A stride ahead in gait analysis for detecting potential health issues

click to enlargeReaders experienced in senior healthcare know that changes in gait can be predictors or a proxy for negative change in physical or mental status, for instance when walking becomes slow or unsteady and the risk of falling rises. We’re familiar with various remote monitoring approaches such as pads, sensor arrays, camera systems such as the VICON tracker, worn sensors, and Fitbits but none so far have proven workable, widespread, or particularly accurate. A research group at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have designed a system using wireless signals which can measure the walking speed of multiple people with 95 to 99 percent accuracy, the same as clinical measurement and VICON. The WiGait device is the size of a small painting and emits signals at about the level of a smartphone. It analyzes reflected signals off the body and can differentiate through algorithms the type of movement, e.g. walking versus brushing teeth. It can also gauge stride length, since changes in that may indicate progression in diseases such as Parkinson’s. Since the WiGait can be used for longitudinal tracking, gait changes can be further correlated with disease state with the intent of avoiding hospitalization. The researchers built off of previous work on WiTrack, which used signals to track behaviors from breathing and falling to specific emotions.  MIT NewsPaper: Extracting Gait Velocity and Stride Length from Surrounding Radio Signals

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