New Device Measures Walking Speed using Wireless Signals

A team of researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a device that can measure the walking speed of multiple people with 95 to 99 percent accuracy using wireless signals.

We have long known that blood pressure, breathing, body temperature and pulse provide an important window into the complexities of human health. But a growing body of research suggests that tracking how fast you walk could be a better predictor of health issues like cognitive decline, falls, and even certain cardiac or pulmonary diseases.

Unfortunately, it’s hard to accurately monitor walking speed in a way that’s both continuous and unobtrusive. Professor Dina Katabi’s group at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has been working on the problem, and believes that the answer is to do this wirelessly.

The team introduced “WiGait,” a device that wirelessly measures walking speeds of multiple people with 95 to 99 percent accuracy. The size of a small painting, the device can be placed on the wall of a person’s house and its signals emit roughly one-hundredth the amount of radiation of a standard cellphone. It builds on Katabi’s previous work on WiTrack, which analyzes wireless signals reflected off people’s bodies to measure a range of behaviors from breathing and falling to specific emotions.

WiGait uses wireless signals to continuously measure a person's walking speed, which may help predict cognitive and motor function decline, and even certain cardiac or pulmonary diseases.  

WiGait is also 85% to 99% accurate at measuring a person’s stride length, which could allow researchers to better understand conditions like Parkinson’s disease that are characterized by reduced step size. The team will present their paper in May at ACM’s CHI Conference on Human Factors in Computing Systems in Colorado.  

Today, walking speed is measured by physical therapists or clinicians using a stopwatch. Wearables like FitBit can only roughly estimate speed based on step count, and GPS-enabled smartphones are similarly inaccurate and can’t work indoors. Cameras are intrusive and can only monitor one room. VICON motion tracking is the only method that’s comparably accurate to WiGate, but it is not widely available to be practical for monitoring day-to-day health changes.

Meanwhile, WiGait measures walking speed with a high level of granularity, without requiring that the person wear or carry a sensor. It does so by analyzing the surrounding wireless signals and their reflections off a person’s body. The CSAIL team’s algorithms can also distinguish walking from other movements, such as cleaning the kitchen or brushing one's teeth.

Katabi says the device could help reveal a wealth of important health information, particularly for the elderly. A change in walking speed, for example, could mean that the person has suffered an injury or is at an increased risk of falling. The system's feedback could even help the person determine if they should move to a different environment such as an assisted-living home.

The team developed WiGait to be more privacy-minded than cameras, showing you as nothing more than a moving dot on a screen. In the future they hope to train it on people with walking impairments from Parkinson’s, Alzheimer’s or multiple sclerosis, to help physicians accurately track disease progression and adjust medications. The true novelty of this device is that it can map major metrics of health and behavior without any active engagement from the user, which is especially helpful for the cognitively impaired.