Researchers continuously hunt for longevity indicators. Traditional longevity metrics include blood pressure, blood sugar, heart rate and heart rate variability (HRV), body temperature, and resting pulse. An aggregate study of studies, Gait Speed and Survival in Older Adults published in 2011, indicated that walking gait correlates positively with survival. The researchers theorized that accurate gait measurements would help clinicians make more individualized survival estimates and therefore be able to set better goals of care for geriatric patients.
Computer scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) developed WiGait, a Wi-Fi motion-sensitive device that hangs on the wall. WiGait can measure walking speeds of multiple people with 95 to 99 percent accuracy. WiGait, which is about the size of a small painting, works by analyzing wireless signals in the room and their reflections off people’s bodies. People in the room do not need to wear sensors and signaling hardware, which makes the system less intrusive and aids compliance. There’s nothing people need to do but go about their daily lives. According to the researchers, WiGait’s granularity is sufficient to differentiate between cleaning the kitchen or brushing one’s teeth. Stride length can also understand conditions like Parkinson’s disease, which is characterized by reduced step size.
WiGait is less intrusive than camera systems because it does not make images of the person. The system can detect falling, breathing, and even emotions, according to the MIT researchers. In the future the scientists hope to develop algorithms can track the progression of Parkinson’s Disease and multiple sclerosis to assist clinicians in adjusting medications.
