Quantum

From Mind to Movement

ENGINEERING PROFESSOR CARLO DE LUCA SEEKS TO UNDERSTAND THE NEURO-MUSCULAR CONNECTION

By Hope Green

ENGINEERING PROFESSOR CARLO DE LUCA Whether it’s a pair of hands subtly interpreting Chopin on a piano keyboard or the apparently simple act of walking, every movement of the body is controlled by distinct patterns of electronic pulses decoded by individual muscle fibers, thousands per second. Interpreting these pulsating signals transmitted from brain to muscle is one of the primary goals of Professor Carlo De Luca, founding director of Boston University’s NeuroMuscular Research Center (NMRC). The benefits are practical: stroke and spinal cord–injury victims, for example, could one day benefit from the research.

Until recently the technology for signal processing has been far too cumbersome to be useful in clinical settings outside the research laboratory. That could soon change. The NMRC recently received a $3.2 million grant from the National Institutes of Health’s National Center for Medical Rehabilitation Research to design and test exponentially faster, more accurate investigations of human motor control. Meanwhile, technology advances are shrinking the amount of equipment needed, meaning that such work could eventually be done in outpatient treatment.

De Luca, principal investigator for the team, says the new technology will make it possible to explore “a whole world of physiological questions we haven’t been able to touch” using current methods. Among the most critical of these questions is how aging affects the way our central nervous system controls our muscles. De Luca and co-principal investigator Zeynep Erim, a research assistant professor at NMRC, have gathered preliminary data showing that with age, the code from the brain to the muscles changes and seems to become less effective at generating force.

“We want to take that one step further,” De Luca says, “and look at whether different kinds of exercise can make the workings of the central nervous system, with respect to controlling muscle fiber, revert to its youthful pattern.”

Another priority for the team is to understand the degree to which signals from the brain and spinal cord are disrupted by strokes and diseases including Parkinson’s, cerebral palsy, and multiple sclerosis. Currently clinicians have no way to quantify nervous system disorders. “If something goes wrong with the liver, you can draw blood and do an enzyme test,” De Luca says. “If something goes wrong with the heart, you can measure blood pressure and take an EKG. But for central nervous system diseases, there are no technologies that allow the clinician to measure the degree of the injury objectively. Our technology will change that.”

A third clinical study will investigate control signals sent to the larynx that affect breathing and speech. Clinical trials of the signal-decomposition technology will begin within a few years. Responsible for the sophisticated software design is Associate Professor Hamid Nawab, associate chairman of undergraduate studies at ENG’s Electrical and Computer Engineering Department.

On the surface, De Luca’s method for measuring electric pulses in muscle has not changed for twenty years: a fine needle containing four tiny wire sensors is inserted into a muscle fiber and linked to a computer. What’s different is the computer setup. The current system was considered an exciting breakthrough when it was designed in the early 1980s, but it is slow and unreliable, and involves a six-foot-tall mechanical assembly and two personal computers.

“It has been a useful tool in the research environment and has helped us answer some important physiological questions,” De Luca says, “but it is useless outside the laboratory. It can take up to two months to analyze a muscle contraction of fifteen seconds. We’re going to be developing a system that works with a new concept of artificial intelligence, called IPUS, which Professor Nawab has been investigating for some time.”

With the assistance of Donald Gilmore, senior design engineer at NMRC, the scientists will shrink the equipment to an 8-by-10-inch box and a laptop computer. The new system will enable researchers to complete calculations 100 times faster, bringing their work into a clinical setting sooner.

The five-year renewable Bioengineering Research Partnership Grant from the NIH supports a multidisciplinary team of scientists at BU, New York Medical College, and the Free University of Brussels. It will also fund research by five BU graduate students and more than a dozen undergraduates.

The NIH’s initiative to fund projects of this nature — teaming up experts in fields as diverse as physiology, computer science, and engineering — reflects “a major change in philosophy” for the government agency, says De Luca. “This is the first time it has provided awards of this magnitude, with this potential impact, to go directly to the bioengineering community.”


