Investigating the relationship between morphology, intrinsic body dynamics, information structure generation through coordinated sensory-motor activities and learning.

In collaboration with the Developmental Cognitive Machines Lab. at the University of Tokyo (Prof. Hiroshi Yokoi), we have developed a prosthetic robotic hand inspired by the muscle tendon system of the human hand. The robotic hand has 13 degrees of freedom, and each finger has been equipped with different types of sensors (i.e., flex/bend, angle, and pressure).

In this project, we use the robotic hand to investigate the relationship between morphology, intrinsic body dynamics, generation of information structure through sensorimotor coordinated activity, and learning. We have implemented biologically inspired learning mechanism to allow the robotic hand to explore its own movement capabilities. Moreover, by correlating the sensory input as a result of its motor outputs, the robotic hand can learn to manipulate and grasp objects by itself.

The same robotic hand has been used as a prosthetic device. EMG signals can be used to interface the robot hand non-invasively to a patient and electrical stimulation can be used as a substitute for tactile feedback.

The goal of this project is the development of a prosthetic hand for motor-sensory function substitution which is dynamically coupled to an amputee’s sensor and motor control system. The hand will be based on EMG signals and various types of sensory feedback. By carefully investigating human upper limb dynamics and by taking into account morphological and material properties of assistive devices we hope to develop a scheme by which patients quickly learn to control the hand with less and less cognitive awareness by the user.

The main researchers involved in the project are: Prof. This e-mail address is being protected from spambots. You need JavaScript enabled to view it , Prof. This e-mail address is being protected from spambots. You need JavaScript enabled to view it , Prof. Robert Riener, Dr. Gabriel Gomez, Dr. Alejandro Hernandez, Konstantinos Dermitzakis and Dana Damian.

Student Projects

In this project we have a couple of students projects, ranging from making new classification algorithms to construct novel sensors and hardware mechanisms. Currently we have the following students projects:

1. Design a discrimination algorithm to recognize individual movement of the fingers from electromyographic signals.
2. Develop an upper limb simulation platform for human movement analysis.
3. Design a sensor network for upper limb dynamic movement analysis.
4. Construction of a sensor-exoskeleton for prosthetic applications.
5. Development of novel electrical stimulation devices to provide  sensory feedback in prosthetic applications.
6. Development of an embedded system for control of a novel prosthetic hand.

for more information please contact:

Dr. Alejandro Hernandez ( This e-mail address is being protected from spambots. You need JavaScript enabled to view it )

Stay tuned :)