The effects of white noise and swaddling methods on orogastric tube insertion-related pain in preterm infants: A randomized controlled trial.

AIM: This study aims to investigate the effects of the white noise, swaddling and white noise + swaddling methods on pain and physiological parameters associated with orogastric tube insertion procedure. METHODS: This was a randomized controlled trial. A total of 132 preterm infants were randomly assigned to four groups as white noise group (n = 33), swaddling group (n = 33), white noise + swaddling group (n = 33) and control group (n = 33). Interventions were initiated 5 min before the orogastric tube insertion procedure and continued during and up to 5 min after the procedure. RESULTS: White noise intervention alone did not have a significant effect on reducing pain associated with orogastric tube insertion (p > 0.05). Compared with the control group, the preterm infants in the swaddling group experienced 0.587 times less pain, and those in the white noise + swaddling group experienced 0.473 times less pain. CONCLUSIONS: Findings indicate the swaddling and the combination of white noise + swaddling may be a useful intervention in reducing the invasive pain experienced by preterm infants during and after orogastric tube insertion and in improving the physiological parameters associated with pain.

Higher exposure to 1,3-butadiene is associated with more severe hearing loss.

While volatile organic compounds (VOCs) impair various organs, their influence on hearing loss (HL) has not been extensively researched. We aimed to identify the association between VOCs and HL or high-frequency hearing loss (HFHL). We extracted data on age, sex, pure tone audiometry, hypertension, occupational noise exposure, and creatinine-corrected urine VOC metabolite concentrations from the eighth Korea National Health and Nutrition Survey. Among the VOC metabolites, N-acetyl-S-(benzyl)-L-cysteine (BMA, P = 0.004), N-acetyl-S-(phenyl)-L-cysteine (SPMA, P = 0.027), and N-acetyl-S-(3,4-dihydroxybutyl)-L-cysteine (DHBMA, P < 0.001) showed associations with HL. Additionally, HFHL exhibited significant associations with BMA (P = 0.005), 3- and 4-methylhippuric acid (3, 4 MHA, P = 0.049), mandelic acid (MA, P = 0.015), SPMA (P < 0.001), N-acetyl-S-(3-hydroxypropyl)-L-cysteine (3-HPMA, P < 0.001), and DHBMA (P < 0.001). After controlling other factors, DHBMA were associated with HL (P = 0.021) and HFHL (P = 0.014) and exhibited a linear association with the mean hearing level (ß = 0.054, P = 0.024) and high-frequency hearing level (ß = 0.045, P = 0.037). Since 1,3-butadiene may act as an ototoxic material, early screening for workers exposed to 1,3-butadiene and reducing exposure to 1,3-butadiene in everyday life may be helpful to prevent further HL.

A cross-sectional study on the correlation of image quality, effective dose, and body composition with thyroid, chest, and abdominal computed tomography scans.

Background: The rapid increase in the use of radiodiagnostic examinations in China, especially computed tomography (CT) scans, has led to these examinations being the largest artificial source of per capita effective dose (ED). This study conducted a retrospective analysis of the correlation between image quality, ED, and body composition in 540 cases that underwent thyroid, chest, or abdominal CT scans. The aim of this analysis was to evaluate the correlation between the parameters of CT scans and body composition in common positions of CT examination (thyroid, chest, and abdomen) and ultimately inform potential measures for reducing radiation exposure. Methods: This study included 540 patients admitted to Fudan University Shanghai Cancer Center from January 2015 to December 2019 who underwent both thyroid or chest or abdominal CT scan and body composition examination. Average CT values and standard deviation (SD) values were collected for the homogeneous areas of the thyroid, chest, or abdomen, and the average CT values and SD values of adjacent subcutaneous fat tissue were measured in the same region of interest (ROI). All data were measured three times, and the average was taken to calculate the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for each area. The dose-length product (DLP) was recorded, and the ED was calculated with the following: formula ED = k × DLP. Dual-energy X-ray was used to determine body composition and obtain indicators such as percentage of spinal and thigh muscle. Pearson correlation coefficient was used to analyze the correlations between body composition indicators, height, weight, body mass index (BMI), and ED. Results: The correlation coefficients between the SNR of abdominal CT scan and weight, BMI, and body surface area (BSA) were -0.470 (P=0.001), -0.485 (P=0.001), and -0.437 (P=0.002), representing a moderate correlation strength with statistically significant differences. The correlation coefficients between the ED of chest CT scans and weight, BMI, spinal fat percentage, and BSA were 0.488 (P=0.001), 0.473 (P=0.002), 0.422 (P=0.001), and 0.461 (P=0.003), respectively, indicating a moderate correlation strength with statistical differences. There was a weak statistically significant correlation between the SNR, CNR, and ED of the other scans with each physical and body composition index (P=0.023). Conclusions: There were varying degrees of correlation between CT image quality and ED and physical and body composition indices, which may inform novel solutions for reducing radiation exposure.

