The Experts below are selected from a list of 96 Experts worldwide ranked by ideXlab platform

Craig Hukins - One of the best experts on this subject based on the ideXlab platform.

  • towards a home Apnea Monitor a new method of extracting speech and voiced snore segments from noisy respiratory sounds
    IEEE International Workshop on Biomedical Circuits and Systems, 2004
    Co-Authors: A S Karunajeewa, Udantha R Abeyratne, Craig Hukins
    Abstract:

    Snoring is the most frequent symptom of obstructive sleep Apnea (OSA), which is a difficult-to-diagnose serious disease of high prevalence. Recent work from our group (and others) has unequivocally established that snore-related-sounds (SRS) carries sufficient information to base the design of a community screening device on SRS. A main challenge to overcome in such a device is that the background electrical and acoustical noise, including embedded speech segments, can corrupt genuine snores. In this paper, we model snore sounds as the response of a mixed-phase system, when excited by a pseudo-periodic or white noise sequences (as needed to describe voiced and unvoiced snore segments). Observation noise is considered a Gaussian process. We present a novel algorithm to extract speech and voiced-snore segments from corrupted SRS measurements. The algorithm utilizes higher order statistics (HOS) due to its insensitivity to Gaussian noise and the ability to reconstruct a system preserving true phase characteristics.

  • 2004 ieee international workshop on biomedical circuits systems towards a home Apnea Monitor a new method of extracting speech and voiced snore segments from noisy respiratory sounds
    2004
    Co-Authors: Asela S Kumnajeewu, Udantha R Abeyratne, Craig Hukins
    Abstract:

    Snoring is the most frequent symptom of Obstructive SIeep Apnea (OSA), which is a difficult-to-diagnose serious disease of high prevalence. Recent work from our group (and others) has unequivocally established that Snore-Related-Sounds (SE) carries sufficient information to base the design of a community screening device on SRS. A main challenge to overcome in such a device is that the background dectrical and acoustical noise, including embedded speech segments, can corrupt genuine snores. In this paper, we model snore sounds as the response of a mixed-phase system, when excited by a pseudo-periodic or while noise sequences (as needed to dewribe Voiced and Unvoiced snore segments), Observation noise is considered a Gaussian process. We present a novel algorithm to extract Speech and Voiced-Snore segments from corrupted SRS measurements. The algorithm utilizes Higher Order Statistics (HOS) due to its insensitivity to Gaussian noise and the ability to reconstruct a system preserving true phase characteristics.

Nuno Cabanelas - One of the best experts on this subject based on the ideXlab platform.

  • Utility of Pacemaker With Sleep Apnea Monitor to Predict Left Ventricular Overload and Acute Decompensated Heart Failure.
    The American journal of cardiology, 2019
    Co-Authors: João B. Augusto, M Beringuilho, Susana Antunes, João Baltazar Ferreira, D. Faria, D Roque, Hilaryano Ferreira, Inês Fialho, Mariana Faustino, Nuno Cabanelas
    Abstract:

    Pacemakers with sleep Apnea Monitor (SAM) provide an easy tool to assess obstructive sleep Apnea over long periods of time. The link between respiratory disturbances at night and the incidence of acute decompensated heart failure (ADHF) is not well established. We aimed at (1) determining the ability of SAM pacemakers to evaluate the extent of left ventricular overload and (2) assess the impact of respiratory disturbances at night on the occurrence of ADHF over 1-year of follow-up. We conducted a single-center prospective study. Consecutive patients with SAM pacemakers were comprehensively assessed. SAM automatically computes a respiratory disturbance index (RDI, Apneas/hypopneas per hour - AH/h) in the previous night and the percentage of nights with RDI >20 AH/h in the previous 6 months. Thirty-seven patients were included (79.3 ± 11.2 years, 46% males). A high RDI in the previous night and a higher %nights with increased RDI were associated with increased NT-proBNP values (p = 0.008 and p = 0.013, respectively) and were the sole predictors of increased noninvasive pulmonary capillary wedge pressures (PCWP) in the morning of assessment (p = 0.031 and p = 0.044, respectively). Receiver operating characteristic curve analysis revealed an area under the curve of 0.804 (95% confidence interval 0.656 to 0.953, p = 0.002) for %nights with RDI >20 AH/h in the prediction of high PCWP. Patients with >12.5% of nights with RDI >20AH/h tended to have more ADHF during follow-up (log-rank p = 0.067). In conclusion, a high burden of Apneas/hypopneas at night is associated with elevated NT-proBNP and PCWP values and an increased risk of ADHF over 1 year. These patients might benefit from early tailored clinical management.

