Neuromuscular Control Colloquium (Winter and Summer semesters)
Our Neuromuscular Control Colloquium will be used to start research projects in the field of Neuromuscular control. We will meet as a group to plan, conduct, analyze and write up our work together as a group. The goal is to publish papers together with all members over the period of a few terms. Interested Undergraduate and Masters students are welcome to join. Please contact Prof. Franklin by email for further information.
A Masters level course in which we discuss human motor control from a robotics perspective, specifically focusing on issues such as neuromechanics (muscle, joint and limb stiffness), prediction (predictive feedforward control), motion planning (optimal control and cost functions), coordinate transformations, and integration and control of sensory feedback. Finally we will discuss applications in robotics and rehabilitation.
Neuromuscular Control and Learning
This module covers current advanced topics in neuromuscular control and learning with a special relevance to sports, exercise and health. This class will cover the neural, physiological and computational basis of human learning and adaptation.The questions asked in the course is how do we learn new tasks or skills, and how can we use this information to improve learning.
Peripheral and Neuromuscular Mechanisms
A Bachelors level course introducing the peripheral and central physiology involved in the neuromuscular system of the human body.
Masters level course introducing programming (Matlab) and simple analysis of physiological measures.
Biomechanics, Human Movement and Neuromechanical Control
Masters level course covering basic biomechanics, human movement and neuromechanics.
Special course on Computational Neuroscience offered for the Elite Masters in Neuroengineering.
Sensory Physiology: Sensation and Perception
A Bachelors level course introducing sensory physiology. We cover vision, hearing, vestibular system and balance, touch, pain, proprioception, and general sensory processing involved in perception.
Computational Principles of Sensorimotor Control
A Bachelors level course introducing computational principles involed in sensorimotor control. We first discuss the major reasons why motor control is a difficult problem and then computational approaches that the brain might use to solve these problems. We go through Bayesian Decision Theory, Forward Models, State Estimation, Optimal Control Theory, Learning and Impedance Control.
This class focuses on the experimental techniques used in neuromechanics research to investigate the properties of the neuromuscular system. Where feasible the methods will be taught hand-on in a laboratory setting