Comparative analysis of hearing loss caused by steady-state noise and impulse noise.

BACKGROUND: Varied noise environments, such as impulse noise and steady-state noise, may induce distinct patterns of hearing impairment among personnel exposed to prolonged noise. However, comparative studies on these effects remain limited. OBJECTIVE: This study aims to delineate the different characteristics of hearing loss in workers exposed to steady-state noise and impulse noise. METHODS: As of December 2020, 96 workers exposed to steady-state noise and 177 workers exposed to impulse noise were assessed. Hearing loss across various frequencies was measured using pure tone audiometry and distortion product otoacoustic emission (DPOAE) audiometry. RESULTS: Both groups of workers exposed to steady-state noise and impulse noise exhibited high frequencies hearing loss. The steady-state noise group displayed significantly greater hearing loss at lower frequencies in the early stages, spanning 1- 5 years of work (P < 0.05). Among individuals exposed to impulse noise for extended periods (over 10 years), the observed hearing loss surpassed that of the steady-state noise group, displaying a statistically significant difference (P < 0.05). CONCLUSION: Hearing loss resulting from both steady-state noise and impulse noise predominantly occurs at high frequencies. Early exposure to steady-state noise induces more pronounced hearing loss at speech frequencies compared to impulse noise.

Relationship Between Work-Related Noise Exposure and Cognitive Impairment: A Cross-Sectional Study in China.

Background: Noise exposure and the risk of cognitive impairment are currently major public health issues. Objective: This study aimed to analyze the relationship between noise exposure and early impairment of cognitive function from the perspective of occupational epidemiology and to provide evidence for the long-term prevention and treatment of dementia in the context of aging. Methods: This study was conducted in China between May and August 2021. The independent variables were the type of hazardous factors, duration of noise exposure, perceived noise intensity, and cumulative noise exposure (CNE). The dependent variable was cognitive function, which was measured using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Multiple linear and logistic regression were used to analyze the relationship between noise exposure and cognitive function and to establish an effect curve. Results: The detection rates of cognitive dysfunction using the MMSE and MoCA were 1.1% and 36.2%, respectively. The predicted MMSE and MoCA scores showed a downward trend within the CNE value ranging from 90-140 dB.time. Each unit increase in CNE decreased cognitive function scores by 0.025 (0.037, 0.013) and 0.020 (0.037, 0.003) points,respectively. Conclusions: From the perspective of occupational epidemiology, these findings reveal a potential link between long-term noise exposure and early cognitive impairment.

Minimizing Contact Resistance and Flicker Noise in Micro Graphene Hall Sensors Using Persistent Carbene Modified Gold Electrodes.

Scalable micro graphene Hall sensors (µGHSs) hold tremendous potential for highly sensitive and label-free biomagnetic sensing in physiological solutions. To enhance the performance of these devices, it is crucial to optimize frequency-dependent flicker noise to reduce the limit of detection (LOD), but it remains a great challenge due to the large contact resistance at the graphene-metal contact. Here we present a surface modification strategy employing persistent carbene on gold electrodes to reduce the contact resistivity by a factor of 25, greatly diminishing µGHS flicker noise by a factor of 1000 to 3.13 × 10-14 V2/Hz while simultaneously lowering the magnetic LOD SB1/2 to 1440 nT/Hz1/2 at 1 kHz under a 100 µA bias current. To the best of our knowledge, this represents the lowest SB1/2 reported for scalable µGHSs fabricated through wafer-scale photolithography. The reduction in contact noise is attributed to the π-π stacking interaction between the graphene and the benzene rings of persistent carbene, as well as the decrease in the work function of gold as confirmed by Kelvin Probe Force Microscopy. By incorporating a microcoil into the µGHS, we have demonstrated the real-time detection of superparamagnetic nanoparticles (SNPs), achieving a remarkable LOD of ∼528 µg/L. This advancement holds great potential for the label-free detection of magnetic biomarkers, e.g., ferritin, for the early diagnosis of diseases associated with iron overload, such as hereditary hemochromatosis (HHC).

