ORCID Profile
0000-0003-4467-8588
Current Organisation
Flinders University School of Medicine
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Publisher: American Thoracic Society
Date: 04-2022
Publisher: Oxford University Press (OUP)
Date: 04-03-2022
Abstract: To determine if a novel EEG-derived continuous index of sleep depth/alertness, the odds ratio product (ORP), predicts self-reported daytime sleepiness and poor sleep quality in two large population-based cohorts. ORP values which range from 0 (deep sleep) to 2.5 (fully alert) were calculated in 3s intervals during awake periods (ORPwake) and NREM sleep (ORPNREM) determined from home sleep studies in the HypnoLaus (N = 2162: 1106 females, 1056 males) and men androgen inflammation lifestyle environment and stress (MAILES) cohorts (N = 754 males). Logistic regression was used to examine associations between ORPwake, ORPNREM, and traditional polysomnography measures (as comparators) with excessive sleepiness (Epworth sleepiness scale & ) and poor sleep quality (Pittsburgh sleep quality index & ) and insomnia symptoms. High ORPwake was associated with a ~30% increase in poor sleep quality in both HypnoLaus (odds ratio, OR, and 95% CI) 1.28 (1.09, 1.51), and MAILES 1.36 (1.10, 1.68). High ORPwake was also associated with a ~28% decrease in excessive daytime sleepiness in the MAILES dataset. ORPNREM was associated with a ~30% increase in poor sleep quality in HypnoLaus but not in MAILES. No consistent associations across cohorts were detected using traditional polysomnography markers. ORP, a novel EEG-derived metric, measured during wake periods predicts poor sleep quality in two independent cohorts. Consistent with insomnia symptomatology of poor perceived sleep in the absence of excessive daytime sleepiness, ORPwake may provide valuable objective mechanistic insight into physiological hyperarousal.
Publisher: Acoustical Society of America (ASA)
Date: 08-2021
DOI: 10.1121/10.0005849
Abstract: This paper presents results from a one-year study of indoor annoyance and self-reported sleep times for two participants located near different wind farms. Continuous measurements of outdoor and indoor noise and meteorological conditions were taken at each location for the duration of the study. In at least 50% of the annoyance recordings, participants described noise as “swish” or “swoosh.” Furthermore, the majority of the annoyance recordings occurred at nighttime and in the early morning. The third quartile of A-weighted indoor sound pressure level [SPL(A)], between 27 and 31 dBA, was associated with an 88% increased probability of annoyance compared to the lowest reference quartile, which was between 12 and 22 dBA [odds ratio and 95% confidence intervals, 7.72 (2.61,22.8), p & 0.001]. The outdoor SPL(A) was also predictive of annoyance but only between 40 and 45 dBA. The outdoor prevalence of litude modulation (AM), defined as the percentage of time that AM was detectable by an algorithm for each annoyance period, was also associated with annoyance. Self-reported sleep efficiency (time spent asleep relative to time in bed available for sleep) was significantly associated with nighttime annoyance (β = −0.66, p = 0.02) but only explained a small fraction of the variance (R2 = 5%).
Publisher: Oxford University Press (OUP)
Date: 12-03-2021
Abstract: The primary aim of this study was to examine dose–response relationships between sound pressure levels (SPLs) and K-complex occurrence probability for wind farm and road traffic noise. A secondary aim was to compare K-complex dose–responses to manually scored electroencephalography arousals and awakenings. Twenty-five participants underwent polysomnography recordings and noise exposure during sleep in a laboratory. Wind farm and road traffic noise recordings of 20-sec duration were played in random order at 6 SPLs between 33 and 48 dBA during established N2 or deeper sleep. Noise periods were separated with periods of 23 dBA background noise. K-complexes were scored using a validated algorithm. K-complex occurrence probability was compared between noise types controlling for noise SPL, subjective noise sensitivity, and measured hearing acuity. Noise-induced K-complexes were observed in N2 sleep at SPLs as low as 33 dBA (Odds ratio, 33 dBA vs 23 dBA, mean (95% confidence interval) 1.75 (1.16, 2.66)) and increased with SPL. EEG arousals and awakenings were only associated with noise above 39 dBA in N2 sleep. K-complexes were 2 times more likely to occur in response to noise than EEG arousals or awakenings. Subjective noise sensitivity and hearing acuity were associated with the K-complex occurrence, but not arousal or awakening. Noise type did not detectably influence K-complexes, EEG arousals, or awakening responses. These findings support that K-complexes are a sensitive marker of sensory processing of environmental noise during sleep and that increased hearing acuity and decreased self-reported noise sensitivity increase K-complex probability.
