STEM-Based Innovations in AI-Enabled Prosthetics: Toward Smarter Biomechanical Systems
Palabras clave:
artificial intelligence, smart prosthetics, biomechanics, machine learning, sensor integration, brain-computer interface, electromyography, neural networks, haptic feedback, STEM innovations, adaptive systems, biomedical engineering, human-machine interaction, gait optimization, cognitive-machine synergyResumen
Advancements in science, technology, engineering, and mathematics (STEM) have catalyzed transformative innovations in the field of prosthetics, particularly with the integration of artificial intelligence (AI). AI-enabled prosthetic systems are emerging as intelligent biomechanical solutions that offer enhanced mobility, adaptability, and user-centered control for individuals with limb loss. These smart prosthetics utilize machine learning algorithms, sensor integration, and real-time data processing to mimic natural limb movements, providing seamless interaction between the user and the device. Innovations such as brain-computer interfaces (BCIs), electromyographic (EMG) signal interpretation, and adaptive neural networks enable these systems to learn from user behavior and environmental contexts, ensuring more intuitive and precise movements.