M Beringuilho - One of the best experts on this subject based on the ideXlab platform.

  • Utility of Pacemaker With Sleep Apnea Monitor to Predict Left Ventricular Overload and Acute Decompensated Heart Failure.
    The American journal of cardiology, 2019
    Co-Authors: João B. Augusto, M Beringuilho, Susana Antunes, João Baltazar Ferreira, D. Faria, D Roque, Hilaryano Ferreira, Inês Fialho, Mariana Faustino, Nuno Cabanelas
    Abstract:

    Pacemakers with sleep Apnea Monitor (SAM) provide an easy tool to assess obstructive sleep Apnea over long periods of time. The link between respiratory disturbances at night and the incidence of acute decompensated heart failure (ADHF) is not well established. We aimed at (1) determining the ability of SAM pacemakers to evaluate the extent of left ventricular overload and (2) assess the impact of respiratory disturbances at night on the occurrence of ADHF over 1-year of follow-up. We conducted a single-center prospective study. Consecutive patients with SAM pacemakers were comprehensively assessed. SAM automatically computes a respiratory disturbance index (RDI, Apneas/hypopneas per hour - AH/h) in the previous night and the percentage of nights with RDI >20 AH/h in the previous 6 months. Thirty-seven patients were included (79.3 ± 11.2 years, 46% males). A high RDI in the previous night and a higher %nights with increased RDI were associated with increased NT-proBNP values (p = 0.008 and p = 0.013, respectively) and were the sole predictors of increased noninvasive pulmonary capillary wedge pressures (PCWP) in the morning of assessment (p = 0.031 and p = 0.044, respectively). Receiver operating characteristic curve analysis revealed an area under the curve of 0.804 (95% confidence interval 0.656 to 0.953, p = 0.002) for %nights with RDI >20 AH/h in the prediction of high PCWP. Patients with >12.5% of nights with RDI >20AH/h tended to have more ADHF during follow-up (log-rank p = 0.067). In conclusion, a high burden of Apneas/hypopneas at night is associated with elevated NT-proBNP and PCWP values and an increased risk of ADHF over 1 year. These patients might benefit from early tailored clinical management.

  • Utility of Pacemaker With Sleep Apnea Monitor to Predict Left Ventricular Overload and Acute Decompensated Heart Failure
    'Elsevier BV', 2019
    Co-Authors: Augusto J, Antunes S, Jb Ferreira, Faria D, Roque D, M Beringuilho
    Abstract:

    Pacemakers with sleep Apnea Monitor (SAM) provide an easy tool to assess obstructive sleep Apnea over long periods of time. The link between respiratory disturbances at night and the incidence of acute decompensated heart failure (ADHF) is not well established. We aimed at (1) determining the ability of SAM pacemakers to evaluate the extent of left ventricular overload and (2) assess the impact of respiratory disturbances at night on the occurrence of ADHF over 1-year of follow-up. We conducted a single-center prospective study. Consecutive patients with SAM pacemakers were comprehensively assessed. SAM automatically computes a respiratory disturbance index (RDI, Apneas/hypopneas per hour - AH/h) in the previous night and the percentage of nights with RDI >20 AH/h in the previous 6 months. Thirty-seven patients were included (79.3 ± 11.2 years, 46% males). A high RDI in the previous night and a higher %nights with increased RDI were associated with increased NT-proBNP values (p = 0.008 and p = 0.013, respectively) and were the sole predictors of increased noninvasive pulmonary capillary wedge pressures (PCWP) in the morning of assessment (p = 0.031 and p = 0.044, respectively). Receiver operating characteristic curve analysis revealed an area under the curve of 0.804 (95% confidence interval 0.656 to 0.953, p = 0.002) for %nights with RDI >20 AH/h in the prediction of high PCWP. Patients with >12.5% of nights with RDI >20AH/h tended to have more ADHF during follow-up (log-rank p = 0.067). In conclusion, a high burden of Apneas/hypopneas at night is associated with elevated NT-proBNP and PCWP values and an increased risk of ADHF over 1 year. These patients might benefit from early tailored clinical management.info:eu-repo/semantics/publishedVersio

