Tel Aviv University’s Dr. Jeffrey M. Hausdorff Discusses His Mobility And Neurological Research

During our conversation, Professor Hausdorff shared details regarding his background and research.

“After completing my formal education in biomedical engineering, I carried out postdoctoral training in aging at Harvard Medical School and carried out research for a number of years at the Margret & H.A. Rey Institute for Nonlinear Dynamics in Physiology and Medicine in Boston. Under the direction of Professor Ary Goldberger, at the Reylab, we investigated research questions, developed and applied innovative research tools based on nonlinear dynamics and fractal physiology. In 2000, I moved to Israel with my family and joined a clinical and research team in the Movement Disorders Unit (MDU) in the Department of Neurology at the Tel Aviv Sourasky Medical Center. MDU was led by Professor Nir Giladi and it focused on treating and improving the lives of people with Parkinson’s Disease. Professor Giladi and I shared interests in studying gait and patients with Parkinson’s Disease and Nir allowed me to set up my research lab as part of the MDU. A major advantage of this setup was that our research facility was actually integrated into the clinic. We aim to better understand the physiology of a healthy gait. We have also studied the relationship between genetic mutations associated with PD and their impact on gait in healthy people who have an increased risk of developing PD in the future (single neuron firing in patients undergoing surgery for deep brain stimulation.)”

“Early studies of gait focused on biomechanics, muscle strength and movement of the joints,” Hausdorff continued.

“One of the major insights we learned is that among older adults and many patients with neurological disease, like PD, biomechanics play a role, however, cognitive function is also critically important to safe ambulation and fall risk. We have spent much of the past two decades characterizing and fine-tuning our understanding of everyday walking where there are obstacles, surprises and many challenges that require many specific aspects of cognitive function. This led us to use brain imaging techniques like MRI (and functional MRI) as well as functional near infra-red spectroscopy (fNIRS) and EEG, allowing us to probe brain function during walking.”

“The second broad goal of our research is to develop new tools and methods for quantifying gait and mobility,” Hausdorff continued.

“This line of work has emerged as a very exciting field on its own with much interest from the FDA and many others. It has the potential to capture not just what a person can do when he or she is tested in a clinic, but also actual, daily living performance. While capacity is necessary for function, we have shown that there are large gaps between the two. Moreover, function may be more relevant to the patient than capacity. From a clinical trial and drug development perspective, many have suggested that long-term, continuous, 24/7 monitoring could save time and money, potentially shortening the time needed to test the value of a new therapy or drug.”

Hausdorff shared his further studies on gait. “Gait speed and a closely related measure of step length, are two very powerful and sensitive measures of gait. Among older adults, gait speed predicts morbidity, mortality, disability, fall risk, cognitive decline and the development of Dementia. In the past, a biomechanical model of gait was used to estimate step length and gait speed from a sensor worn on the lower back during real-world, daily living studies. This was helpful and insightful, however, the model was not very accurate. With the help of a graduate student, Assaf Zadka, and Professor Neta Rabin, an expert in machine learning at TAU, we developed a new approach to estimating step length and gait speed from a wearable sensor. The machine learning approach is about four times more accurate than the biomechanical model.”

“Another application of machine learning and wearable sensors was in our recent study of freezing of gait (FOG) among people with PD,” Hausdorff added.

“FOG is a mysterious, disabling problem that affects many, but not all people with PD. When it happens, typically in an unpredictable manner, the person reports as if her feet are glued to the ground. This problem markedly impairs function, leads to falls, and, ultimately, confines the person to wheelchair use because of safety concerns. We have shown, for example, the key role of anxiety, depression and certain aspects of cognitive function in this problem. However, in the past, our investigations were limited to snapshot assessments in the clinic or home that do not fully reflect daily living FOG. Combining machine learning, with wearable sensor data, enabled us to quantify this problem in the daily living setting. We found (for the first time) time of day affects therapy treatment and prevention.”

Hausdorff explained the therapeutic focus of his research. “Our third research direction is therapy, building on insights from our earlier studies. We aim to develop interventions that improve gait, reduce fall risk, and enhance cognitive function. For example, after learning that certain cognitive functions are crucial in safe walking, we tested cognitive-enhancing drugs like Ritalin and found promising results. We’ve also used non-invasive brain stimulation to explore brain-gait interactions with exciting findings that show the brain's ability to adapt positively, even with aging or neurological disease.”

“Together with Dr. Brad Manor at Harvard Medical School, we recently received NIH funding to study the effects of six months of home-based, non-invasive brain stimulation on gait, cognitive function, and Dementia risk in older adults,” Hausdorff continued.

“Additionally, with Professor Anat Mirelman, we developed a virtual reality approach that enhances traditional treadmill training. By immersing patients in a VR environment with motor and cognitive challenges, they can improve their walking and thinking skills subconsciously through fun, game-like tasks. In a multi-center, randomized study we led, this VR-based method reduced fall risk by 40% more than conventional treadmill walking. The technology was later transferred to a startup, GaitBetter, which is now used in many Israeli HMOs and gaining traction in the US. The (real-world) results have been even more impressive than in our studies. Patients and therapists are enthusiastic, and the system has significantly reduced falls and related costs. This ‘bench-to-bedside’ success has been deeply gratifying, highlighting the practical impact of our research on the health of older adults. We were also among the first to study the link between cognitive function and gait, which is now widely recognized. Our research shows that the ability to walk while performing another task can predict fall risk five years later.”

When asked about the secret to his longevity, Hausdorff smiled.