There are different alternatives when selecting removable prostheses for below the knee amputated patients. The designs of these prostheses vary according to their different functions. These prostheses designs can be classified into Energy Storing and Return (ESAR), Controlled Energy Storing and Return (CESR), active, and hybrid. This paper aims to identify the state of the art related to the design of these prostheses of which ESAR prostheses are grouped into five types, and active and CESR are categorized into four groups. Regarding patent analysis, 324 were analyzed over the last six years. For scientific communications, a bibliometric analysis was performed using 104 scientific reports from the Web of Science in the same period. The results show a tendency of ESAR prostheses designs for patents (68%) and active prostheses designs for scientific documentation (40%).

Medical simulators have revolutionized clinical training, particularly in teaching skills such as cardiac auscultation. This review synthesizes recent advances in the technological design and implementation of cardiac simulators for medical education, alongside scientometric and patentometric analyses. The focus is on innovations enhancing efficacy, safety, and accessibility. Analyses included 69 patents published over the past five years, sourced from Google Patents, Patentscope, Espacenet, and The Lens. A bibliometric analysis was performed using 52 scientific reports from PubMed, ScienceDirect, and The Lens within the same timeframe. Key findings indicate an 8% increase in AI-integrated cardiac auscultation devices compared to conventional equipment. Furthermore, 85% of the studies reported compliance with applicable regulations of at least 90%, reflecting improved regulatory alignment. This analysis provides a foundation for future research and the development of more accurate and accessible educational tools for cardiac auscultation training.

This paper presents a hybrid methodology for the creation of educational mobile robots, combining the efforts of developers in design, construction, and instrumentation with the use of “Vibe Coding” as an alternative programming approach. To achieve this objective, the methodology integrates electronics and algorithmic thinking to enable adaptive behavior across three operating modes for robotics competitions. The mobile robot features a compact and modular architecture (430 g, 22 cm length × 14 cm width) with support components manufactured using 3D printing. Instrumentation included an Arduino Uno^® development board, a Syb-170^® proto shield, a buzzer, an HC-SR04^® ultrasonic sensor, an SG90 RC^® servomotor, a SSD1315 display, three TCRT5000^® reflective optical sensors, two DC motors with integrated 48:1 gearboxes, an L298N motor driver, and two 18650^® rechargeable lithium-ion batteries. Programming and algorithmic implementation were carried out using Vibe Coding, leveraging its intuitive environment to accelerate the development of three independent operating modes: (1) line follower on a racetrack, (2) obstacle avoidance with various objects, and (3) Bluetooth control via the free MIT Application Inventor. The mobile robot successfully demonstrated all three tasks, validating its suitability for educational and competitive purposes. Furthermore, its architecture supports AI-assisted decision-making through Vibe Coding, enabling dynamic responses to environmental disturbances. The multimodal configuration enhances navigation by correcting trajectory deviations, thereby improving robustness, adaptability, and overall functionality.