Purpose Due to lack of access and high cost of polysomnography, portable sleep apnea testing has been developed to diagnose sleep apnea. Despite being less expensive, and having fewer sensors and reasonable accuracy in identifying sleep apnea, such devices can be less accurate than polysomnography in detecting apneas/hypopneas. To increase the accuracy of apnea/hypopnea detection, an accurate airflow estimation is required. However, current airflow measurement techniques employed in portable devices are inconvenient and subject to displacement during sleep. In this study, algorithms were developed to estimate respiratory motion and airflow using tracheo-sternal motion and tracheal sounds. Patients and Methods Adults referred for polysomnography were included. Simultaneous to polysomnography, a patch device with an embedded 3-dimensional accelerometer and microphone was affixed to the suprasternal notch to record tracheo-sternal motion and tracheal sounds, respectively. Tracheo-sternal motion was used to train two mathematical models for estimating changes in respiratory motion and airflow compared to simultaneously measured thoracoabdominal motion and nasal pressure from polysomnography. The amplitude of the estimated airflow was then adjusted by the tracheal sound envelope in segments with unstable breathing. Results Two hundred and fifty-two subjects participated in this study. Overall, the algorithms provided highly accurate estimates of changes in respiratory motion and airflow with mean square errors (MSE) of 3.58 ± 0.82% and 2.82 ± 0.71%, respectively, compared to polysomnographic signals. The estimated motion and airflow from the patch signals detected apneas and hypopneas scored on polysomnography in 63.9% and 88.3% of cases, respectively. Conclusion This study presents algorithms to accurately estimate changes in respiratory motion and airflow, which provides the ability to detect respiratory events during sleep. Our study suggests that such a simple and convenient method could be used for portable monitoring to detect sleep apnea. Further studies will be required to test this possibility.
Purpose Sleep apnea (SA) is highly prevalent, but under diagnosed due to inaccessibility of sleep testing. To address this issue, portable devices for home sleep testing have been developed to provide convenience with reasonable accuracy in diagnosing SA. The objective of this study was to test the validity a novel portable sleep apnea testing device, BresoDX1, in SA diagnosis, via recording of trachea-sternal motion, tracheal sound and oximetry. Patients and Methods Adults with a suspected sleep disorder were recruited to undergo in-laboratory polysomnography (PSG) and a simultaneous BresoDX1 recording. Data from BresoDX1 were collected and features related to breathing sounds, body motions and oximetry were extracted. A deep neural network (DNN) model was trained with 61-second epochs of the extracted features to detect apneas and hypopneas from which an apnea-hypopnea index (AHI) was calculated. The AHI estimated by BresoDX1 (AHI breso ) was compared to the AHI determined from PSG (AHI PSG ) and the sensitivity and specificity of SA diagnosis were assessed at an AHI PSG ≥ 15. Results Two-hundred thirty-three participants (mean ± SD) 50 ± 16 years of age, with BMI of 29.8 ± 6.6 and AHI of 19.5 ± 22.7, were included. There was a strong relationship between AHI breso and AHI PSG (r = 0.91, p < 0.001). SA detection for an AHI PSG ≥ 15 was highly sensitive (90.0%) and specific (85.9%). Conclusion We conclude that the DNN model we developed via recording and analyses of trachea-sternal motion and sound along with oximetry provides an accurate estimate of the AHI PSG with high sensitivity and specificity. Therefore, BresoDX1 is a simple, convenient and accurate portable SA monitoring device that could be employed for home SA testing in the future.
