A Study on Linear Acceleration of the Wrist During Free-Living

摘要

Accelerometers have gained popularity in biomedical and m-health applications such as actigraphy or automated dietary monitoring due to their ease of use and their ability to characterize motion. These sensors report raw acceleration from which gravity and linear acceleration must be separated, with commercial packages reporting raw acceleration, linear acceleration or both. New researchers to the field may often be confused when to use raw acceleration or linear acceleration, especially given the susceptibility of linear acceleration to noise, and the lack of published distributions of these signals. This paper provides a short tutorial on obtaining linear acceleration estimates. Using these methods we analyze a large dataset containing 4,680 hours of wrist tracking data, the largest such dataset known to us. We learn the range of wrist motion accelerations, and quantify the expected noise in the linear acceleration signal. We explain the sources of this noise, and a filtering technique to mitigate it. For the first time, we report the range of wrist acceleration values observed during free-living, and quantify the expected range of noise in this wrist acceleration. We show that while previous work has reported average accelerations at the feet and body ranging from 0-15g during spots-like activities like walking, running or jumping, wrist acceleration in free-living subjects during daily activities is often much lower, and ranges from 0-0.2g. We show that noise in linear acceleration can range from 0-0.06g, an overlap of 70%. This suggests that in applications where the wrist acceleration is in this range of noise, linear acceleration may not provide useful features, and researchers should only rely on raw acceleration instead.