Optimal filters for ERP research II: Recommended settings for seven common ERP components

In research with event-related potentials (ERPs), aggressive filters can substantially improve the signal-to-noise ratio and maximize statistical power, but they can also produce significant waveform distortion. Although this tradeoff has been well documented, the field lacks recommendations for filter cutoffs that quantitatively address both of these competing considerations. To fill this gap, we quantified the effects of a broad range of low-pass filter and high-pass filter cutoffs for seven common ERP components (P3b, N400, N170, N2pc, mismatch negativity, error-related negativity, and lateralized readiness potential) recorded from a set of neurotypical young adults. We also examined four common scoring methods (mean amplitude, peak amplitude, peak latency, and 50% area latency). For each combination of component and scoring methods, we quantified the effects of filtering on data quality (noise level and signal-to-noise ratio) and waveform distortion. This led to recommendations for optimal low-pass and high-pass filter cutoffs. We repeated the analyses after adding artificial noise to provide recommendations for data sets with moderately greater noise levels. For researchers who are analyzing data with similar ERP components, noise levels, and participant populations, using the recommended filter settings should lead to improved data quality and statistical power without creating problematic waveform distortion.

Noise exposure assessment of workers inspecting construction machinery vehicles in the Republic of Korea

Previous studies have investigated the health hazards caused by exposure to the noise of heavy equipment used at construction sites. Korea's Ministry of Land, Infrastructure, and Transport operates a registration system for construction machinery, and regular safety inspections are mandatory. Although workers inspecting construction machinery vehicles are exposed to unwanted noise, no noise exposure assessment has been made regarding these workers in Korea. The time-weighted average (TWA) daily average noise exposure level among construction machinery inspectors at 18 inspection centers was 75.3 dB(A). Among the inspection steps, the exhaust gas inspection step was found to exhibit the highest noise exposure level, up to 100 dB(A). In Korea, if the noise level of a workplace exceeds 85 dB(A) as a TWA, workers are required to undergo special medical examinations. This study found that special medical examinations were required for two of the 18 target inspection centers (approximately 115 workers) as the 8-hour TWA noise level exceeded 85 dB(A). Therefore, regular noise exposure assessment and special medical examinations for noise are required to prevent inspectors from developing hearing disorders due to noise exposure.

Cross noise level PET denoising with continuous adversarial domain generalization

Objective.Performing positron emission tomography (PET) denoising within the image space proves effective in reducing the variance in PET images. In recent years, deep learning has demonstrated superior denoising performance, but models trained on a specific noise level typically fail to generalize well on different noise levels, due to inherent distribution shifts between inputs. The distribution shift usually results in bias in the denoised images. Our goal is to tackle such a problem using a domain generalization technique.Approach.We propose to utilize the domain generalization technique with a novel feature space continuous discriminator (CD) for adversarial training, using the fraction of events as a continuous domain label. The core idea is to enforce the extraction of noise-level invariant features. Thus minimizing the distribution divergence of latent feature representation for different continuous noise levels, and making the model general for arbitrary noise levels. We created three sets of 10%, 13%-22% (uniformly randomly selected), or 25% fractions of events from 9718F-MK6240 tau PET studies of 60 subjects. For each set, we generated 20 noise realizations. Training, validation, and testing were implemented using 1400, 120, and 420 pairs of 3D image volumes from the same or different sets. We used 3D UNet as the baseline and implemented CD to the continuous noise level training data of 13%-22% set.Main results.The proposed CD improves the denoising performance of our model trained in a 13%-22% fraction set for testing in both 10% and 25% fraction sets, measured by bias and standard deviation using full-count images as references. In addition, our CD method can improve the SSIM and PSNR consistently for Alzheimer-related regions and the whole brain.Significance.To our knowledge, this is the first attempt to alleviate the performance degradation in cross-noise level denoising from the perspective of domain generalization. Our study is also a pioneer work of continuous domain generalization to utilize continuously changing source domains.

