Researchers have used machine learning technologies to develop an algorithm that converts data from a small, lightweight, waterproof wearable sensor taped to the lower back into an accurate estimate of step length. The model is almost four times more accurate than the currently accepted biomechanical model.
Accurate and continuous remote monitoring of step length can be sensitive marker for neurological diseases and aging
