This paper describes motion assessment in young adults (YA) and older adults (OA) during the use of an upper limb rehabilitation robot (ULRR). An experimental protocol was proposed to collect kinematic and surface electromyographic (sEMG) data from 20 participants. The protocol included the use of the ULRR along with an interface to execute standardized wrist movements randomly (flexion, extension, radial deviation, and ulnar deviation) at fixed intervals. For the sEMG, representative features were computed, and for the kinematic data, compensatory movements, reaction times, range of movement, and smoothness of movement were estimated. The results showed significant differences in the calculated metrics between YA and OA. The OA group reported 15.5% more compensatory movements and an average of 37 ms increment compared with YA times. Finally, the velocity curves showed more frequency components in OA, which, along with the estimation of the Spectral Arc Length, indicated a smoother movement in the YA group. These outputs can be used to create personalized therapies or to develop a methodology for assessing robotic rehabilitation.

This work presents the development of a soft robotic lung phantom named SOFTLUPHA to characterize and evaluate radiopharmaceuticals on nuclear imaging systems. The proposed design envisages the lungs, the trachea, and two hollow spherical inserts that simulate tumors. The trachea and tumors were manufactured by 3D printing with polylactic acid (PLA) filament and coated with epoxy resin. The lungs were obtained with the medical grade silicone EcoFlex™ 00–33 AF, following a silicone casting process with 3D printed molds. Phantom actuation was obtained through instrumentation and control stages that included an air bomb, an airflow sensor, electronics, and an Arduino Uno microcontroller. The developed phantom was tested for nuclear image acquisition using a single photon emission tomography/computed tomography system. The tests were carried out using known radioactive concentrations of ^99m Tc with the prototype executing a respiratory routine. The results showed that the SOFTLUPHA could be used to evaluate the performance of motion correction algorithms that could impact the quantification processes of lung malignancies.

This work presents the design, manufacturing, and implementation of three uniaxial rotational molding (URM) systems, each corresponding to a mold of the trachea, lung, and tumor lesions, for the production of a soft anthropomorphic phantom. The phantom structures were manufactured using Ecoflex® 00-20 silicone. Each mold was designed in Autodesk Inventor and fabricated via 3D printing, enabling customized and reproducible geometries. A proportional-derivative (PD) controller was implemented in each URM system to regulate rotation speed according to a reference trajectory. Additionally, curing times and silicone volumes were tested to ensure uniform material distribution. The resulting phantom elements demonstrate the potential of controlled rotational molding for producing soft, anatomically realistic models suitable for radiopharmaceutical characterization, medical research, and quality assurance in nuclear imaging systems.

Este trabajo está enfocado en la generación de una base de datos de señales cinemáticas y de electromiografía superficial (EMG), recolectados mediante un exoesqueleto de miembro superior y un brazalete con sensores de EMG. Los sensores son colocados en la extremidad superior derecha de los participantes. El usuario hace uso del exoesqueleto robótico de rehabilitación y de una interfaz gráfica donde le son mostrados con marcadores movimientos específicos, dichos movimientos son flexión, extensión, desviación cubital y desviación radial de la muñeca. Por medio de esta interfaz se almacenan los datos de los "Encoders" del sistema robótico para obtener la información cinemática. El sistema también cuenta con una segunda interfaz donde son mostradas cuatro gráficas correspondientes a los sensores de EMG colocados en la pulsera, donde a partir de esta, se puede adquirir la información, posprocesarla y almacenarla.

This work presents a pilot study to analyze the effect of aging on motor performance of young adults (YAs) and older adults (OAs) through wrist movement assessment, using an upper limb rehabilitation robot (ULRR) in passive mode coupled to a maze-solving task serious video game. The proposed approach considers the use of kinematic metrics, such as ROM, path accuracy, and movement smoothness, as quantitative biomarkers that evidence differences between YAs and OAs. An experimental protocol was conducted with 20 participants: 10 OAs and 10 YAs. Standardized wrist movements corresponding to flexion (F), extension (E), radial deviation (R), and ulnar deviation (U) were assessed at each level of the maze. The kinematic analysis was based on metrics for range of motion (ROM), path accuracy, smoothness, and root-mean-square error (RMSE) in trajectory tracking. The results revealed clear differences between the groups: the YAs achieved a greater ROM and made fewer errors on mean (2.167 errors for YAs compared to 6.000 errors for OAs), and showed a lower RMSE, while the OAs showed greater smoothness in their movements, because the YAs exhibit greater variability and disturbances in movement when correcting and controlling their movements to achieve good performance, reflecting more precise motor control and a greater capacity for error correction during movements with trajectory constraints.