RESUMO -Dada a relevância do açúcar, um dos principais subprodutos da canade-açúcar para o Brasil, é crescente a realização de trabalhos visando aumentar a eficiência, bem como evitar perdas no processo. No entanto, durante oarmazenamentodo açúcar, é sabido que fatores ambientais (Temperatura, Umidade Relativa, Luz e Tempo) afetam a qualidade do produto final. Nesse contexto, este projeto teve por objetivos avaliar quais fatores sãodeterminantes para acentuar o processo de formação de corICUMSA durante o período de armazenamento de açúcar cristal branco. Os resultados das quantidades de açúcares redutores (AR), açúcares redutores totais (ART) e cor ICUMSA foram avaliados por superfície de respostas. Concluiu-se que houve alterações das quantidades de AR, ART e cor ICUMSA nas amostras de sacarose analisadas em função das variáveis, sendo a Umidade a mais decisiva. Assim,ficou evidente que deve-se evitar tais condições de umidade e temperatura elevadas nos galpões de armazenamento de açúcar, a fim de que se preserve a qualidade do produto, que é altamente perecível. 1.INTRODUÇÃOA importância da agroindústria canavieira no Brasil e os derivados deste setor, na balança comercial, especialmente o açúcar, incentivam trabalhos que abordem o desempenho do segmento exportador do país de maneira particular. Tal setor tem participação direta tanto no mercado interno quanto internacional, uma vez que a cana-de-açúcar está entre as principais culturas em termos de área plantada, volume e custo produtivo (Alves e Bacchi, 2004).No entanto, durante a armazenagem do açúcar, é sabido que diferentes fatores ambientais afetam a qualidade do produto acabado. Dentre os fatores podem ser listados, a Temperatura, Umidade Relativa do ambiente, a presença de Luz no local de estocagem, bem como o Tempo, ou seja, o período que o produto permanece armazenado.A sacarose é o carboidrato de maior interesse no processamento da cana-de-açúcar, a qual se deseja obter na forma cristalizada, é susceptível a reações importantes por efeito da temperatura, enzimas e microrganismos (Mantelatto, 2005).
Introduction Diagnosing sleep apnea requires detection of apneas and hypopneas during sleep either via in-laboratory overnight polysomnography (PSG) or portable in-home sleep apnea testing (HSAT). While PSG is the optimal method, it is expensive, inconvenient and often inaccessible for patients. Although HSATs are more convenient and less expensive than PSG, they are not as accurate and have relatively high failure rates because of the nature of the sensors used to measure respiratory variables. We have developed a HSAT, the Patch, that is unique in that it is very simple and reliable because it measures respiratory variables using tracheal motion and sound combined with oximetry to detect respiratory events. In this study we tested the ability of the Patch to detect respiratory events versus simultaneous PSG. Methods Participants were adults with a suspected sleep disorder referred to the sleep laboratory at Toronto Rehabilitation Institute for PSG. Simultaneous to the PSG, the Patch, consisting of a module containing a microphone and a 3-D accelerometer that was affixed to participants’ suprasternal notch, and a finger oximeter. After filtering the tracheal signals, the envelope of the tracheal motions in the cranial and postero-anterior directions and tracheal sound envelope were extracted. Along with tracheal features, the amplitude and slopes of oxygen desaturations were also extracted and, were fed into a supervised deep neural network model to detect apneas and hypopneas. The total number of detected events was divided by total estimated sleep time to estimate the apnea-hypopnea index (AHI). The performance of the model in diagnosing sleep apnea was evaluated by sensitivity (AHI≥15) and specificity (AHI<15). The relationship between the estimated AHI and PSG-based AHI was quantified using Pearson correlation. Results Ninety-nine participants (42 females, age: 48±16 years, body mass index: 29.2±5.2 kg/m2, and AHI: 15.8±19.4 events/hour) completed the study. We found that the Patch had 88.6% sensitivity and 89.1% specificity for diagnosing sleep apnea. Strong agreement was observed between the estimated and reference AHI values (r = 0.92, p < 0.001). Conclusion The Patch is a novel, robust and convenient portable device that provides an accurate means of detecting and quantifying sleep apnea. It has the potential to provide reliable home-based sleep apnea monitoring. Support (If Any) Funded by Bresotec Inc.
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