The Hand Prosthesis That Learns from the User

Explore a groundbreaking machine learning approach to hand prosthesis control in this 34-minute conference talk. Delve into the complexities of modern mechatronic hand prostheses and the challenges of controlling multiple degrees of freedom. Discover how a prosthesis can learn from its user, enhancing manipulation, interaction, and gesticulation capabilities. Gain insights into current prosthetic technologies, problem-solving techniques, and practical demonstrations. Learn about the inner workings of this innovative system and its potential impact on arm and leg amputees. Address critical aspects such as stress management, cost considerations, user experience, and proprioceptive feedback in prosthetic development.

Introduction
Current prosthesis
The problem
Demonstration
How it works
QA
Stress
Arm amputation
Leg amputation
Cost
User experience
proprioceptive feedback