From Mind to Movement ENGINEERING PROFESSOR CARLO DE LUCA SEEKS TO UNDERSTAND THE NEURO-MUSCULAR CONNECTION By Hope Green Whether it’s a pair of hands subtly interpreting Chopin on a piano keyboard or the apparently simple act of walking, every movement of the body is controlled by distinct patterns of electronic pulses decoded by individual muscle fibers, thousands per second. Interpreting these pulsating signals transmitted from brain to muscle is one of the primary goals of Professor Carlo De Luca, founding director of Boston University’s NeuroMuscular Research Center (NMRC). The benefits are practical: stroke and spinal cord–injury victims, for example, could one day benefit from the research. Until recently the technology for signal processing has been far too cumbersome to be useful in clinical settings outside the research laboratory. That could soon change. The NMRC recently received a $3.2 million grant from the National Institutes of Health’s National Center for Medical Rehabilitation Research to design and test exponentially faster, more accurate investigations of human motor control. Meanwhile, technology advances are shrinking the amount of equipment needed, meaning that such work could eventually be done in outpatient treatment. De Luca, principal investigator for the team, says the new technology will make it possible to explore “a whole world of physiological questions we haven’t been able to touch” using current methods. Among the most critical of these questions is how aging affects the way our central nervous system controls our muscles. De Luca and co-principal investigator Zeynep Erim, a research assistant professor at NMRC, have gathered preliminary data showing that with age, the code from the brain to the muscles changes and seems to become less effective at generating force. “We want to take that one step further,” De Luca says, “and look at whether different kinds of exercise can make the workings of the central nervous system, with respect to controlling muscle fiber, revert to its youthful pattern.” Another priority for the team is to understand the degree to which signals from the brain and spinal cord are disrupted by strokes and diseases including Parkinson’s, cerebral palsy, and multiple sclerosis. Currently clinicians have no way to quantify nervous system disorders. “If something goes wrong with the liver, you can draw blood and do an enzyme test,” De Luca says. “If something goes wrong with the heart, you can measure blood pressure and take an EKG. But for central nervous system diseases, there are no technologies that allow the clinician to measure the degree of the injury objectively. Our technology will change that.” A third clinical study will investigate control signals sent to the larynx that affect breathing and speech. Clinical trials of the signal-decomposition technology will begin within a few years. Responsible for the sophisticated software design is Associate Professor Hamid Nawab, associate chairman of undergraduate studies at ENG’s Electrical and Computer Engineering Department. On the surface, De Luca’s method for measuring electric pulses in muscle has not changed for twenty years: a fine needle containing four tiny wire sensors is inserted into a muscle fiber and linked to a computer. What’s different is the computer setup. The current system was considered an exciting breakthrough when it was designed in the early 1980s, but it is slow and unreliable, and involves a six-foot-tall mechanical assembly and two personal computers. “It has been a useful tool in the research environment and has helped us answer some important physiological questions,” De Luca says, “but it is useless outside the laboratory. It can take up to two months to analyze a muscle contraction of fifteen seconds. We’re going to be developing a system that works with a new concept of artificial intelligence, called IPUS, which Professor Nawab has been investigating for some time.” With the assistance of Donald Gilmore, senior design engineer at NMRC, the scientists will shrink the equipment to an 8-by-10-inch box and a laptop computer. The new system will enable researchers to complete calculations 100 times faster, bringing their work into a clinical setting sooner. The five-year renewable Bioengineering Research Partnership Grant from the NIH supports a multidisciplinary team of scientists at BU, New York Medical College, and the Free University of Brussels. It will also fund research by five BU graduate students and more than a dozen undergraduates. The NIH’s initiative to fund projects of this nature — teaming up experts in fields as diverse as physiology, computer science, and engineering — reflects “a major change in philosophy” for the government agency, says De Luca. “This is the first time it has provided awards of this magnitude, with this potential impact, to go directly to the bioengineering community.”
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