Publisher: Elsevier BV
Date: 03-2023
Publisher: Elsevier BV
Date: 12-2021
Publisher: Oxford University Press (OUP)
Date: 29-01-2019
Abstract: Wind turbine noise (WTN) exposure could potentially interfere with the initiation of sleep. However, effects on objectively assessed sleep latency are largely unknown. This study sought to assess the impact of WTN on polysomnographically measured and sleep diary-determined sleep latency compared to control background noise alone in healthy good sleepers without habitual prior WTN exposure. Twenty-three WTN naïve urban residents (mean ± SD age: 21.7 ± 2.1 years, range 18–29, 13 females) attended the sleep laboratory for two polysomnography studies, one week apart. Participants were blind to noise conditions and only informed that they may or may not hear noise during each night. During the sleep onset period, participants were exposed to counterbalanced nights of WTN at 33 dB(A), the upper end of expected indoor values or background noise alone as the control condition (23 dB(A)). Linear mixed model analysis revealed no differences in log10 normalized objective or subjective sleep latency between the WTN versus control nights (median [interquartile range] objective 16.5 [11.0 to 18.5] vs. 16.5 [10.5 to 29.0] min, p = .401 subjective 20.0 [15.0 to 25.0] vs. 15.0 [10.0 to 30.0] min, p = .907). Although undetected small effects cannot be ruled out, these results do not support that WTN extends sleep latency in young urban-dwelling in iduals without prior WTN exposure.
Publisher: Elsevier BV
Date: 05-2016
Publisher: Elsevier BV
Date: 03-2023
Publisher: Oxford University Press (OUP)
Date: 2023
Publisher: Oxford University Press (OUP)
Date: 16-04-2020
Abstract: K-complexes (KCs) are a recognized electroencephalography marker of sensory processing and a defining feature of sleep stage 2. KC frequency and morphology may also be reflective of sleep quality, aging, and a range of sleep and sensory processing deficits. However, manual scoring of K-complexes is impractical, time-consuming, and thus costly and currently not well-standardized. Although automated KC detection methods have been developed, performance and uptake remain limited. The proposed algorithm is based on a deep neural network and Gaussian process, which gives the input waveform a probability of being a KC ranging from 0% to 100%. The algorithm was trained on half a million synthetic KCs derived from manually scored sleep stage 2 KCs from the Montreal Archive of Sleep Study containing 19 healthy young participants. Algorithm performance was subsequently assessed on 700 independent recordings from the Cleveland Family Study using sleep stages 2 and 3 data. The developed algorithm showed an F1 score (a measure of binary classification accuracy) of 0.78 and thus outperforms currently available KC scoring algorithms with F1 = 0.2–0.6. The probabilistic approach also captured expected variability in KC shape and litude within in iduals and across age groups. An automated probabilistic KC classification is well suited and effective for systematic KC detection for a more in-depth exploration of potential relationships between KCs during sleep and clinical outcomes such as health impacts and daytime symptomatology.