João B. Augusto - One of the best experts on this subject based on the ideXlab platform.

  • Utility of Pacemaker With Sleep Apnea Monitor to Predict Left Ventricular Overload and Acute Decompensated Heart Failure.
    The American journal of cardiology, 2019
    Co-Authors: João B. Augusto, M Beringuilho, Susana Antunes, João Baltazar Ferreira, D. Faria, D Roque, Hilaryano Ferreira, Inês Fialho, Mariana Faustino, Nuno Cabanelas
    Abstract:

    Pacemakers with sleep Apnea Monitor (SAM) provide an easy tool to assess obstructive sleep Apnea over long periods of time. The link between respiratory disturbances at night and the incidence of acute decompensated heart failure (ADHF) is not well established. We aimed at (1) determining the ability of SAM pacemakers to evaluate the extent of left ventricular overload and (2) assess the impact of respiratory disturbances at night on the occurrence of ADHF over 1-year of follow-up. We conducted a single-center prospective study. Consecutive patients with SAM pacemakers were comprehensively assessed. SAM automatically computes a respiratory disturbance index (RDI, Apneas/hypopneas per hour - AH/h) in the previous night and the percentage of nights with RDI >20 AH/h in the previous 6 months. Thirty-seven patients were included (79.3 ± 11.2 years, 46% males). A high RDI in the previous night and a higher %nights with increased RDI were associated with increased NT-proBNP values (p = 0.008 and p = 0.013, respectively) and were the sole predictors of increased noninvasive pulmonary capillary wedge pressures (PCWP) in the morning of assessment (p = 0.031 and p = 0.044, respectively). Receiver operating characteristic curve analysis revealed an area under the curve of 0.804 (95% confidence interval 0.656 to 0.953, p = 0.002) for %nights with RDI >20 AH/h in the prediction of high PCWP. Patients with >12.5% of nights with RDI >20AH/h tended to have more ADHF during follow-up (log-rank p = 0.067). In conclusion, a high burden of Apneas/hypopneas at night is associated with elevated NT-proBNP and PCWP values and an increased risk of ADHF over 1 year. These patients might benefit from early tailored clinical management.

A S Karunajeewa - One of the best experts on this subject based on the ideXlab platform.

  • towards a home Apnea Monitor a new method of extracting speech and voiced snore segments from noisy respiratory sounds
    IEEE International Workshop on Biomedical Circuits and Systems, 2004
    Co-Authors: A S Karunajeewa, Udantha R Abeyratne, Craig Hukins
    Abstract:

    Snoring is the most frequent symptom of obstructive sleep Apnea (OSA), which is a difficult-to-diagnose serious disease of high prevalence. Recent work from our group (and others) has unequivocally established that snore-related-sounds (SRS) carries sufficient information to base the design of a community screening device on SRS. A main challenge to overcome in such a device is that the background electrical and acoustical noise, including embedded speech segments, can corrupt genuine snores. In this paper, we model snore sounds as the response of a mixed-phase system, when excited by a pseudo-periodic or white noise sequences (as needed to describe voiced and unvoiced snore segments). Observation noise is considered a Gaussian process. We present a novel algorithm to extract speech and voiced-snore segments from corrupted SRS measurements. The algorithm utilizes higher order statistics (HOS) due to its insensitivity to Gaussian noise and the ability to reconstruct a system preserving true phase characteristics.