Introducing the latest prototype of our prosthetic hand with its innovative features:


Muscle Pattern Recognition

By using machine learning, our hand is able to recognize your muscle patterns to intuitively allow users to have finer control of their prosthesis. In addition to hand open and a power grasp, our pattern recognition technology allows users to pinch, 3-finger grasp, and grasp a tool or a key by performing the same movements they did prior to the amputation.

The signal travels from rubber finger tip to amputee

Sensory Feedback

This feature is what makes us stand at the forefront of our industry. No commercial prosthesis has ever been able to relay the feeling of touch back to a person with an amputation. 


This is the open-source myoelectric prosthetic hand, Tact.

This project was developed by Patrick Slade through the Bretl Research Lab at UIUC. It consists of a myoelectric prosthetic hand design that can be easily rapid prototyped with 3D printers and common mechanical components. This allows it to be produced as a complete myoelectric system for less than $250.

For complete parts lists and assembly instructions see the assembly pdf file on this link.

P. Slade, A. Akhtar, M. Nguyen, T. Bretl. Tact: design and performance of an open-source, affordable, myoelectric prosthetic hand. International Conference on Robotics and Automation, Seattle, WA, 2015.

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