Publisher: Oxford University Press (OUP)
Date: 29-12-2022
Abstract: This study was designed to test the utility of cardiovascular responses as markers of potentially different environmental noise disruption effects of wind farm compared to traffic noise exposure during sleep. Twenty participants underwent polysomnography. In random order, and at six sound pressure levels from 33 dBA to 48 dBA in 3 dB increments, three types of wind farm and two types of road traffic noise recordings of 20-s duration were played during established N2 or deeper sleep, each separated by 20 s without noise. Each noise sequence also included a no-noise control. Electrocardiogram and finger pulse oximeter recorded pulse wave litude changes from the pre-noise onset baseline following each noise exposure and were assessed algorithmically to quantify the magnitude of heart rate and finger vasoconstriction responses to noise exposure. Higher sound pressure levels were more likely to induce drops in pulse wave litude. Sound pressure levels as low as 39 dBA evoked a pulse wave litude response (Odds ratio [95% confidence interval] 1.52 [1.15, 2.02]). Wind farm noise with litude modulation was less likely to evoke a pulse wave litude response than the other noise types, but warrants cautious interpretation given low numbers of replications within each noise type. These preliminary data support that drops in pulse wave litude are a particularly sensitive marker of noise-induced cardiovascular responses during. Larger trials are clearly warranted to further assess relationships between recurrent cardiovascular activation responses to environmental noise and potential long-term health effects.
Publisher: Springer Berlin Heidelberg
Date: 18-12-2015
Publisher: Acoustical Society of America (ASA)
Date: 09-2017
DOI: 10.1121/1.5003651
Abstract: Numerical simulations are used to investigate the noise generated by the passage of a rotor blade past a fixed object (the blade-passage effects), which was studied by simulating a three-bladed rotor that is supported by a vertical cylindrical tower. To isolate the blade-passage effects, no incoming wind was introduced in the simulation. The symmetric blade was set to zero pitch angle relative to the plane of rotation and two blade-tower distances were investigated. The sliding mesh method was used to simulate the rotation of the blades and Curle's acoustic analogy was used to predict the noise generated from the simulated flow data. Intense force fluctuations occur during the interaction on both the tower and the passing blade, and these are the primary sources of blade-passage noise. The contribution of the force fluctuations on the support tower to blade-passage noise, which previously had been ignored, was revealed to be more significant than that of the blades. The numerical model successfully predicts the noise spectra, which are validated by the very good agreement with experimental measurements. The simulations provide a framework to better understand blade–tower interaction noise in various applications.
Publisher: Springer Science and Business Media LLC
Date: 15-02-2018
Publisher: Institute of Noise Control Engineering (INCE)
Date: 03-2014
DOI: 10.3397/1/376207
Publisher: Wiley
Date: 12-11-2021
DOI: 10.1111/JSR.13228
Abstract: Little is known about the potential impacts of wind turbine noise (WTN) on sleep. Previous research is limited to cross‐sectional studies reporting anecdotal impacts on sleep using inconsistent sleep metrics. This meta‐analysis sought to comprehensively review studies evaluating the impact of WTN using widely accepted and validated objective and subjective sleep assessments. Search terms included: “wind farm noise”, “wind turbine noise”, “wind turbine sound”, “wind turbine noise exposure” AND “sleep”. Only original articles published in English published after the year 2000 and reporting sleep outcomes in the presence of WTN using polysomnography, actigraphy or psychometrically validated sleep questionnaires were included. Uniform outcomes of the retrieved studies were meta‐analysed to examine WTN effects on objective and subjective sleep outcomes. Nine studies were eligible for review and five studies were meta‐analysed. Meta‐analyses (Hedges’ g 95% confidence interval [CI]) revealed no significant differences in objective sleep onset latency (0.03, 95% CI −0.34 to 0.41), total sleep time (−0.05, 95% CI −0.77 to 0.67), sleep efficiency (−0.25, 95% CI −0.71 to 0.22) or wake after sleep onset (1.25, 95% CI −2.00 to 4.50) in the presence versus absence of WTN (all p .05). Subjective sleep estimates were not meta‐analysed because measurement outcomes were not sufficiently uniform for comparisons between studies. This systematic review and meta‐analysis suggests that WTN does not significantly impact key indicators of objective sleep. Cautious interpretation remains warranted given variable measurement methodologies, WTN interventions, limited s le sizes, and cross‐sectional study designs, where cause‐and‐effect relationships are uncertain. Well‐controlled experimental studies using ecologically valid WTN, objective and psychometrically validated sleep assessments are needed to provide conclusive evidence regarding WTN impacts on sleep.
