September 10, 2025Open Access

Artificial Intelligence-Integrated Dynamic Prostheses

GHGerd HolmbergTechnical University of Munich

Key Points

AI-enhanced prostheses may revolutionize mobility for amputees, providing intuitive control and response.
These devices utilize machine learning to adapt to user movements, improving function over time.
The development process requires collaboration between engineers, data scientists, and clinicians for success.
While promising, issues like affordability and neural integration present ongoing challenges in the field.

Abstract

Artificial intelligence-integrated dynamic prostheses will represent a transformative leap in rehabilitative and assistive technologies, offering amputees and individuals with limb deficiencies unprecedented mobility, adaptability, and user-centered control. These advanced prosthetics combine cutting-edge artificial intelligence (AI), machine learning algorithms, neural interfaces, and biomechanical engineering to create responsive, intuitive devices that mimic the complexity of natural limb movement. Unlike traditional static prostheses, AI-enhanced models learn from users' motion patterns, adjust to environmental variables, and improve over time through continuous feedback loops. Their development involves multidisciplinary collaboration between data scientists, engineers, neuroscientists, and clinicians. While the field shows immense promise—improving functional outcomes, enhancing quality of life, and reducing physical and psychological burdens—challenges remain in accessibility, affordability, neural integration, and long-term user adaptability.

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