Could the way we walk give clues to our thoughts or feelings?
Two University of Miami researchers are exploring this question through a project called MindStep, where participants answer survey questions about their mental health and then complete different intellectual tasks while walking, as specialized cameras record and measure their walking patterns.
"The way we walk may tell us more about our mental health than we realize," said Moataz Eltoukhy, a professor of kinesiology and sport sciences in the School of Education and Human Development who has expertise in gait analysis and motion capture. "Changes in mood, stress or mental well-being can sometimes be reflected in subtle changes in the way a person moves."
Their work was spurred by the mental health crisis permeating the United States and the world, with a burden especially prevalent among teens between the ages of 15 and 19, according to the Institute for Health Metrics and Evaluation. That is why the researchers chose to focus on college students, and they are now analyzing data to see whether a student's own thoughts can affect the way they walk.
But researchers already have a hunch that they do.
Last year, through a University Laboratory of Integrative Science (U-LINK) grant, Eltoukhy and Jennifer Britton, an associate professor of psychology in the College of Arts and Sciences, began working together to investigate whether two of the most common mental health conditions—depression and anxiety—can influence the way college students walk and whether increased stress can alter the way they walk during certain times of the year. Those participating in the study did so voluntarily and visited the lab four times over six weeks to conduct brief gait analysis sessions while also completing surveys. Researchers said about 25 percent of these participants reported symptoms of anxiety or depression.
"We wanted to see how gait changes with time and whether or not we could track symptoms with individuals," Britton said.
In two studies with about 95 participants, early results from one study suggest that those who reported symptoms of depression tended to change their stride length, or the distance between steps, more often when engaged in more difficult working memory tasks. They also discovered that college students who were more likely to suppress their emotions showed differences in their walking patterns when researchers asked them to name things that made them happy or frustrated.
This year, with an additional 50 student participants, they are still focused on analyzing students' walking patterns, Britton explained. Yet Britton and Eltoukhy are also interested in learning how students perform additional tasks while walking, such as using a phone and ignoring distracting information. The researchers are also changing the environment.
"We'll start by monitoring them inside the lab, but then we will also monitor them outside of the lab," she said. "We are also trying to figure out if there are walking patterns that correspond with changes in anxiety and depression."
Their ability to monitor participants walking inside and outside of the lab is possible by AI and new motion-capture technology. While traditional movement analysis techniques, known as marker-based motion capture, require the use of multiple specialized cameras and reflective markers on the participant's body for their movements to be measured, Eltoukhy and his team have developed a much less intrusive AI-based tool that eliminates the need for markers and specialized cameras.
Their new system allows a single tablet camera to track movement and provide various biomechanical measures, such as gait speed, step length and stride length with a level of accuracy comparable to the industry gold-standard, marker-based motion capture systems, Eltoukhy said. The team is comparing its results with those from an established multicamera system, but Eltoukhy hopes to validate the new technology through this study. Then, it will allow them to observe participants walking outside of the lab in more natural settings, such as clinics and college campuses.
"Our goal is to use artificial intelligence to recognize those changes in walking patterns in an objective and noninvasive way," Eltoukhy added. "So instead of relying only on what someone tells us about how they are feeling at a particular moment, we are exploring whether movement can provide an additional piece of information about their mental well-being."
Ultimately, the researchers hope that changes in gait could provide another signal that someone may be experiencing fluctuations in their mental health. For example, Britton said, with anxiety and depression today, some of the core features that often lead to a diagnosis include feelings reported by the individual and changes in sleep or appetite, but there is no mention about movement.
"A lot of people assume that mental health is just about how you think, but there are other behavioral measures that may be indicative of this," said Britton, an affective neuroscientist. "If I am tired, I've noticed that I walk a little different, and if I'm happy, my gait changes. We are trying to figure out if this is another variable to assess disorders like anxiety and depression."
If researchers find a meaningful relationship, students' walking patterns could provide another signal that additional support may be helpful.
"If you have a mental health disorder, there is more risk for academic issues and social issues, so we want to help students who are at risk of being in those situations to be more successful," she added.
Eltoukhy agreed and said the results could end up helping populations beyond the college campus.
"It takes time for a person to realize they are experiencing a decline in their mental health, and sometimes that can be too late," Eltoukhy said. "Hopefully, we can be more proactive. If this research tool proves accurate, we could continuously monitor walking patterns to help identify meaningful changes sooner and create an opportunity for earlier interventions."