Publisher: RWTH Aachen University
Date: 2019
Publisher: Acoustical Society of America (ASA)
Date: 05-2017
DOI: 10.1121/1.4983295
Abstract: Trailing edge noise from stationary and rotating NACA 0012 airfoils is characterised and compared with a noise prediction based on the semi-empirical Brooks, Pope, and Marcolini (BPM) model. The NACA 0012 is symmetrical airfoil with no camber and 12% thickness to chord length ratio. Acoustic measurements were conducted in an anechoic wind tunnel using a stationary NACA 0012 airfoil at 0° pitch angle. Airfoil self-noise emissions from rotating NACA 0012 airfoils mounted at 0° and 10° pitch angles on a rotor-rig are studied in an anechoic room. The measurements were carried out using microphone arrays for noise localisation and magnitude estimation using beamforming post-processing. Results show good agreement between peak radiating trailing edge noise emissions of stationary and rotating NACA 0012 airfoils in terms of the Strouhal number. Furthermore, it is shown that noise predictions based on the BPM model considering only two dimensional flow effects, are in good agreement with measurements for rotating airfoils, at these particular conditions.
Publisher: Acoustical Society of America (ASA)
Date: 04-2014
DOI: 10.1121/1.4877445
Abstract: A recently presented hypothesis and model relating to the generation of spinning modes from wind turbines, as a direct result of acoustic interaction involving the tower, results in a far field infrasound sound pressure level prediction, which is higher than that predicted by point source method. The model also predicts a significant attenuation of the fundamental blade passing frequency component relative to the second and higher harmonics. The model concurrently predicts a low frequency (~20 Hz), litude modulated harmonic series as a side effect of the acoustic interaction on a 1.6 MW 80 m diameter wind turbine. This study examines the model predictions of a 3.0 MW 90 m diameter wind turbine, and compares the predictions to measurements of the low frequency harmonic series and blade passing frequency harmonics at several different distances from the wind turbine.
Publisher: Acoustical Society of America (ASA)
Date: 05-2022
DOI: 10.1121/10.0010494
Abstract: This study proposes an approach for the characterisation and assessment of wind farm noise (WFN), which is based on extraction of acoustic features between 125 and 7500 Hz from a pretrained deep learning model (referred to as deep acoustic features). Using data measured at a variety of locations, this study shows that deep acoustic features can be linked to meaningful characteristics of the noise. This study finds that deep acoustic features can reveal an improved spatial and temporal representation of WFN compared to what is revealed using traditional spectral analysis and overall noise descriptors. These results showed that this approach is promising, and thus it could provide the basis for an improved framework for WFN assessment in the future.
Publisher: Acoustical Society of America (ASA)
Date: 12-2022
DOI: 10.1121/10.0016499
Abstract: This study tested for differences in perceived annoyance and loudness between road traffic noise (RTN) and wind farm noise (WFN) with litude modulation (AM) and tonality. Twenty-two participants, who were primarily university students with no previous exposure to WFN and aged between 19 and 29 (mean, 22 years old standard deviation, 2) years old with normal hearing, underwent a laboratory-based listening test. Each participant rated perceived annoyance and loudness of WFN and RTN s les played at sound pressure levels (SPLs) ranging from 33 to 48 dBA. Probability modeling revealed that participants were the largest source of variability in ratings of perceived annoyance and loudness while noise type and SPL were relatively minor sources. Overall, no differences were found between WFN and RTN perceived annoyance or loudness ratings. On the other hand, no substantial differences in annoyance were found between low-frequency tonal AM and mid-to-high-frequency AM or “swish” WFN.
