Perceptual evaluation of measures of spectral variance

Agus, Natalie; Anderson, Hans; Chen, Jer‐Ming; Lui, Simon; Herremans, Dorien

doi:10.1121/1.5040484

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…represents a non-seasonal autoregressive lag polynomial, φ p (B s ) represents a seasonal autoregressive lag polynomial, θ q (B) represents a non-seasonal moving average lag polynomial, θ Q (B s ) represents a seasonal moving average lag polynomial, A(t) represents a trend polynomial, and can be constant. Finally, we need to apply the Ljung-Box method to perform a goodness-offit test on the model [21]. The purpose is to analyze the autocorrelation of the residual sequence.…”

Section: Seasonal Autoregressive Integrated Moving Average Model (Sar...mentioning

confidence: 99%

Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models

Chen,

Zheng,

Shi

et al. 2024

BMC Public Health

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Background Influenza is a highly contagious respiratory disease that presents a significant challenge to public health globally. Therefore, effective influenza prediction and prevention are crucial for the timely allocation of resources, the development of vaccine strategies, and the implementation of targeted public health interventions. Method In this study, we utilized historical influenza case data from January 2013 to December 2021 in Fuzhou to develop four regression prediction models: SARIMA, Prophet, Holt-Winters, and XGBoost models. Their predicted performance was assessed by using influenza data from the period from January 2022 to December 2022 in Fuzhou. These models were used for fitting and prediction analysis. The evaluation metrics, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), were employed to compare the performance of these models. Results The results indicate that the epidemic of influenza in Fuzhou exhibits a distinct seasonal and cyclical pattern. The influenza cases data displayed a noticeable upward trend and significant fluctuations. In our study, we employed SARIMA, Prophet, Holt-Winters, and XGBoost models to predict influenza outbreaks in Fuzhou. Among these models, the XGBoost model demonstrated the best performance on both the training and test sets, yielding the lowest values for MSE, RMSE, and MAE among the four models. Conclusion The utilization of the XGBoost model significantly enhances the prediction accuracy of influenza in Fuzhou. This study makes a valuable contribution to the field of influenza prediction and provides substantial support for future influenza response efforts.

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Section: Seasonal Autoregressive Integrated Moving Average Model (Sar...mentioning

confidence: 99%

Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models

Chen,

Zheng,

Shi

et al. 2024

BMC Public Health

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“…In this study, a series of listening tests are conducted to measure the JND SD level. For other psychoacoustic JNDs recently reported in the literature, please see Agus et al (2018), Alkahtani (2019), Boucher et al (2019), Chappel et al (2016), and Nadiroh and Arifianto (2018). We investigate the JND SD level over a range of conditions.…”

Section: Introductionmentioning

confidence: 99%

Spectral distortion level resulting in a just-noticeable difference between an a priori signal-to-noise ratio estimate and its instantaneous case

Nicolson

Paliwal

2020

The Journal of the Acoustical Society of America

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Minimum mean-square error (MMSE) approaches to speech enhancement are widely used in the literature. The quality of enhanced speech produced by an MMSE approach is directly impacted by the accuracy of the employed a priori signal-to-noise ratio (SNR) estimator. In this paper, the a priori SNR estimate spectral distortion (SD) level that results in a just-noticeable difference (JND) in the perceived quality of MMSE approach enhanced speech is found. The JND SD level is indicative of the accuracy that an a priori SNR estimator must exceed to have no impact on the perceived quality of MMSE approach enhanced speech. To measure the JND SD level, listening tests are conducted across five SNR levels, five noise sources, and two MMSE approaches [the MMSE short-time spectral amplitude (MMSE-STSA) estimator and the Wiener filter]. A statistical analysis of the results indicates that the JND SD level increases with the SNR level, is higher for the MMSE-STSA estimator, and is not impacted by the type of background noise. Following the literature, a significant improvement in a priori SNR estimation accuracy is required to reach the JND SD level. V

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Wearable pulmonary monitoring system with integrated functional lung imaging and chest sound recording: a clinical investigation in healthy subjects

Frerichs¹,

Paradiso

Kilintzis

et al. 2023

Physiol. Meas.

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Objective. Current wearable respiratory monitoring devices provide a basic assessment of the breathing pattern of the examined subjects. More complex monitoring is needed for healthcare applications in patients with lung diseases. A multi-sensor vest allowing continuous lung imaging by electrical impedance tomography (EIT) and auscultation at six chest locations was developed for such advanced application. The aims of our study were to determine the vest´s capacity to record the intended bio-signals, its safety and the comfort of wearing in a first clinical investigation in healthy adult subjects. Approach. Twenty subjects (age range: 23-65 years) were studied while wearing the vests during a 14-step study protocol comprising phases of quiet and deep breathing, slow and forced full expiration manoeuvres, coughing, breath-holding in seated and three horizontal postures. EIT, chest sound and accelerometer signals were streamed to a tablet using a dedicated application and uploaded to a back-end server. The subjects filled in a questionnaire on the vest properties using a Likert scale.Main results. All subjects completed the full protocol. Good to excellent EIT waveforms and functional EIT images were obtained in 89% of the subjects. Breathing pattern and posture dependent changes in ventilation distribution were properly detected by EIT. Chest sounds were recorded in all subjects. Detection of audible heart sounds was feasible in 44%-67% of the subjects, depending on the sensor location. Accelerometry correctly identified the posture in all subjects. The vests were safe and their properties positively rated, thermal and tactile properties achieved the highest scores. Significance. The functionality and safety of the studied wearable multi-sensor vest and the high level of its acceptance by the study participants were confirmed. Availability of personalized vests might further advance its performance by improving the sensor-skin contact.

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Perceptual evaluation of measures of spectral variance

Cited by 4 publications

References 32 publications

Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models

Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models

Spectral distortion level resulting in a just-noticeable difference between an a priori signal-to-noise ratio estimate and its instantaneous case

Wearable pulmonary monitoring system with integrated functional lung imaging and chest sound recording: a clinical investigation in healthy subjects

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