Research

Intuitive control of prosthetic hands

• Intuitive control of prosthetic hands is an essential need for individuals using these devices. Meanwhile, the current control strategies use machine learning algorithms that convert the EMG activity recorded from the residual limb into different hand gestures in the prosthetic hand. However, biological hands are capable of continuous force and joint angle control. Therefore, we are examining the possibility of extracting more information for more continuous control in the prosthetic hand.

Sensory restoration for prosthetic hands

• Receiving sensory feedback during interaction with the environment is essential for successful motor implementation. However, the individuals who are using prosthetic hands do not receive sensory feedback from the device. This can create several issues, such as a lack of sense of embodiment over the prosthetic, lack of fine-tuned movement, and high cognitive load. Therefore, we are working on developing different invasive and non-invasive methods of sensory feedback and neuromorphic encoding to restore sensation.