Health and sleep nursing assistant for real-time, contactless, and non-invasive monitoring
Department
Information Technology
Document Type
Article
Publication Date
8-1-2021
Abstract
In this paper, we introduce a novel health and sleep nursing assistant called “Helena” for real-time, contactless, and non-invasive monitoring that can be mounted on a bed frame to continuously monitor sleep activities (entry/exit of bed, movement, and posture changes), vital signs (heart rate and respiration rate), and falls from bed in a pervasive computing manner. The smart sensor senses bed vibrations generated by body movements to characterize sleep activities and vital signs based on advanced signal processing and machine learning methods. The device can provide information about sleep patterns, generate real-time results, and support continuous sleep assessment and health tracking. The novel method for detecting falls from bed has not been attempted before and represents a life-changing for high-risk communities, such as seniors. Comprehensive tests and validations were conducted to evaluate system performances using FDA approved and wearable devices. Our system has an accuracy of 99.5% detecting on-bed (entries), 99.73% detecting off-bed (exits), 97.92% detecting movements on the bed, 92.08% detecting posture changes, and 97% detecting falls from bed. The system estimation of heart rate (HR) ranged ±2.41 beats-per-minute compared to Apple Watch Series 4, while the respiration rate (RR) ranged ±0.89 respiration-per-minute compared to an FDA (Food and Drug Administration) oximeter and a metronome.
Journal Title
Pervasive and Mobile Computing
Journal ISSN
15741192
Volume
75
Digital Object Identifier (DOI)
10.1016/j.pmcj.2021.101422