Noise Stress Research Articles

Transcriptomic and Behavioral Studies of Small Yellow Croaker (Larimichthyspolyactis) in Response to Noise Exposure.

Simple SummaryOcean noise pollution from marine traffic may affect the behavioral, ecological and biochemical parameters of marine fish species. Most studies have focused on behavioral changes and hearing damage in fishes, but the molecular mechanism of noise exposure in the impairment of the brain has rarely been reported. In this study, using small yellow croaker (L. polyactis) as a model, we used RNA-seq methods to characterize differently expressed genes between the control group and the noise exposure group. GO and KEGG pathway analysis found that synaptic transmission, neurotransmitter transport, endocytosis procession, cell adhesion molecules and the extracellular matrix receptor interaction pathway were over-represented in the DEGs. In addition, behavioral studies revealed that L. polyactis kept motionless on the surface of the water and lost the ability to keep their balance after noise exposure. Collectively, our results indicate that exposure to noise stressors contributes to neurological dysfunction in the brain and impaired locomotor ability in L. polyactis.Noise has the potential to induce physiological stress in marine fishes, which may lead to all sorts of ecological consequences. In the current study, we used the RNA-sequencing (RNA-seq) method to sequence the whole transcriptome of the brain in small yellow croaker (Larimichthys polyactis). The animals were exposed to a mix of noises produced by different types of boat played back in a tank, then the brain tissues were collected after the fish had been exposed to a 120 dB noise for 0.5 h. In total, 762 differently expressed genes (DEGs) between the two groups were identified, including 157 up regulated and 605 down regulated genes in the noise exposure group compared with the control group. Gene ontology (GO) enrichment analysis indicated that the most up regulated gene categories included synaptic membranes, receptor-mediated endocytosis and the neurotransmitter secretion process. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways found that endocytosis, cell adhesion molecules and the extracellular matrix (ECM) receptor interaction pathway were over-represented. Specifically, ECM-related genes, including lamin2, lamin3, lamin4, coll1a2, coll5a1 and col4a5 were down regulated in the noise exposure group, implying the impaired composition of the ECM. In addition, the behavioral experiment revealed that L. polyactis exhibited avoidance behaviors to run away from the noise source at the beginning of the noise exposure period. At the end of the noise exposure period, L. polyactis kept motionless on the surface of the water and lost the ability to keep their balance. Taken together, our results indicate that exposure to noise stress contributes to neurological dysfunction in the brain and impaired locomotor ability in L. polyactis.

Electromyography Parameter Variations with Electrocardiography Noise

Electromyograms (EMG signals) may be contaminated by electrocardiographic (ECG) signals that cannot be easily separated with traditional filters, because both signals have some overlapping spectral components. Therefore, the first challenge encountered in signal processing is to extract the ECG noise from the EMG signal. In this study, the EMG, mixed with different degrees of noise (ECG), is simulated to investigate the variations of the EMG features. Simulated data were derived from the MIT-BIH Noise Stress Test (NSTD) Database. Two EMG and four ECG data were composed with four EMG/ECG SNR to 32 simulated signals. Following Pan-Tompkins R-peak detection, four ECG removal methods were used to remove ECG with different compensation algorithms to obtain the denoised EMG signal. A total of 13 time-domain and four frequency-domain EMG features were calculated from the denoised EMG. In addition, the similarity of denoised EMG features compared to clean EMG was also evaluated. Our results showed that with the ratio EMG/ECG SNR = 10 and 20, the ECG can be almost ignored, and the similarity of EMG features is close to 1. When EMG/ECG SNR = 1 and 2, there is a large variation of EMG features. The results of our simulation study would be beneficial for understanding the variations of EMG features upon the different EMG/ECG SNR.

A Stochastic Resonance Electrocardiogram Enhancement Algorithm for Robust QRS Detection.