Advancing noise management in aviation: Strategic approaches for preventing noise-induced hearing loss.

As urbanization and population growth escalate, the challenge of noise pollution intensifies, particularly within the aviation industry. This review examines current insights into noise-induced hearing loss (NIHL) in aviation, highlighting the risks to pilots, cabin crew, aircraft maintenance engineers, and ground staff from continuous exposure to high-level noise. It evaluates existing noise management and hearing conservation strategies, identifying key obstacles and exploring new technological solutions. While progress in developing protective devices and noise control technologies is evident, gaps in their widespread implementation persist. The study underscores the need for an integrated strategy combining regulatory compliance, technological advances, and targeted educational efforts. It advocates for global collaboration and policy development to safeguard the auditory health of aviation workers and proposes a strategic framework to enhance hearing conservation practices within the unique challenges of the aviation sector.

A periodic-modulation-oriented noise resistant correlation method for industrial fault diagnostics of rotating machinery under the circumstances of limited system signal availability.

The periodical impulses caused by localized defects of components are the vital characteristic information for fault detection and diagnosis of rotating machines. In recent years, multitudinous spectrum analysis-based signal processing methods have been developed and authenticated as the powerful tools for excavating fault-related repetitive transients from the measured complex signals. Nonetheless, in practice, their applications can be severely confined by the constraints of limited system signal availability and incomplete information extraction under intricate noise interferences. To tackle the aforementioned issues, this paper proposes a periodic-modulation-oriented noise resistant correlation (PMONRC) method for target period detection and fault diagnosis of rotating machinery. Firstly, the envelope of raw signal is obtained via a novel sequential procedure of signal element-wise squaring, spectral Gini index-guided adaptive low-pass filtering, and signal element-wise square root computation, to highlight the modulated wave component that is more likely to be related to the potential fault-induced periods. Subsequently, a series of sub-signals, which can encode the fault-related repetitive information and enhance noise resistance, are constructed utilizing the envelope signal. Based upon the envelope signal and the obtained sub-signals, a weighted envelope noise resistant correlation function can be derived with the assistance of the L-moment ratio-based indicator and Sigmoid transformation. Finally, the specific fault type of the rotating machinery can be identified and affirmed accordingly. The proposed PMONRC method, which is nonparametric and completely adaptive to the signal being processed itself, overcomes the deficiencies of spectral analysis-based approaches, and is applicable for the engineering circumstances of system signal limitation and low signal-to-noise ratio (SNR), possessing immense practical merit. Both simulation analyses and experimental validations profoundly demonstrate that the proposed method is superior to other existing state-of-the-art time-domain correlation methods. Moreover, as an attempt as well as exemplar to apply this method, the PMONRC-based incipient fault diagnostic results of rolling bearing data from the well-known experimental platform PRONOSTIA are presented and discussed as well, to further elucidate the effectiveness and practical engineering significance of the proposed method.

Active disturbance rejection control based on a cascade estimator composed of reduced-order and full-order extended state observers.

This paper presents a pioneering cascade estimator, CRESO, which merges reduced-order and full-order extended state observers (ESO) in a novel manner. CRESO is designed to navigate the trade-off between robustness, estimation accuracy, and noise amplification inherent in active disturbance rejection control (ADRC) schemes. An analysis in the frequency domain substantiates CRESO's performance and robustness capabilities compared to those of single-level ESO and cascade ESO (CESO). These features are quantified using practical metrics, such as stability margins, sensitivity bandwidth, and estimation error at low frequencies. Additionally, the discussion encompasses the impact of selecting bandwidths for the cascade levels of CRESO on noise suppression. Experimental validation on a synchronous buck converter demonstrates the effectiveness of CRESO-based ADRC against control gain uncertainties, frequency-varying external disturbances, and sensor noise. The results highlight the advantages of the proposed approach over ADRC strategies employing singular ESO, two-level CESO, and two independent ESOs, as evidenced by several quality indices derived from the tracking errors and control signals.

Ultralow-Noise MoS2/Type II Superlattice Mixed-Dimensional van der Waals Barrier Long-Wave Infrared Detector.

