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GERONTOLOGY Walking Rhythm Offers Gait-way to Reduce Falls Walking seems simple enough. Just put one foot in front of the other, and soon you are out the door. In fact, walking is not so simple, according to a gerontology research group at Beth Israel Deaconess Medical Center. They are finding complex patterns hidden in an ordinary stroll that reveal changes in the brain and body wrought by aging and disease. Probed by many of the same mathematical tools used to model climate changes and stock market fluctuations, a walk down the hall now offers a way to evaluate the risk of falling in older adults. The findings target gait instability as a potentially reversible contributing factor to the risk of falling, a major public health problem. Through gait analysis, Jeffrey Hausdorff may have found objective measures for some neurological diseases. Photo by Tooli Herman To most people, walking may be the same old heel-toe, heel-toe, left-right-left-right-left-right. But Jeffrey Hausdorff, HMS assistant professor of medicine, has found a veritable ambulatory symphony. Over the past 10 years, he has studied thousands of steps from hundreds of feet. He devised a clever gadget to measure the timing of the heel and toe strike of each stride. The device is flatter than a cushy drugstore shoe insert and feeds data through a short wire to a small monitor worn around the ankle. Wearing these force-sensitive insoles, children as young as 3 have pattered around a track at MIT. The Telltale Footprint Published analyses show that children's sometimes faltering and wavering steps toward maturity are distinctly different from changes in the aging gaits of the elderly. Hausdorff and his colleagues also have found that gait rhythm may provide key objective measures of neurological diseases such as Huntington's, Parkinson's, and Alzheimer's. "In a traditional gait laboratory, each person's 'typical' walking pattern is studied in great detail," Hausdorff said. "People will take a few steps in front of a camera system, and details of those steps will be averaged to generate a picture of the person's gait. We are interested in studying how the gait pattern changes over time, how it varies from one stride to the next over hundreds of strides instead of just a few." Rusty Gaits Gait variability may be used to help predict falls, allowing clinicians to appropriately focus fall prevention education and rehabilitation efforts on people at greatest risk, according to a report in the August Archives of Physical Medicine and Rehabilitation. The prospective cohort study collected strides at three outpatient geriatric clinics from 52 men and women who were 70 or older and lived in the community (not in nursing homes). Although all of them were under the care of geriatric specialists, almost 40 percent reported one or more falls in the one-year follow-up period. Hausdorff found the initial baseline stride time variability of people who later fell was double that of nonfallers. Not surprisingly, stride variability was also significantly correlated with strength, balance, gait speed, and functional status. But these factors did not distinguish fallers from nonfallers as the stride variability analysis so clearly did. PhysioNet Adds Math To Medicine Just as geneticists post the discovery of new genes to GenBank and structural biologists post details of newly elucidated molecular structures to the Protein Data Bank, Jeffrey Hausdorff, HMS assistant professor of medicine at Beth Israel Deaconess, shares his datasets and algorithms at a new NIH-sponsored Web resource called PhysioNet. PhysioNet aims to match clinical and basic data with nonlinear mathematical expertise more commonly found in physics and engineering departments, according to PhysioNet director Ary Goldberger, HMS associate professor of medicine and director of BID's Margret and H.A. Rey Laboratory for Nonlinear Dynamics in Medicine. The resource arose from collaborations and is maintained by Goldberger and his colleagues at Boston University, MIT, and McGill University. Nonlinear mathematical tools are essential to handle major biological questions about how components of the human system integrate and work with each other, Goldberger said. Yet few biomedical researchers have the necessary expertise, and even fewer of the mathematicians and physicists expert in these techniques have access to biomedical data. PhysioNet promotes cross-talk among multiple disciplines. The shared data and algorithms encourage reexamination by other researchers, perhaps from new perspectives, of gait dynamics, heartbeat recordings, and many other physiologic signals. A related paper published in the June Journal of Applied Physiology examines another aspect. Hausdorff and his colleagues teased out the many factors contributing to gait instability and suggest that it may be a reversible by-product of aging. The randomized placebo-controlled six-month exercise trial of 67 patients, mostly women, age 70 or older was conducted in collaboration with Tufts University researchers. In baseline testing, the team found that many factors may contribute to gait instability, including balance, leg strength, and emotional well-being. Physical conditioning lessened gait instability—and likely reduced the risk of falling—suggesting that a steady gait may be in reach for frail elders. "Gait variability measures may provide a sensitive 'assay' of neurodynamics, perhaps revealing increased variability (instability) even when the component systems that contribute to gait variability show more subtle changes," Hausdorff speculated. Pictures in Complexity In his studies, Hausdorff wields nonlinear mathematical tools developed over the past few decades that are used primarily by physicists and mathematicians to understand complex systems such as traffic flow, weather, population dynamics, organizational behavior, shifts in public opinion, stock market fluctuations, epidemics, and cardiological arrhythmias. Hausdorff has been interested in math, engineering, and the application of such tools to medicine and rehabilitation since college. His opportunity came in the lab of BID cardiologist Ary Goldberger, where Hausdorff collected his first gait time series working on another project. There, Hausdorff met statistical physicist C.K. Peng, HMS assistant professor of medicine, then a postdoctoral fellow, who was tinkering with ways to quantify the fractal properties of genes and heart rate rhythm. Now, Hausdorff, working with Peng, Goldberger, and physicists at Boston University, has discovered that gait has fractal qualities. Fractal geometry describes objects or systems that resemble themselves over different scales. A wide variety of natural shapes share this internal look-alike property, including branching trees, coral formations, jagged coastlines, ragged mountain ranges, branching arteries and veins, and the electrical network of the heart. Systems with fractal properties can be quantitatively characterized through a series of algorithms that can be fed into a computer to extract meaningful information from otherwise undetectable changes in a set of data. Earlier, Hausdorff and his colleagues showed that fractal scaling is an intrinsic feature of normal walking that is lost when healthy subjects walk in time to a metronome or if subjects suffer from certain diseases like Huntington's. Recent modeling efforts conducted with collaborators at Boston University suggest that some of the observed changes in fractal properties may be related to the ability of neurons to communicate with one another. But Hausdorff says they are just beginning to crack the code of fractal gait and its implications for health and disease. —Carol Cruzan Morton