LESA Researchers published in Biomedical Signal Processing and Control for Work in Automatic Sleep Estimation Using Actigraphy
LESA Researchers published in Biomedical Signal Processing and Control for Work in Automatic Sleep Estimation Using Actigraphy

LESA Researchers published in Biomedical Signal Processing and Control for Work in Automatic Sleep Estimation Using Actigraphy


Building on the growing body of work in human circadian function, LESA researchers Jiawei Yin, Agung Julius, John Wen, John Hanifin, Ben Warfield, and George ‘Bud’ Brainard provide insights into ‘Automatic sleeping time estimation and mild traumatic brain injury (mTBI) detection using actigraphy data’ in the March issues of Biomedical Signal Processing and Control‘. Their paper presents a method for estimating the sleep/wake state based on the minute-by-minute actigraphy data measured by wrist actigraphy and its associated scoring software. The circadian phase shift is estimated from actigraphy data using an adaptive notch filter algorithm. Compared with the scoring methods used in wrist actigraphy, the estimated wake-onset time from our method is more consistent with the sleep logs reported by the subjects. Concussion detection based on the sleep-related features calculated from actigraphy data is also presented, with detection accuracy up to about 90%. This result implies that the concussion is closely related to sleep and circadian disruption. Learn more about LESA’s Human Centric Healthcare.