Towards Sonomyography-Based Real-Time Control of Powered Prosthesis Grasp Synergies
Published in IEEE EMBC, 2020
Recommended citation: Bimbraw, K., Fox, E., Weinberg, G. and Hammond, F. L. (2020). "Towards Sonomyography-Based Real-Time Control of Powered Prosthesis Grasp Synergies." 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Montreal, QC, Canada, 2020, pp. 4753-4757. https://ieeexplore.ieee.org/document/9176483
The paper describes the classification of ultrasound information and its mapping onto a soft robotic gripper. In our real-time ultrasound-based control of a soft robotic gripper pipeline, we were able to train a machine learning model to classify 4 hand grasping configurations with an average accuracy percentage of 93%. The paper is a step toward intuitive and robust biosignal-based control methods for robots.
Recommended citation: Bimbraw, K., Fox, E., Weinberg, G. and Hammond, F. L. (2020). “Towards Sonomyography-Based Real-Time Control of Powered Prosthesis Grasp Synergies.” 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Montreal, QC, Canada, 2020, pp. 4753-4757.