This study presents a new QRS detection algorithm making use of the background noise that is inevitably present in electrocardiogram (ECG) recordings. The algorithm suppresses noise, enhances the QRS-waves, and applies a threshold for QRS detection. Noise suppression and QRS enhancement are performed by a band-pass filter stage followed by a nonlinear stage based on the interaction of a particle inside an underdamped monostable potential well. The nonlinear stage maximizes the output when there is a QRS-wave and minimizes the output otherwise. One of the instruments that the nonlinear stage uses to enhance the QRS-waves is stochastic resonance, where the output is maximized for a non-zero intensity background noise. In terms of QRS-wave detection F1 score, which ranges from 98.87% to 99.99% on four major benchmarking databases (MIT-BIH Arrhythmia, QT, European ST-T, and MIT-BIH Noise Stress Test), the algorithm outperforms all existing ECG processing algorithms. The study, for the first time, demonstrates QRS-enhancement by facilitating stochastic resonance while suppressing in-band noise of ECG signals. Detecting QRS-waves as the ECG data streams, having a complexity of O(n), and not requiring any training data make the algorithm convenient for real-time ECG monitoring applications with limited computational resources.

Effect of increasing physical workload and environmental noise exposure on physiological stress among textile industry workers in the CARE covid-19

In June-September 2021, Surakarta experienced a long dry season as a result of global climate change, creating high temperatures that interfere with working comfort. In the textile industry, these conditions can make the workplace hotter than usual. In addition, the presence of very high noise and increased physical workload can trigger physiological stress events for weaving workers. The Community Activities Restrictions Enforcement (CARE) throughout Indonesia, restriction of people's movement to daily work, especially for unvaccinated workers. This condition has an impact on the activities of the textile industry sector, restrictions on the number of workers, trigger a shortage of manpower, forcing available workers to carry out more overtime to get the company's production targets. The increase in overtime causes workers to experience an increase in physical workload than usual. This study is to investigate the direct impact of this phenomenon and corrective action analysis can be carried out. This cross-sectional study included 47 workers of the weaving section in IT Co. Ltd Surakarta, Indonesia using a sound level meter and fitness tracker to measured physical workload, environmental noise, and physiological stress. This study showed physical workload (p=0.005, r=0.745) and environmental noise exposure (p=0.021, r=0,886) has a significant correlation toward physiological stress. Noise and workload control by using a hierarchy of control are urgently needed to reduce the incidence of physiological stress in the workplace.

A Novel ECG Denoising Scheme Using the Ensemble Kalman Filter.

Monitoring of electrocardiogram (ECG) provides vital information as well as any cardiovascular anomalies. Recent advances in the technology of wearable electronics have enabled compact devices to acquire personal physiological signals in the home setting; however, signals are usually contaminated with high level noise. Thus, an efficient ECG filtering scheme is a dire need. In this paper, a novel method using Ensemble Kalman Filter (EnKF) is developed for denoising ECG signals. We also intensively explore various filtering algorithms, including Savitzky-Golay (SG) filter, Ensemble Empirical mode decomposition (EEMD), Normalized Least-Mean-Square (NLMS), Recursive least squares (RLS) filter, Total variation denoising (TVD), Wavelet and extended Kalman filter (EKF) for comparison. Data from the MIT-BIH Noise Stress Test database were used. The proposed methodology shows the average signal to noise ratio (SNR) of 10.96, the Percentage Root Difference of 150.45, and the correlation coefficient of 0.959 from the modified MIT-BIH database with added motion artifacts.

Muscle Artifact Removal in Single-Channel Electrocardiograms using Temporal Convolutional Networks.

The electrocardiogram (ECG) is a vital diagnostic tool used in many health applications. In practice, interference by muscle artifacts is very common and may significantly complicate interpretation of the ECG waveform. In this work we investigate the removal of muscle artifacts in single-channel ECG signals using neural network models. To this end, we compare two neural network architectures which were previously used for ECG denoising and propose a novel third method based on the ConvTasNet. The neural networks are trained on simulated data using artificial mixtures of single-channel ECG (lead II) and surface EMG signals taken from publicly available datasets. ECG data were sampled from the MIT-BIH Arrhythmia and the PTB-XL database. The former provides recordings of ambulatory ECGs while the latter contains a large variety of cardiac pathologies recorded in a clinical setting. The muscle artifacts were sampled from the MIT-BIH Noise Stress Test database and the TaiChi database. In the past, most denoising methods were only tested on the two smaller MIT-BIH datasets. In this work, we report performances on larger datasets and thus provide stronger evidence for a clinical use-case. We also report out-of distribution performance of the three methods by switching the ECG dataset between training and test. The herein investigated variant of the ConvTasNet substantially reduces interference by muscle artifacts, outperforms state-of-the-art methods and thus, may support clinical decision making.