A Cloud Detection Method for Vertically Pointing Millimeter-Wavelength Cloud Radar

A new method using three dimensions of cloud continuity, including range dimension, Doppler dimension, and time dimension, is proposed to discriminate cloud from noise and detect more weak cloud signals in vertically pointing millimeter-wave cloud radar observations by fully utilizing the spatiotemporal continuum of clouds. A modified noise level estimation method based on the Hildebrand and Sekhon algorithm is used for more accurate noise level estimation, which is critical for weak signals. The detection method consists of three steps. The first two steps are performed at the Doppler power spectrum stage, while the third step is performed at the base data stage. In the first step, a new adaptive spatial filter combined with the Kuwaraha filter and the Gaussian filter, using the ratio of mean to standard deviation as the adaptive parameter, is applied to initially mask the potential cloud signals to improve the detection performance at the boundary of cloud and noise. Simulations of boundary cases were performed to compare our adaptive filter and normal Gaussian filters. Box filters are used in steps two and three to remove the remaining noise. We applied our method to cloud radar observations with TJ-II cloud radar at the Nanjing University of Information Science & Technology. The results showed that our method can detect more weak cloud signals than the usual methods, which are performed only at the Doppler power spectrum stage or the base data stage.

Modelling of Animal Activity, Illuminance, and Noise on a Weaned Piglet Farm

Measuring animal activity and its evolution in real time is useful for animal welfare assessment. In addition, illuminance and noise level are two factors that can improve our understanding of animal activity. This study aims to establish relationships between animal activity as measured by passive infrared sensors, and both illuminance and noise level on a conventional weaned piglet farm. First, regression models were applied, and then cosine models with three harmonics were developed using least squares with a Generalized Reduced Gradient Nonlinear method. Finally, all the models were validated. Linear models showed positive correlations, with values between 0.40 and 0.56. Cosine models drew clear patterns of daily animal activity, illuminance and noise level with two peaks, one in the morning and one in the afternoon, coinciding with human activity inside the building, with a preference for inactivity at night-time and around midday. Cosine model fitting revealed strong correlations, both in the measurement and validation periods, for animal activity (R = 0.97 and 0.92), illuminance (R = 0.95 and 0.91) and noise level (R = 0.99 and 0.92). The developed models could be easily implemented in animal welfare monitoring systems and could provide useful information about animal activity through continuous monitoring of illuminance or noise levels.

Optimal Filters for ERP Research II: Recommended Settings for Seven Common ERP Components

In research with event-related potentials (ERPs), aggressive filters can substantially improve the signal-to-noise ratio and maximize statistical power, but they can also produce significant waveform distortion. Although this tradeoff has been well documented, the field lacks recommendations for filter cutoffs that quantitatively address both of these competing considerations. To fill this gap, we quantified the effects of a broad range of low-pass filter and high-pass filter cutoffs for seven common ERP components (P3b, N400, N170, N2pc, mismatch negativity, error-related negativity, and lateralized readiness potential) recorded from a set of neurotypical young adults. We also examined four common scoring methods (mean amplitude, peak amplitude, peak latency, and 50% area latency). For each combination of component and scoring method, we quantified the effects of filtering on data quality (noise level and signal-to-noise ratio) and waveform distortion. This led to recommendations for optimal low-pass and high-pass filter cutoffs. We repeated the analyses after adding artificial noise to provide recommendations for datasets with moderately greater noise levels. For researchers who are analyzing data with similar ERP components, noise levels, and participant populations, using the recommended filter settings should lead to improved data quality and statistical power without creating problematic waveform distortion.

A Single-Image Noise Estimation Algorithm Based on Pixel-Level Low-Rank Low-Texture Patch and Principal Component Analysis

Noise level is an important parameter for image denoising in many image-processing applications. We propose a noise estimation algorithm based on pixel-level low-rank, low-texture subblocks and principal component analysis for white Gaussian noise. First, an adaptive clustering algorithm, based on a dichotomy merge, adaptive pixel-level low-rank matrix construction method and a gradient covariance low-texture subblock selection method, is proposed to construct a pixel-level low-rank, low-texture subblock matrix. The adaptive clustering algorithm can improve the low-rank property of the constructed matrix and reduce the content of the image information in the eigenvalues of the matrix. Then, an eigenvalue selection method is proposed to eliminate matrix eigenvalues representing the image to avoid an inaccurate estimation of the noise level caused by using the minimum eigenvalue. The experimental results show that, compared with existing state-of-the-art methods, our proposed algorithm has, in most cases, the highest accuracy and robustness of noise level estimation for various scenarios with different noise levels, especially when the noise is high.

