An interpretable framework for sleep posture change detection and postural inactivity segmentation using wrist kinematics.

ABSTRACT: Sleep posture and movements offer insights into neurophysiological health and correlate with overall well-being and quality of life. Clinical practices utilise polysomnography for sleep assessment, which is intrusive, performed in unfamiliar environments, and requires trained personnel. While sensor technologies such as actigraphy are less invasive alternatives, concerns about their reliability and precision in clinical practice persist. Moreover, the field lacks a universally accepted algorithm, with methods ranging from raw signal thresholding to data-intensive classification models that may be unfamiliar to medical staff. This paper proposes a comprehensive framework for objectively detecting sleep posture changes and temporally segmenting postural inactivity using clinically relevant j

SUBMITTER: Elnaggar O 

PROVIDER: S-EPMC10590424 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature