Paper
29 August 2017 Shedding light to sleep studies
James Dieffenderfer, Andrew Krystal, Alper Bozkurt
Author Affiliations +
Abstract
This paper presents our efforts in the development of a small wireless, flexible bandage sized near-infrared spectroscopy (NIRS) system for sleep analysis. The current size of the system is 2.8 cm × 1.7 cm × 0.6 cm. It is capable of performing NIRS with 660nm, 940nm and 850nm wavelengths for up to 11 hours continuously. The device is placed on the forehead to measure from the prefrontal cortex and the raw data is continuously streamed over Bluetooth to a nearby data aggregator such as a smartphone for post processing and cloud connection. In this study, we performed traditional polysomnography simultaneously with NIRS to evaluate agreement with traditional measures of sleep and to provide labelled data for future work involving learning algorithms. Ultimately, we expect a machine learning algorithm to be able to generate characterization of sleep states comparable to traditional methods based on this biophotonics data. The system also includes an inertial measurement unit and the features that can be extracted from the presented system include sleep posture, heart rate, respiratory rate, relative change in oxy and deoxy hemoglobin concentrations and tissue oxygenation and cerebral arterial oxygen extracted from these. Preliminary proof of concept results are promising and demonstrate the capability to measure heart rate, respiratory rate and slow-wave-sleep stages. This system serves as a prototype to evaluate the potential of a small bandage-size continuous-wave NIRS device to be a useful means of studying sleep.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James Dieffenderfer, Andrew Krystal, and Alper Bozkurt "Shedding light to sleep studies", Proc. SPIE 10352, Biosensing and Nanomedicine X, 103520M (29 August 2017); https://doi.org/10.1117/12.2275625
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Near infrared spectroscopy

Polysomnography

Biomedical optics

Biological research

Feature extraction

Heart

Machine learning

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