Researchers at Florida Atlantic University (FAU) have found that wearable foot sensors and a 3D depth camera can provide accurate gait analysis in clinical settings, offering an alternative to traditional, expensive equipment. The study was conducted by the College of Engineering and Computer Science and the Sensing Institute (I-SENSE) at FAU.
Gait analysis is used to assess walking patterns, which can help detect fall risk, monitor rehabilitation progress, and identify early signs of neurodegenerative diseases such as Parkinson’s and Alzheimer’s. Traditionally, electronic walkways like the Zeno Walkway are considered the standard for this type of assessment but are limited by their high cost and lack of portability.
To address these limitations, FAU researchers conducted what they describe as the first direct comparison of three sensing technologies: APDM wearable inertial measurement units (IMUs), Microsoft’s Azure Kinect depth camera, and the Zeno Walkway. The Azure Kinect captures 3D data, color images, and body movements for motion tracking.
“This is the first time these three technologies have been directly compared side by side in the same clinical setting,” said Behnaz Ghoraani, Ph.D., senior author and associate professor at FAU. “We wanted to answer a question the field has been asking for a long time: Can more accessible tools like wearables and markerless cameras reliably match the clinical standard for detailed gait analysis? The answer is yes – especially when it comes to foot-mounted sensors and the Azure Kinect.”
The study involved 20 adults aged 52 to 82 who performed both single-task and dual-task walking trials. All three systems recorded each participant’s gait simultaneously using a custom-built hardware platform developed by FAU researchers to synchronize data collection.
Eleven different gait markers were evaluated, including walking speed, step frequency, stride time, support phases, and swing time. These metrics were analyzed statistically to compare each device with results from the Zeno Walkway.
The findings showed that foot-mounted sensors closely matched measurements from the walkway across nearly all markers. The Azure Kinect also demonstrated strong accuracy even in busy clinic environments where multiple people were present in its field of view. In contrast, lumbar-mounted sensors commonly used in wearable studies were less accurate for detailed gait events.
“By testing these tools in a realistic clinical environment with all the unpredictable visual noise that comes with it, we’ve made great strides toward validating them for everyday use,” said Ghoraani. “This isn’t just a lab experiment. These technologies are ready to meet real-world demands.”
The study is also noted as being the first to benchmark Azure Kinect against an electronic walkway for micro-temporal gait markers.
“The implications of this research are far-reaching,” said Stella Batalama, Ph.D., dean of FAU’s College of Engineering and Computer Science. “As health care systems increasingly embrace telehealth and remote monitoring, scalable technologies like wearable foot sensors and depth cameras are emerging as powerful tools. They enable clinicians to track mobility, detect early signs of functional decline, and tailor interventions – without the need for costly, space-intensive equipment.”
Other contributors included doctoral students Marjan Nassajpour (first author) and Mahmoud Seifallahi from FAU; Amie Rosenfeld; Magdalena I. Tolea; and James E. Galvin from University of Miami Miller School of Medicine.
The research received funding from grants awarded by the National Science Foundation to Ghoraani and by the National Institutes of Health to Galvin.
