Accelerometer-based method for correcting signal baseline changes caused by motion artifacts in medical near-infrared spectroscopy

摘要

In medical near-infrared spectroscopy (NIRS), movements of the subject often cause large step changesnin the baselines of the measured light attenuation signals. This prevents comparison of hemoglobin concentrationnlevels before and after movement. We present an accelerometer-based motion artifact removal (ABAMAR) algorithmnfor correcting such baseline motion artifacts (BMAs). ABAMAR can be easily adapted to various long-termnmonitoring applications of NIRS.We applied ABAMAR to NIRS data collected in 23 all-night sleep measurementsnand containing BMAs from involuntary movements during sleep. For reference, three NIRS researchers independentlynidentified BMAs from the data. To determine whether the use of an accelerometer improves BMA detectionnaccuracy, we compared ABAMAR to motion detection based on peaks in the moving standard deviation (SD) ofnNIRS data. The number of BMAs identified by ABAMAR was similar to the number detected by the humans, andn79% of the artifacts identified by ABAMAR were confirmed by at least two humans. While the moving SD of NIRSndata could also be used for motion detection, on average 2 out of the 10 largest SD peaks in NIRS data each nightnoccurred without the presence of movement. Thus, using an accelerometer improves BMA detection accuracy innNIRS.