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      Continuous Vital Monitoring During Sleep and Light Activity Using Carbon-Black Elastomer Sensors

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          Abstract

          The comfortable, continuous monitoring of vital parameters is still a challenge. The long-term measurement of respiration and cardiovascular signals is required to diagnose cardiovascular and respiratory diseases. Similarly, sleep quality assessment and the recovery period following acute treatments require long-term vital parameter datalogging. To address these requirements, we have developed “VitalCore”, a wearable continuous vital parameter monitoring device in the form of a T-shirt targeting the uninterrupted monitoring of respiration, pulse, and actigraphy. VitalCore uses polymer-based stretchable resistive bands as the primary sensor to capture breathing and pulse patterns from chest expansion. The carbon black-impregnated polymer is implemented in a U-shaped configuration and attached to the T-shirt with “interfacing” material along with the accompanying electronics. In this paper, VitalCore is bench tested and compared to gold standard respiration and pulse measurements to verify its functionality and further to assess the quality of data captured during sleep and during light exercise (walking). We show that these polymer-based sensors could identify respiratory peaks with a sensitivity of 99.44%, precision of 96.23%, and false-negative rate of 0.557% during sleep. We also show that this T-shirt configuration allows the wearer to sleep in all sleeping positions with a negligible difference of data quality. The device was also able to capture breathing during gait with 88.9–100% accuracy in respiratory peak detection.

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          Most cited references45

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          Correlated and uncorrelated regions in heart-rate fluctuations during sleep.

          Healthy sleep consists of several stages: deep sleep, light sleep, and rapid eye movement (REM) sleep. Here we show that these sleep stages can be characterized and distinguished by correlations of heart rates separated by n beats. Using the detrended fluctuation analysis (DFA) up to fourth order we find that long-range correlations reminiscent to the wake phase are present only in the REM phase. In the non-REM phases, the heart rates are uncorrelated above the typical breathing cycle time, pointing to a random regulation of the heartbeat during non-REM sleep.
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            Comparison of detrended fluctuation analysis and spectral analysis for heart rate variability in sleep and sleep apnea.

            Sleep has been regarded as a testing situation for the autonomic nervous system, because its activity is modulated by sleep stages. Sleep-related breathing disorders also influence the autonomic nervous system and can cause heart rate changes known as cyclical variation. We investigated the effect of sleep stages and sleep apnea on autonomic activity by analyzing heart rate variability (HRV). Since spectral analysis is suited for the identification of cyclical variations and detrended fluctuation analysis can analyze the scaling behavior and detect long-range correlations, we compared the results of both complementary techniques in 14 healthy subjects, 33 patients with moderate, and 31 patients with severe sleep apnea. The spectral parameters VLF, LF, HF, and LF/HF confirmed increasing parasympathetic activity from wakefulness and REM over light sleep to deep sleep, which is reduced in patients with sleep apnea. Discriminance analysis was used on a person and sleep stage basis to determine the best method for the separation of sleep stages and sleep apnea severity. Using spectral parameters 69.7% of the apnea severity assignments and 54.6% of the sleep stage assignments were correct, while using scaling analysis these numbers increased to 74.4% and 85.0%, respectively. We conclude that changes in HRV are better quantified by scaling analysis than by spectral analysis.
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              Respiratory rate: the neglected vital sign.

              The level of documentation of vital signs in many hospitals is extremely poor, and respiratory rate, in particular, is often not recorded. There is substantial evidence that an abnormal respiratory rate is a predictor of potentially serious clinical events. Nurses and doctors need to be more aware of the importance of an abnormal respiratory rate as a marker of serious illness. Hospital systems that encourage appropriate responses to an elevated respiratory rate and other abnormal vital signs can be rapidly implemented. Such systems help to raise and sustain awareness of the importance of vital signs.
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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                12 March 2020
                March 2020
                : 20
                : 6
                : 1583
                Affiliations
                [1 ]The MARCS Institute, Western Sydney University, Milperra, NSW 2560, Australia; P.Breen@ 123456westernsydney.edu.au
                [2 ]School of Engineering, Western Sydney University, Penrith, NSW 2751, Australia; G.Gargiulo@ 123456westernsydney.edu.au
                [3 ]Translational Health Research Institute, Western Sydney University, Campbelltown, NSW 2560, Australia
                Author notes
                Author information
                https://orcid.org/0000-0002-1849-4235
                https://orcid.org/0000-0002-2616-2804
                Article
                sensors-20-01583
                10.3390/s20061583
                7146453
                32178307
                95f4b106-f5a4-4a7e-92b9-af2af545676b
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 10 January 2020
                : 10 March 2020
                Categories
                Article

                Biomedical engineering
                vital parameter monitoring,sleep monitoring,conductive polymer,home sleep test,continuous respiratory monitoring

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