Mapping Body Motion:

Ted Raphan Uses Sophisticated Computer Models to Study Foot, Head and Eye Movement

Despite the old axiom, walking is much more complicated than simply putting one foot in front of the other. In fact, Distinguished Professor Theodore Raphan explains that if stride length, stepping frequency, velocity, and “toe clearance” are not in proper coordination, everything can go awry.

“Parkinson’s patients have problems with this toe clearance,” explains Raphan, a professor in the Ph.D. programs in computer science and psychology. “They hit their toe into the ground because they can’t control that toe lift, which is very critical for walking. It’s been known for a long time that Parkinson’s patients festinate because they can’t generate the stride length necessary to do natural walking. But now we’re beginning to understand why, which leads to: How can we train them to appropriately move their foot so that they can walk better?”

That question is but one that Raphan is hoping can be solved by applying engineering and mathematical concepts from adaptive control theory to the body’s physiological systems.
He started out using the theory to develop mathematical models that map out the eye’s movements and reflexes as a doctoral student and then as a postdoctoral fellow at Mt. Sinai School of Medicine with Dr. Bernard Cohen, the Dr. Morris B. Bender Professor of Neurology. Years later, at Brooklyn College where he now heads the Institute for Neural and Intelligent Systems, he discovered that similar formulae could be applied to understanding the trajectory of the foot’s movements during walking.

“Nobody had made that connection before, and it adds a kind of uniformity to the mechanisms that control movement,” he says.

Raphan got his undergraduate and master’s degrees from City College and earned his Ph.D. in electrical engineering from The Graduate Center in 1976. He is currently working on four grants, all of which deal with understanding different parts of the interrelated concepts of locomotion, eye movement, and the brain’s ability to adapt when people suffer from neurological diseases that interfere with either.

“Although they’re separate, they’re all intertwined and one helps the other,” he says of his projects, which are funded by the National Institutes of Health, the National Eye Institute and The National Institutes of Deafness and other Communicative Disorders. “They’re very symbiotic.”

As part of his research, he straps a patient with tiny light- emitting diodes — or LEDs—on the leg, foot, chest, back and head and has the patient walk. Camera units sense the position of every LED during walking, allowing Raphan to reconstruct the movement of the foot, body and head on a computer in real time. In a project funded by the NSF and a CUNY collaborative grant, he is now studying how to use the models of foot, head and eye movements to control the movement of robots that are hooked up to computers. By manipulating certain variables in the formulae—like toe clearance or velocity, for example—he expects to be able to better understand what goes wrong in the walking patterns of Parkinson’s patients and others with balance deficits. He also plans to use the
data to improve the gaze of robots during locomotion, which would lead to a better understanding of how humans maintain their gaze while they are walking.

“The more we understand about the motion of every part of the body, the better we’ll be able to relate these parameters to deficient gait,” he explains. “When you watch these robots walk, you can relate it back to what’s going on in humans with deficient gait and you can figure out what you can do mathematically to improve their gait.”

His studies of the vestibulocular reflex—an eye movement that stabilizes images on the retina during head movement—have proven the brain’s ability to adapt its processes during moments of imbalance or instability. He’s now trying to figure out how that knowledge can be applied to helping Parkinson’s and other locomotively challenged patients.

“What we’re learning from a lot of these adaptive studies is how you can skew that misadaptation process,” he says. “What can you do to help speed up the adaptation process? Because neurological diseases in general are so intractable, we’re hoping that what we’ve learned about adaptive processes and learning algorithms, over the years, will help us to alleviate the suffering of people with neuromuscular diseases.”

Raphan also has a grant pending from NIH to study motion sickness, which is believed to be due to a mismatch between signals processed by the visual and vestibular systems. Motion sickness is also likely caused by an orientation disparity in a person’s “velocity storage,” a brain mechanism that receives information from visual, acceleration and orientation sensors and combines them to determine how best we should move in order to maintain stability. Raphan and his Mt. Sinai post-doctoral advisor, Cohen, discovered velocity storage in 1977.
“It’s when you read in a car that makes you most sick because your head is moving,” he explains. “The vestibular system tells you that you are moving but your visual system says that you are not. This conflict causes the motion sickness. It gives the brain disparate signals.”

Raphan got his first grant in 1979 and has received continuous support from the NIH since arriving at Brooklyn College in 1982. He says he feels fortunate to have his entire body of research build on what he first embarked on as a doctoral student. He was in the engineering program studying adaptive control theory and it was his Ph.D. advisor who suggested that he apply some of the techniques he was developing to physiological systems.

“My research started out in a very simple way. It has now grown and has tentacles and important implications that could help people in a clinical setting,” he says. “That to me is the most fascinating part of my work. It’s very rare after 30 years of doing research that you start to see clinical applications for your work. The fact that I was able to follow a single thread and finally build a model for balance and locomotion, over so many years, and the initial model still has validity, is very exciting. Papers that I published in 1979 are still being referenced in 2006. That, to me, is very satisfying.”