Channel-Wise Average Pooling and 1D Pixel-Shuffle Denoising Autoencoder for Electrode Motion Artifact Removal in ECG

This paper presents a channel-wise average pooling and one dimension pixel-shuffle architecture for a denoising autoencoder (CPDAE) design that can be applied to efficiently remove electrode motion (EM) artifacts in an electrocardiogram (ECG) signal. The three advantages of the proposed design are as follows: (1) In the skip connection layer, less memory is needed to transfer the features extracted by the neural network; (2) Pixel shuffle and pixel unshuffle techniques with point-wise convolution are used to effectively reserve the key features generated from each layer in both the encoder and decoder; (3) Overall, fewer parameters are required to reconstruct the ECG signal. This paper describes three deep neural network models, namely CPDAELite, CPDAERegular, and CPDAEFull, which support various computational capacity and hardware arrangements. The three proposed structures involve an encoder and decoder with six, seven, and eight layers, respectively. Furthermore, the CPDAELite, CPDAERegular, and CPDAEFull structures require fewer multiply-accumulate operations—355.01, 56.96, and 14.69 million, respectively—and less parameter usage—2.69 million, 149.7 thousand, and 55.5 thousand, respectively. To evaluate the denoising performance, the MIT–BIH noise stress test database containing six signal-to-noise ratios (SNRs) of noisy ECGs was employed. The results demonstrated that the proposed models had a higher improvement of SNR and lower percentage root-mean-square difference than other state-of-the-art methods under various conditions of SNR.

Nanocurcumin substantially alleviates noise stress-induced anxiety-like behavior: The roles of tight junctions and NMDA receptors in the hippocampus

Environmental noise stress affects non-auditory brain regions such as the hippocampus; an area of the brain implicated in cognition and emotion. Recent experimental data indicate that dysfunction of the blood-brain barrier (BBB) and overexpression of NMDA receptors may cause anxiety. In this experiment, we evaluated the effect of nanocurcumin on anxiety-like behavior and the expression of tight junctions and NMDA receptor subunits in the hippocampus of rats exposed to traffic noise. Forty rats were assigned to control (CON), stress (ST), nanocurcumin (NC), and nanocurcumin+stress (NC+ST) groups. Anxiety-like behavior was evaluated through an elevated zero maze apparatus. The gene expression of tight junctions and NMDA receptor subunits was examined by real-time PCR in the hippocampus. Statistical analysis showed that noise exposure developed anxiety-like behavior and elevated the corticosterone level in the ST group compared to the CON group. The nanocurcumin administration decreased the stress and anxiety in the NC+ST group compared to the ST animals. While the noise stress reduced the gene expression of tight junctions occludin, claudin-5, and ZO-1, the nanocurcumin administration increased them in the NC+ST animals. Furthermore, the noise stress elevated the gene expression of the NMDA receptor subunits GRIN1 and GRIN2B. The NC+ST animals showed a modification of these subunits compared to the ST animals. Our findings showed that noise exposure promotes stress and anxiety and impairs the NMDA receptor structure and BBB integrity. The nanocurcumin treatment partly restores the destructive effects of noise exposure.

Gas compressor noise does not influence tree swallow nestling condition or immune response

AbstractAnthropogenic noise pollution, such as that derived from traffic and industrial machinery, has been identified as an urgent conservation priority as it is often louder and more prevalent than natural acoustic stimuli, and can act as a stressor on wildlife. Research in avian systems has shown that anthropogenic noise can affect physiology and reproductive success of adult birds – but effects on juvenile birds have been less‐studied despite their being potentially more vulnerable during the nestling period. What studies have been done have shown remarkable variability in juvenile response to anthropogenic noise, suggesting that effects are highly context‐ and species‐specific. Here, we investigate the effects of gas compressor noise, an increasingly prevalent and biologically relevant noise stressor produced during natural gas production, on juvenile tree swallows (Tachycineta bicolor). Gas compressors generate considerable sound pressure as they work to pressurize gas pipelines for downstream distribution. We predicted that exposure to increased noise during incubation and the nestling period would result in smaller chicks in poorer body condition and with a dampened immune response. Surprisingly, we found no evidence for any of these predictions, providing further evidence that noise effects on juvenile birds is highly variable, and we explore ways in which individual birds may compensate for the effects of disturbance at the nest.