Low-noise, high-performance long-wave infrared detectors play a crucial role in diverse applications, including in the industrial, security, and medical fields. However, the current performance of long-wave detectors is constrained by the noise associated with narrow bandgaps. Therefore, exploring novel heterostructures for long-wavelength infrared detection is advantageous for the development of compact and high-performance infrared sensing. In this investigation, we present a MoS2/type II superlattice mixed-dimensional van der Waals barrier long-wave infrared detector (Mixed-vdWH). Through the design of the valence band barrier, substantial suppression of device dark noise is achieved, resulting in 2 orders of magnitude reduction in dark current. The device exhibits outstanding performance, with D* reaching 4 × 1010 Jones. This integration approach synergizes the distinctive properties of two-dimensional layered materials (2DLM) with the well-established processing techniques of traditional three-dimensional semiconductor materials, offering a compelling avenue for the large-scale integration of 2DLM.

Modeling correlated uncertainties in stochastic compartmental models.

We consider compartmental models of communicable disease with uncertain contact rates. Stochastic fluctuations are often added to the contact rate to account for uncertainties. White noise, which is the typical choice for the fluctuations, leads to significant underestimation of the disease severity. Here, starting from reasonable assumptions on the social behavior of individuals, we model the contacts as a Markov process which takes into account the temporal correlations present in human social activities. Consequently, we show that the mean-reverting Ornstein-Uhlenbeck (OU) process is the correct model for the stochastic contact rate. We demonstrate the implication of our model on two examples: a Susceptibles-Infected-Susceptibles (SIS) model and a Susceptibles-Exposed-Infected-Removed (SEIR) model of the COVID-19 pandemic and compare the results to the available US data from the Johns Hopkins University database. In particular, we observe that both compartmental models with white noise uncertainties undergo transitions that lead to the systematic underestimation of the spread of the disease. In contrast, modeling the contact rate with the OU process significantly hinders such unrealistic noise-induced transitions. For the SIS model, we derive its stationary probability density analytically, for both white and correlated noise. This allows us to give a complete description of the model's asymptotic behavior as a function of its bifurcation parameters, i.e., the basic reproduction number, noise intensity, and correlation time. For the SEIR model, where the probability density is not available in closed form, we study the transitions using Monte Carlo simulations. Our modeling approach can be used to quantify uncertain parameters in a broad range of biological systems.

Water, Soil, Noise, and Light Pollution: JACC Focus Seminar, Part 2.

Various forms of pollution carry a substantial burden with respect to increasing the risk of causing and exacerbating noncommunicable diseases, especially cardiovascular disease. The first part of this 2-part series on pollution and cardiovascular disease provided an overview of the impact of global warming and air pollution. This second paper provides an overview of the impact of water, soil, noise, and light pollution on the cardiovascular system. This review discusses the biological mechanisms underlying these effects and potential environmental biometrics of exposure. What is clear from both these pollution papers is that significant efforts and redoubled urgency are needed to reduce the sources of pollution in our environment, to incorporate environmental risk factors into medical education, to provide resources for research, and, ultimately, to protect those who are particularly vulnerable and susceptible.

Environmentally Not So Friendly: Global Warming, Air Pollution, and Wildfires: JACC Focus Seminar, Part 1.

Environmental stresses are increasingly recognized as significant risk factors for adverse health outcomes. In particular, various forms of pollution and climate change are playing a growing role in promoting noncommunicable diseases, especially cardiovascular disease. Given recent trends, global warming and air pollution are now associated with substantial cardiovascular morbidity and mortality. As a vicious cycle, global warming increases the occurrence, size, and severity of wildfires, which are significant sources of airborne particulate matter. Exposure to wildfire smoke is associated with cardiovascular disease, and these effects are underpinned by mechanisms that include oxidative stress, inflammation, impaired cardiac function, and proatherosclerotic effects in the circulation. In the first part of a 2-part series on pollution and cardiovascular disease, this review provides an overview of the impact of global warming and air pollution, and because of recent events and emerging trends specific attention is paid to air pollution caused by wildfires.

Investigating the effects of underwater noise from two vessels on the behaviour of short-finned pilot whales.