Association of indoor noise level with depression in hotel workers: A multicenter study from 111 China's cities

Several studies have elucidated the link between outdoor noise and depression, but the relationship between indoor noise levels and depression symptoms in residential and public places remains unclear. This study was a multicenter observational study with a cross-sectional design. In 2019, a total of 10 545 indoor noise levels on-site and 26 018 health data from practitioners were collected from 2402 hotels in 111 cities. Indoor daily noise data levels were detected, and PHQ-9 questionnaires were used to collect health data. Logistic analysis was used to determine the association between depression score and noise level, negative binomial regression was used to determine potential risks. The geometric mean indoor noise level was 38.9 dB (A), with approximately 40.9% of hotels exceeding the 45 dB value (A). Approximately 19.1% of hotel workers exhibited mild and above depressive symptoms. In addition to functional zoning, geographic location, central air conditioner, decoration status, and other factors had an impact on noise levels (p < 0.05). Results of logistic and negative binomial regression showed the following: (1) there was significantly positive association between indoor noise and high depression scores above 2 (OR = 1.007, 95% CI: 1.002, 1.012) and (2) some sub-groups were more susceptible to this effect, especially for the younger female workers working in the first-tier cities, having higher education level, lower level of income, smoking, and longer working hours. This study confirms an early potential effect of indoor noise on depression. It is recommended to implement evidence-based measures to control noise sources in hotels.

Association Between Operating Room Noise and Team Cognitive Workload in Cardiac Surgery

Excessive intra-operative noise in cardiac surgery has the potential to serve as source of distraction and additional cognitive workload for the surgical team, and may interfere with optimal performance. The separation from bypass phase is a technically complex phase of surgery, making it highly susceptible to communication breakdowns due to high cognitive demands and requiring tightly coupled team coordination. The objective of this study was to investigate team cognitive workload levels and communication in relation to intra-operative time periods representative of infrequent vs. frequent peaks in ambient noise. Compared to 5-minute segments with no peaks in noise at all, segments with the highest percentage of noise peaks (≥10%) were significantly associated with higher team members' heart rate before, during, and after noise segments analyzed. These noisier segments were also associated with a significantly higher level of case-irrelevant communication events. These data suggest that case-irrelevant conversations associated with a greater degree of excessive peaks in noise may be associated with team workload levels, warranting further investigation into efforts to standardize communication during critical surgical phases.

The impact of operating room noise levels on stress and work efficiency of the operating room team: A protocol for systematic review and meta-analysis

BACKGROUND

There is no high-quality meta-analysis in the literature to determine the noise level in the operating room. Therefore, the aim of this study is to systematically review the available evidence in the literature to elucidate the impact of operating room noise levels on stress and work efficiency of the operating room team.

METHODS

Two individual researchers will conduct the platform searches on the PubMed, Cochrane Library, and Embase databases from inception to June 1, 2022. The cohort studies assessing the impact of operating room noise levels on stress and work efficiency of the operating room team will be included. The outcomes include total workload level, stress scores, anxiety scores, operation time. We will collect data according to the guidelines in the Cochrane Handbook for Systematic Reviews of Interventions. The Meta analysis will be performed using Review Manager version 5.3 provided by the Cochrane Collaboration. Risk bias analysis of the studies will be performed independently by two reviewers using the Cochrane Risk of Bias Assessment Tool.

RESULTS

The review will add to the existing literature by showing compelling evidence and improved guidance in clinic settings.

REGISTRATION NUMBER

10.17605/OSF.IO/7N8RY.

Noise Exposure Assessment in Construction Equipment Operators in Tehran, Iran

Occupational hearing loss is a common complication among construction workers, especially those working with heavy machinery and construction equipment. This research measured the noise that construction operators are exposed to, and proves that most of the construction equipment operators that we studied have a potential risk of hearing impairment. We examined 22 types of construction machinery that are commonly used in various stages of construction projects in Tehran (demolition, excavation, and execution). The noise that construction operators were exposed to was measured with a dosimeter during 8 working hours, and the Time-Weighted Average (TWA) was calculated for each operator according to OSHA standards. Finally, a suitable hearing protection device (HPD) was suggested. The results indicated that the operators of D8N (opened-cab) and CAT D8L SA (closed-cab) bulldozers were exposed to more noise than other operators in this study. Hand-saw, Caterpillar 943, and Komatsu 470 loader operators were also exposed to significant noise levels. Other operators, such as drivers of older Benz and Volvo trucks, the Backhoe HLB95, the Soosan mobile crane, and the Bobcat were also exposed to heavy noise that put them at risk of occupational hearing loss.

The comfort assessment in healthy adults during constant-flow mode in noninvasive ventilator

Background

From the point of view of machine construction and hydrodynamics, this paper innovatively proposes that the essence of high‐flow nasal cannula (HFNC) is a constant‐flow mode in noninvasive ventilator (NIVCFM). This study enrolled healthy adults as study subjects to assess the subjective comfort assessed by visual analog scoring scale of NIVCFM/HFNC and objective comfort measured by the noise level generated by NIVCFM/HFNC, aiming to provide a scientific basis for the rational clinical application of NIVCFM/HFNC.