Predictive model of the risk of formation of mental deadaptation in chemical production workers

IntroductionAccording to WHO, 30-50% of workers experience psychological stress, which contributes to the development of mental and psychosomatic disorders. It’s important to develop the problem of prenosological diagnosis and determination of criteria for the formation of mental maladaptation as predictors of mental disorders in relation to occupational risk factors. Mental disorders in workers in a dangerous environment are of the nature of prenosological, not clearly delineated by a circle of diagnostic symptoms.Objectives1st chemical factor in combination with noise and emotional stress, 2d chemical factor in combination with a threat to life (explosion and fire hazard), 3d working in conditions of noise and emotional stressMethodsThe influence of working environment conditions and non-production factors on the formationResultsPredicting the development of mental mailadaptive state model was developedConclusionsVegetative disorders are most likely to manifest in group 1, comorbid of which with obsessive-phobic disorders and depressive spectrum disorders. The group 2 is characterized by astheno-vegetative symptoms in correlation with the conversion type of response. In the third professional group, the nature of predictors is characterized by a pronounced isolation of groups of symptoms, the leading of which is the vegetative pattern.Vegetative syndroms are most likely to manifest in group 1, comorbid of which is obsessive-phobic disorders and depressive spectrum disorders. The group 2 is characterized by astheno-vegetative symptoms in correlation with the conversion type of response. In the third professional group, the nature of predictors is characterized by a pronounced isolation of groups of symptoms, the leading of which is the vegetative pattern.DisclosureNo significant relationships.

Using Music to Reduce Noise Stress for Patients in the Emergency Department: A Pilot Study

High noise levels in the emergency department (ED) affect patient care and cause noise annoyance (stress) to patients. This pilot project aimed to reduce noise stress by offering patients in the ED a coping strategy: headphones and music. In this randomized controlled study, 30 patients meeting study criteria were recruited, with half undergoing the music intervention. This involved listening to music via headphones and an MP3 player from preloaded playlists in four relevant genres. All participants completed a pre- and post-self-report stress tool, a self-report noise disturbance scale, and visual analogue scales related to stress and music. Results showed a trend toward decreased negative affect scores in the intervention group. Positive affect scores remained constant or increased. Individual comments suggested participants’ enjoyment, distraction, and ‘‘escape’’ from the environment. Results suggested that music may be a beneficial intervention to reduce ED noise stress; however, further exploration is needed.

Dual phase dependent RLS filtering approach for baseline wander removal in ECG signal acquisition

Electrocardiogram (ECG) signals often get contaminated during physical activity, due to baseline disturbances. Removal of baseline interference also leads to variation in the timing of ECG waves. This paper proposes a dual phase dependent-recursive least square (DPD-RLS) adaptive filter that removes the baseline interference during ECG signal acquisition. This approach initially detects the upper envelope followed by the subtraction of the upper envelope with the original signal. The lower envelope is then detected from the resultant signal. Two phases are extracted from the upper envelope signal and the lower envelope signal that compensates for the phase change effects during the baseline wander removal process. A DPD-RLS adaptive filter structure is proposed that compensates for the phase changes near the P, Q, and T onset of the ECG signal. The evaluation was done using the clean ECG signals from the MIT-BIH arrhythmia dataset and baseline wander signals from MIT-BIH noise stress dataset signals using the metrics such as output signal to noise ratio (SNRo), correlation coefficient (γ), and percent root mean square difference (PRD) for the different input signal to noise ratios (SNRi). The proposed scheme provides an average output SNR, the correlation coefficient of 14.07dB and 0.980 respectively at SNRi=5dB when evaluated on different ECG records. Experimental results reveal that the proposed baseline wander removal scheme outperforms the traditional schemes.

