Artificial Intelligence (AI) is rapidly reshaping the field of prosthetics and orthotics by enhancing device design, control strategies, and clinical decision-making. Through advanced machine learning, neural networks, and pattern recognition algorithms, AI enables prosthetic and orthotic systems to interpret bio signals, predict user intent, and adapt in real time to changing environments. These innovations contribute to more natural limb control, improved gait efficiency, and personalized rehabilitation strategies. Moreover, AI-driven computer vision and gait analysis tools support clinicians in patient assessment, socket or orthosis design, and outcome prediction, thereby improving the precision and efficiency of care. Despite these opportunities, significant challenges remain. Data scarcity in amputee populations, high device costs, variability in performance across users, and limited large-scale clinical validation hinder widespread implementation. Ethical considerations such as data privacy, algorithmic transparency, and equitable access further complicate integration into routine clinical practice. Nevertheless, ongoing research into multimodal sensing, brain-computer interfaces, adaptive orthotic control, and AI-assisted digital workflows shows great promise for advancing patient cantered solutions. This paper discusses the challenges, opportunities, and clinical implications of AI in prosthetics and orthotics, emphasizing its potential to transform rehabilitation practices and redefine standards of mobility and independence in the near future.
Minakshi Behera (Sat,) studied this question.