Publisher: Elsevier BV
Date: 03-2019
Publisher: Elsevier BV
Date: 09-2019
Publisher: Oxford University Press (OUP)
Date: 14-04-2022
Abstract: Carefully controlled studies of wind turbine noise (WTN) and sleep are lacking, despite anecdotal complaints from some residents in wind farm areas and known detrimental effects of other noises on sleep. This laboratory-based study investigated the impact of overnight WTN exposure on objective and self-reported sleep outcomes. Sixty-eight participants (38 females) aged (mean ± SD) 49.2 ± 19.5 were recruited from four groups N = 14, living <10 km from a wind farm and reporting WTN related sleep disruption N = 18, living .05). These results do not support that WTN at 25 dB(A) impacts sleep outcomes in participants with or without prior WTN exposure or self-reported habitual noise-related sleep disruption. These findings do not rule out effects at higher noise exposure levels or potential effects of WTN on more sensitive markers of sleep disruption. ACTRN12619000501145, UTN U1111-1229-6126. Establishing the physiological and sleep disruption characteristics of noise disturbances in sleep. www.anzctr.org.au/. This study was prospectively registered on the Australian and New Zealand Clinical Trial Registry.
Publisher: Elsevier BV
Date: 12-2022
Publisher: Elsevier BV
Date: 12-2015
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 09-2020
Publisher: Wiley
Date: 13-11-2022
DOI: 10.1111/JSR.13517
Abstract: Wind turbine noise is dominated by low frequencies for which effects on sleep relative to more common environmental noise sources such as road traffic noise remain unknown. This study examined the effect of wind turbine noise compared with road traffic noise on sleep using quantitative electroencephalogram power spectral analysis. Twenty-three participants were exposed to 3-min s les of wind turbine noise and road traffic noise at three sound pressure levels (33, 38 and 43 dBA) in randomised order during established sleep. Acute (0-30 s) and more sustained (30-180 s) effects of noise presentations during N2 and N3 sleep were examined using spectral analysis of changes in electroencephalogram power frequency ranges across time in 5-s intervals. Both noise types produced time- and sound pressure level-dependent increases in electroencephalogram power, but with significant noise type by sound pressure level interactions in beta, alpha, theta and delta frequency bands (all p < 0.05). Wind turbine noise showed significantly lower delta, theta and beta activity immediately following noise onset compared with road traffic noise (all p < 0.05). However, alpha activity was higher for wind turbine noise played at lower sound pressure levels (33 dBA [p = 0.001] and 38 dBA [p = 0.003]) compared with traffic noise during N2 sleep. These findings support that spectral analyses show subtle effects of noise on sleep and that electroencephalogram changes following wind turbine noise and road traffic noise onset differ depending on sound pressure levels however, these effects were mostly transient and had little impact on conventionally scored sleep. Further studies are needed to establish if electroencephalogram changes associated with modest environmental noise exposures have significant impacts on sleep quality and next-day functioning.
Publisher: Springer Science and Business Media LLC
Date: 05-10-2017
Publisher: Elsevier BV
Date: 10-2019
Publisher: Springer Science and Business Media LLC
Date: 04-2018
Publisher: Elsevier BV
Date: 05-2023
Publisher: Elsevier BV
Date: 12-2019
Publisher: RWTH Aachen University
Date: 2019
Publisher: SAGE Publications
Date: 02-04-2020
Abstract: Survey results have shown that many respondents report to be annoyed by vibration, which they attribute to a wind farm. The aim of this work is to explore wind turbine vibration characteristics and evaluate its effects on humans. The vibration was measured on a bed frame, the floor and a window in three dwellings located 3.3, 5 and 2.4 km from two wind farms in South Australia. It was found that vibration on the window was wind farm related as it contained litude modulation. Vibration on the bed and floor was low and dominated by ambient vibration. Evaluation based on the AS 2670-2 (1990) and BS 6472-1 (2008) standards indicated that the vibration levels on the floor are unlikely to cause discomfort or adverse comment. Also, vibration can be associated with local wind speed and low-frequency noise meaning that wind-induced structural vibration could be erroneously attributed to a wind farm.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Branko Zajamsek.