We know that blood pressure, breathing, body temperature, and pulse provide an important window into the complexities of human health. But a research suggests that there is another vital sign called how fast you walk could also be a better predictor of health issues like cognitive decline, cardiac, or pulmonary diseases.
It is hard to accurately monitor walking speed in a way that is 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 go wireless.
In a new paper, the team presents a device called WiGait, which measures the walking speed of multiple people with 95 to 99 percent accuracy using wireless signals.
The device’s size is of a small painting, which can be placed on the wall of a house and its signals emit roughly one-hundredth the amount of radiation of a standard cell phone. The device is built on Dina Katabi’s previous work on WiTrack, which analyses wireless signals reflected off people’s body to measure a range of behaviors from breathing and falling to specific emotions.
“By using in-home sensors, we can see trends in how walking speed changes over longer periods of time,” says lead author and Ph.D. student Chen-Yu Hsu. “This provides insight into individual health routine, whether that’s doing physical therapy or changing their medications.”
WiGait is 85 to 99 percent accurate at measuring a person’s stride length, which allows researchers to understand conditions like Parkinson’s disease that are characterized by reduced step size.
The walking speed is measured by physical therapists or clinicians using a stopwatch. Wearable’s devices like Fitbit can roughly estimate speed based on step count and GPS. The GPS-enabled smartphones are inaccurate and sometimes doesn’t work indoors. Cameras are intrusive and can only monitor one room. VICON motion tracking is the only method that’s comparably accurate to WiGait, but it is not widely available enough to be practical for monitoring day-to-day health changes.
Meanwhile, WiGait measures walking speed with a high level of granularity, without requiring the user to wear or carry a sensor. It does so by analyzing the surrounding wireless signals and their reflections of a user’s body. The CSAIL team algorithms can also distinguish walking from other movements, such as cleaning the kitchen or brushing one’s teeth.
Katabi says the device helps to reveal important health information, particularly for the elders. 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 helps the person to determine if they should move to a different environment such as an assisted-living home.
“Many avoidable hospitalizations are related to issues like falls, congestive heart disease, or chronic obstructive pulmonary disease, which have all been shown to be correlated to gait speed,” Katabi says. “Reducing the number of hospitalizations, even by a small amount, could vastly improve healthcare costs.”
The team developed WiGait to be more privacy-minded than cameras, showing you 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, which helps physicians to 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,” says Ipsit Vahia, a geriatric clinician at McLean Hospital and Harvard Medical School, who was not involved in the research. “Gait speed is a proxy indicator of many clinically important conditions and down the line, this could extend to measuring sleep patterns, respiratory rates, and other vital human behaviors.”
More information can be found at: CSAIL.