Multiple whale-watching vessels may operate around cetaceans at any one time, and targeted animals may experience underwater noise effects. We hypothesised that the cumulative noise of two vessels with low source levels (SLs) will elicit lower behavioural disturbance in short-finned pilot whales (Globicephala macrorhynchus) compared to a single vessel with a higher SL. We measured the behaviour of whales during 26 controls (stationary vessel >300 m) and 44 treatments off Tenerife (Canary Islands, Spain). Treatments consisted of vessel approaches mimicking whale-watch scenarios (distance ∼60 m, speed 1.5 kn). Approaches with two simultaneous vessels, with maximum cumulative mid and low-frequency (0.2-110 kHz) weighted source levels (SLsMF-LF) 137-143 dB, did not affect mother-calf pairs' resting, nursing, diving, respiration rate or inter-breath interval. However, a louder single vessel approach with twin petrol engines at SLsMF-LF 139-151 dB significantly decreased the proportion of time resting for the mother. The results suggest that if a single or two vessels are present, if the cumulative SL is < 143 dB, the behavioural disturbance on the whales will be negligible. By examining noise effects from multiple vessels on the behaviour of pilot whales, the importance of incorporating a noise threshold into whale-watching guidelines was emphasised.

Machine-learning based detection of marine mammal vocalizations in snapping-shrimp dominated ambient noise.

Passive acoustics is an effective method for monitoring marine mammals, facilitating both detection and population estimation. In warm tropical waters, this technique encounters challenges due to the high persistent level of ambient impulsive noise originating from the snapping shrimp present throughout this region. This study presents the development and application of a neural-network based detector for marine-mammal vocalizations in long term acoustic data recorded by us at ten locations in Singapore waters. The detector's performance is observed to be impeded by the high shrimp noise activity. To counteract this, we investigate several techniques to improve detection capabilities in shrimp noise including the use of simple nonlinear denoisers and a machine-learning based denoiser. These are shown to enhance the detection performance significantly. Finally, we discuss some of the vocalizations detected over three years of our acoustic recorder deployments using the robust detectors developed.

A genome-wide association study reveals a polygenic architecture of speech-in-noise deficits in individuals with self-reported normal hearing.

Speech-in-noise (SIN) perception is a primary complaint of individuals with audiometric hearing loss. SIN performance varies drastically, even among individuals with normal hearing. The present genome-wide association study (GWAS) investigated the genetic basis of SIN deficits in individuals with self-reported normal hearing in quiet situations. GWAS was performed on 279,911 individuals from the UB Biobank cohort, with 58,847 reporting SIN deficits despite reporting normal hearing in quiet. GWAS identified 996 single nucleotide polymorphisms (SNPs), achieving significance (p < 5*10-8) across four genomic loci. 720 SNPs across 21 loci achieved suggestive significance (p < 10-6). GWAS signals were enriched in brain tissues, such as the anterior cingulate cortex, dorsolateral prefrontal cortex, entorhinal cortex, frontal cortex, hippocampus, and inferior temporal cortex. Cochlear cell types revealed no significant association with SIN deficits. SIN deficits were associated with various health traits, including neuropsychiatric, sensory, cognitive, metabolic, cardiovascular, and inflammatory conditions. A replication analysis was conducted on 242 healthy young adults. Self-reported speech perception, hearing thresholds (0.25-16 kHz), and distortion product otoacoustic emissions (1-16 kHz) were utilized for the replication analysis. 73 SNPs were replicated with a self-reported speech perception measure. 211 SNPs were replicated with at least one and 66 with at least two audiological measures. 12 SNPs near or within MAPT, GRM3, and HLA-DQA1 were replicated for all audiological measures. The present study highlighted a polygenic architecture underlying SIN deficits in individuals with self-reported normal hearing.

Association between exposure to metalworking fluid aerosols, occupational noise and chronic kidney disease: a cross-sectional study in China.

