefficient and vertical forces. The robot maneuvers based on the coordinates of the trampoline, as determined by its torque and position sensors. The force sensor measures data related to the force exerted, along with the vertical force data at X, Y, and Z coordinates. The model's accuracy was evaluated using linear regression based on Hooke's Law, with Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient Squared (R-squared) metrics. In the analysis including only the distance between X and the foot-shaped jigs, the average MAE, RMSE, and R-squared values were 17.9702, 21.7226, and 0.9840, respectively. Notably, expanding the model to include distances in X, Y, and between the foot-shaped jigs resulted in a decrease in MAE to 15.7347, RMSE to 18.8226, and an increase in R-squared to 0.9854. The integrated model, including distances in X, Y, and between the foot-shaped jigs, showed improved predictive capability with lower MAE and RMSE and higher R-squared, indicating its effectiveness in more accurately predicting trampoline dynamics, vital in fitness and rehabilitation fields.

Synthesis and Charge Transport of Polymer Nanocomposite of Polyaniline: Polystyrene Sulfonate.

We demonstrate the preparation of water-dispersible polyaniline:polystyrene sulfonate (PANI:PSS), which was doped with camphorsulfonic acid (CSA) and co-doped with poly (4-styrenesulfonic acid) (PSS). The proper formation of the PANI and PANI:PSS was verified by FTIR measurements. The synthesized samples were further characterized via UV-vis spectroscopy. The intensive study on the current density (J)-voltage (V) characteristics within the temperature range (143-303 K) of the synthesized sample was performed systematically. The electrical study shows that the doping of PANI with CSA as a dopant and PSS as a co-dopant significantly improves the overall semi-conducting property of PANI. The detailed analysis of the current density (J)-voltage (V) curve at various temperatures reveals the electrical conduction behavior, which follows the trap-dependent space-charge limited conduction (SCLC) mechanism.

Vision-based fluid-type tactile sensor for measurements on biological tissues.

Hardness, dimensions, and location of biological tissues are important parameters for electronic palpation protocols with standardized performance. This study presents a novel fluid-type tactile sensor able to measure size and depth of heterogeneous substances in elastic bodies. The new sensor is very simple and can be easily fabricated. It consists of an image sensor, LED lights, and a touchpad filled with translucent water. The intensity field of the light traveling in the touchpad is analyzed to estimate the touchpad shape which conforms to the shape of an object in contact. The use of the new sensor for measuring size and depth of heterogeneous substances inside elastic bodies as well as hardness of elastic bodies is illustrated. Results obtained for breast cancer dummies demonstrate the effectiveness of the proposed approach.