The noise pollution and heat stress in different parts of Rabak Cement Factory, White Nile State, Sudan

Cement industry caused environmental impacts at all stages of the process in the area; include emissions of airborne pollution in the form of dust, gases, noise and vibration. This study is conducted to evaluate the noise pollution and heat stress in different parts of Rabak Cement Factory. The study involved the exposed and unexposed groups. The noise levels were measured by the aid of an occupational health specialist who was familiar with the measuring device instructions and the study protocol. On the other hand, structured questionnaires were used to assess the workers' response to noise pollution in all sections of the factory. Environmental temperature was measured as close as feasible to the work area where the workers are exposed. The measurements were taken from two locations in the factory; the chemical laboratory and kiln in order to determine the heat stress. Some instruments were used to calculating heat stress parameters. Highest noise level was found in compressors 105.33 dB, conveyor belts 101.66 dB, raw materials mills 98.33dB and workshops 97.00 dB. The levels exceeded the maximum permitted noise level described by WHO. There is high temperature in work environment over standard level which may lead to heat stress. For these findings, the company should create a formal noise and heat stress management program.

Relationship between noise perception, vocal fatigue, and work-related stress among health workers in a hospital in Bogotá, Colombia

To characterize the relationship between noise perception, vocal fatigue, and work-related stress among health workers. Cross sectional with the participation of 79 participants. Data regarding noise levels, voice functioning, and stress were collected through validated questionaries. Generalized Linear Models (GLMs) were used to evaluate the associations between the study variables. Our results show that more than 60% of health workers reported that noise conditions were high (47% considered that it did not affect their job performance, and 22% reported that it did). Concerning vocal fatigue, on average, health workers scored 8.30 for factor 1, 2.52 for factor 2, and 5.09 for factor 3, which suggests that participants were not feeling their voices very tired (factor 1), but they have physical discomfort associated with voicing (factor 2) and experienced improvement of symptoms after recovery (factor 3). Regarding stress levels, around 80% of participating health workers reported very high or high stress levels (61% for very high and 18% for high). Health workers are exposed to noise levels that affect their communication and mental health. Health care facilities should strive to keep noise conditions at its lowest levels to keep healthy conditions for communication and mental health.

HUBUNGAN KEBISINGAN DAN TEKANAN PANAS DENGAN STRES KERJA PADA PEKERJA MEBEL BAGIAN MILLING DI PT ALIS JAYA CIPTATAMA KLATEN

Heat stress and noise are two common causes of work accidents that can have psychological effects, one of which is work stress. Based on preliminary studies, the milling section exceeds NAB with noise exceeding 85 dB and heat pressure exceeding 28 ºC. From the results of the questionnaire analysis, 8 out of 10 workers experienced moderate work stress due to noise, and 7 out of 10 workers were experiencing moderate work stress due to heat stress. This study aimed to find out the relationship between noise exposure and heat stress to work stress on furniture workers at the milling work station at PT Alis Jaya Ciptatama, Klaten. This research is an observational analytic study with a cross-sectional approach. Research respondents numbered 50 people taken with total sampling techniques. Data collection techniques use noise and heat stress measurements and questionnaires. Data analysis uses the Chi-Square statistical test. The result of this study, namely variables related to work stress, is heat stress (p-value 0.001) and unrelated noise (p-value 0.470). It can be concluded that there is no relationship between noise and work stress at PT Alis Jaya Ciptatama milling section workers with a p-value of 0.470 and there is a relationship between heat stress and work stress at PT Alis Jaya Ciptatama milling section workers with a p-value of 0.001. The suggestions can be done by administrative control with worker rotation, adding ventilator turbines, providing training to workers in overcoming heat stress stressors.

Embedded QRS complex detection based on ECG signal strength and trend

Cardiovascular diseases (CVD) are among the most fatal diseases and its mitigation is a huge challenge in healthcare. Electrocardiography (ECG) remains the most commonly used method and device for the visualization and analysis cardiac rhythm. QRS complex detection has been extensively used for this purpose. Recently, several PC based QRS detection algorithms were proposed wherein the QRS complex is detected from previously stored ECG signals. However, with the expansion of personalized medicine backed by advances in the field of wearable medical devices, it is imperative to have an algorithm that is robust, accurate, real-time, and computationally efficient for low resource microcontroller units (MCU). In this paper, a novel embedded QRS complex detection algorithm based on the ECG signal strength and its trend is presented. The algorithm is based on a simulated capacitor threshold that captures the signal strength two other thresholds based on the signal trend to find the position of the R-peak. Subsequently, the location of the end of the R-peak and the tangent to the ECG curve are used to find the onset of the QRS complex. The algorithm obtained average F1 scores of 99.75%, 99.84%, 97.39%, and 86.63% on the MIT-BIH Arrhythmia, MIT-BIH Normal Sinus, the MIT-BIH Noise Stress Test, and the 2014 PhysioNet/CinC Challenge databases respectively. Average run-times for the processing of a single data point were 3.38μs, and 383μs when the algorithm was running respectively on an ESP32-WROOM-32 MCU @240MHz and an Arduino Nano MCU @16MHz. This algorithm has a great potential in the field of wearable medical devices and remote monitoring systems.