BACKGROUND: Chronic kidney disease (CKD) carries a high public health burden yet little is known about the relationship between metalworking fluid (MWF) aerosols, occupational noise and CKD. We aimed to explore the relationship between occupational MWF aerosols, occupational noise and CKD. METHODS: A total of 2,738 machinists were sampled from three machining companies in Wuxi, China, in 2022. We used the National Institute for Occupational Safety and Health (NIOSH) method 5524 to collect individual samples for MWF aerosols exposure, and the Chinese national standard (GBZ/T 189.8-2007) method to test individual occupational noise exposure. The diagnostic criteria for CKD were urinary albumin/creatinine ratio (UACR) of ≥ 30 mg/g and reduced renal function (eGFR < 60 mL.min- 1. 1.73 m- 2) lasting longer than 3 months. Smooth curve fitting was conducted to analyze the associations of MWF aerosols and occupational noise with CKD. A segmented regression model was used to analyze the threshold effects. RESULTS: Workers exposed to MWF aerosols (odds ratio [OR] = 2.03, 95% confidence interval [CI]: 1.21-3.41) and occupational noise (OR = 1.77, 95%CI: 1.06-2.96) had higher prevalence of CKD than nonexposed workers. A nonlinear and positive association was found between increasing MWF aerosols and occupational noise dose and the risk of CKD. When daily cumulative exposure dose of MWF aerosols exceeded 8.03 mg/m3, the OR was 1.24 (95%CI: 1.03-1.58), and when occupational noise exceeded 87.22 dB(A), the OR was 1.16 (95%CI: 1.04-1.20). In the interactive analysis between MWF aerosols and occupational noise, the workers exposed to both MWF aerosols (cumulative exposure ≥ 8.03 mg/m3-day) and occupational noise (LEX,8 h ≥ 87.22 dB(A)) had an increased prevalence of CKD (OR = 2.71, 95%CI: 1.48-4.96). MWF aerosols and occupational noise had a positive interaction in prevalence of CKD. CONCLUSIONS: Occupational MWF aerosols and noise were positively and nonlinearly associated with CKD, and cumulative MWF aerosols and noise exposure showed a positive interaction with CKD. These findings emphasize the importance of assessing kidney function of workers exposed to MWF aerosols and occupational noise. Prospective and longitudinal cohort studies are necessary to elucidate the causality of these associations.

Probing a neural unreliability account of auditory sensory processing atypicalities in Rett Syndrome.

BACKGROUND: In the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is "stationarity" of the underlying responses - i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this will significantly impact the validity of assumptions about underlying neural dysfunction, and likely lead to overestimation of underlying neuropathology. To assess this possibility, analyses at the single-trial level assessing signal-to-noise ratios (SNR), inter-trial variability (ITV) and inter-trial phase coherence (ITPC) are necessary. METHODS: AEPs were recorded to simple 100 Hz tones from 18 RTT and 27 age-matched controls (Ages: 6-22 years). We applied standard AEP averaging, as well as measures of neuronal reliability at the single-trial level (i.e. SNR, ITV, ITPC). To separate signal-carrying components from non-neural noise sources, we also applied a denoising source separation (DSS) algorithm and then repeated the reliability measures. RESULTS: Substantially increased ITV, lower SNRs, and reduced ITPC were observed in auditory responses of RTT participants, supporting a "neural unreliability" account. Application of the DSS technique made it clear that non-neural noise sources contribute to overestimation of the extent of processing deficits in RTT. Post-DSS, ITV measures were substantially reduced, so much so that pre-DSS ITV differences between RTT and TD populations were no longer detected. In the case of SNR and ITPC, DSS substantially improved these estimates in the RTT population, but robust differences between RTT and TD were still fully evident. CONCLUSIONS: To accurately represent the degree of neural dysfunction in RTT using the ERP technique, a consideration of response reliability at the single-trial level is highly advised. Non-neural sources of noise lead to overestimation of the degree of pathological processing in RTT, and denoising source separation techniques during signal processing substantially ameliorate this issue.

Modeling the Intelligibility Benefit of Active Noise Cancelation in Hearing Devices That Improve Signal-to-Noise Ratio.

The extent to which active noise cancelation (ANC), when combined with hearing assistance, can improve speech intelligibility in noise is not well understood. One possible source of benefit is ANC's ability to reduce the sound level of the direct (i.e., vent-transmitted) path. This reduction lowers the "floor" imposed by the direct path, thereby allowing any increases to the signal-to-noise ratio (SNR) created in the amplified path to be "realized" at the eardrum. Here we used a modeling approach to estimate this benefit. We compared pairs of simulated hearing aids that differ only in terms of their ability to provide ANC and computed intelligibility metrics on their outputs. The difference in metric scores between simulated devices is termed the "ANC Benefit." These simulations show that ANC Benefit increases as (1) the environmental sound level increases, (2) the ability of the hearing aid to improve SNR increases, (3) the strength of the ANC increases, and (4) the hearing loss severity decreases. The predicted size of the ANC Benefit can be substantial. For a moderate hearing loss, the model predicts improvement in intelligibility metrics of >30% when environments are moderately loud (>70 dB SPL) and devices are moderately capable of increasing SNR (by >4 dB). It appears that ANC can be a critical ingredient in hearing devices that attempt to improve SNR in loud environments. ANC will become more and more important as advanced SNR-improving algorithms (e.g., artificial intelligence speech enhancement) are included in hearing devices.