Study of the effect of simultaneous exposure to noise and heat stress on the activity level of biceps and flexor muscles

Study of the effect of simultaneous exposure to noise and heat stress on the activity level of biceps and flexor muscles

Towards a software architecture to manage occupational safety at grain handling and storage facilities

The study had as objective to evaluate occupational hazards on grain storage unit to define a conceptual model, implemented in an algorithm to manage the grains storage facilities safety standards compliance. Sampling points location were defined for static quantification of noise, dust and heat stress hazards in grains pre-processing operations to indicate the effectiveness of the control measures implemented. Safety standards applied to grain handling and storage facilities were identified and selected. Chart flows were elaborated to the algorithm logics and conceptual modeling. The highest level of noise was present in the grain cleaning operation (99.1 dB), while the expedition operation has the highest level of dust (20.27%). The heat stress was present in the grain drying operation (43.64 WBGT). Noise analysis did not show a difference between grains, only between operations. The flow of corn grain mass caused higher dust concentrations in the expedition operation. The method applied to characterize and quantify the hazards in grain storage units was satisfactory, and it is recommended as standard, for use in corn and soybean grains handling and storage units. The algorithm to manage occupational safety at storage facilities collaborates to monitor the safety compliance on postharvest operations.

Long-Term Effects of Aircraft Noise Exposure on Vascular Oxidative Stress, Endothelial Function and Blood Pressure: No Evidence for Adaptation or Tolerance Development.

Transportation noise is recognized as an important cardiovascular risk factor. Key mechanisms are noise-triggered vascular inflammation and oxidative stress with subsequent endothelial dysfunction. Here, we test for adaptation or tolerance mechanisms in mice in response to chronic noise exposure. C57BL/6J mice were exposed to aircraft noise for 0, 4, 7, 14 and 28d at a mean sound pressure level of 72 dB(A) and peak levels of 85 dB(A). Chronic aircraft noise exposure up to 28d caused persistent endothelial dysfunction and elevation of blood pressure. Likewise, reactive oxygen species (ROS) formation as determined by dihydroethidium (DHE) staining and HPLC-based measurement of superoxide formation in the aorta/heart/brain was time-dependently increased by noise. Oxidative burst in the whole blood showed a maximum at 4d or 7d of noise exposure. Increased superoxide formation in the brain was mirrored by a downregulation of neuronal nitric oxide synthase (Nos3) and transcription factor Foxo3 genes, whereas Vcam1 mRNA, a marker for inflammation was upregulated in all noise exposure groups. Induction of a pronounced hearing loss in the mice was excluded by auditory brainstem response audiometry. Endothelial dysfunction and inflammation were present during the entire 28d of aircraft noise exposure. ROS formation gradually increases with ongoing exposure without significant adaptation or tolerance in mice in response to chronic noise stress at moderate levels. These data further illustrate health side effects of long-term noise exposure and further strengthen a consequent implementation of the WHO noise guidelines in order to prevent the development of noise-related future cardiovascular disease.

Relating teachers’ coping styles to student noise and perceived stress

School noise is a serious, inevitable problem that teachers experience as stress or strain. Coping styles have a huge impact on teachers’ mental health and therefore might influence this daily stress experience. Based on the stress-strain model and the transactional stress model, we examined in an online study how 99 teachers with different coping styles reacted to school noise. Four professional coping styles were derived from the overarching dimensions of professional commitment and experience resilience. The healthy type, the unambitious type, type A, and type burnout differed in terms of threat appraisal, noise stress, voice and hearing problems as well as noise-related burnout. Compared to the healthy type, types A and burnout showed higher levels of stress. Teachers of the risk types turned out to be more vulnerable to school noise than teachers of the healthy type. Specific prevention programs may help to improve teacher resilience.