Methods

Forty‐four healthy adults participated in this study. The noise generated by NIVCFM/HFNC is measured, and the comfort is evaluated during NIVCFM delivery at flow rates of 0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, and 60 L/min.

Results

When the ventilator flow rate is 60 L/min, the maximum noise is 65.9 dB, increasing noise by 23.7 dB from a baseline of 42.2 dB at the flow rate of 0 L/min. There was a strong nonlinear positive correlation between the noise level and the flow rates. The median score for dry mouth, nose or throat, dysphagia, sore throat, and other discomfort was 0. The median score for dyspnea was 0 at 0–30 L/min, 1 at 35–55 L/min, and 2 at 60 L/min.

Conclusions

The grater the flow rate, the greater the noise generated by NIVCFM/HFNC (<65.9 dB). The maximum flow rate that most healthy adults can able to tolerate is 30 L/min, and the main discomfort is dyspnea.

Magnetoelectric Magnetic Field Sensors: A Review

One of the new materials that have recently attracted wide attention of researchers are magnetoelectric (ME) composites. Great interest in these materials is due to their properties associated with the transformation of electric polarization/magnetization under the influence of external magnetic/electric fields and the possibility of their use to create new devices. In the proposed review, ME magnetic field sensors based on the widely used structures Terfenol—PZT/PMN-PT, Metglas—PZT/PMN-PT, and Metglas—Lithium niobate, among others, are considered as the first applications of the ME effect in technology. Estimates of the parameters of ME sensors are given, and comparative characteristics of magnetic field sensors are presented. Taking into account the high sensitivity of ME magnetic field sensors, comparable to superconducting quantum interference devices (SQUIDs), we discuss the areas of their application.

Physical and Psychoacoustic Characteristics of Typical Noise on Construction Site: "How Does Noise Impact Construction Workers' Experience?"

Construction noise is an integral part of urban social noise. Construction workers are more directly and significantly affected by construction noise. Therefore, the construction noise situation within construction sites, the acoustic environment experience of construction workers, and the impact of noise on them are highly worthy of attention. This research conducted a 7-month noise level (L_Aeq) measurement on a construction site of a reinforced concrete structure high-rise residential building in northern China. The noise conditions within the site in different spatial areas and temporal stages was analyzed. Binaural recording of 10 typical construction noises, including earthwork machinery, concrete machinery, and hand-held machinery, were performed. The physical acoustics and psychoacoustic characteristics were analyzed with the aid of a sound quality analysis software. A total of 133 construction workers performing 12 types of tasks were asked about their subjective evaluation of the typical noises and given a survey on their noise experience on the construction site. This was done to explore the acoustic environment on the construction site, the environmental experience of construction workers, the impact of noise on hearing and on-site communications, and the corresponding influencing factors. This research showed that the noise situation on construction sites is not optimistic, and the construction workers have been affected to varying degrees in terms of psychological experience, hearing ability, and on-site communications. Partial correlation analysis showed that the construction workers’ perception of noise, their hearing, and their on-site communications were affected by the noise environment, which were correlated to varying degrees with the individual’s post-specific noise, demand for on-site communications, and age, respectively. Correlation analysis and cluster analysis both showed that the annoyance caused by typical construction noise was correlated to its physical and psychoacoustic characteristics. To maintain the physical and mental health of construction workers, there is a need to improve on the fronts of site management, noise reduction, equipment and facility optimization, and occupational protection.

Noise Pollution and Its Correlations with Occupational Noise-Induced Hearing Loss in Cement Plants in Vietnam

Noise-Induced Hearing Loss (NIHL) is a global issue that is caused by many factors. The purpose of this study was to survey noise level to identify NIHL and its relationship with other factors in cement plants in Vietnam. Noise level was measured at one cement plant and three cement grinding stations located in the South of Vietnam. The audiometric data of exposed workers were surveyed to determine NIHL. Finally, the relationship between NIHL and noise level in cement plants was determined. The results show that noise level in almost all processes exceeded the permissible exposure limit (PEL). In this study, 42 cases (10% of exposed workers) with occupational NIHL were found with mean age (SD) of 49 (9.0) years. All NIHL cases were found in the departments in which the noise level exceeded the PEL, which included quarry (n = 16), maintenance (n = 12), production (n = 10), co-waste processing (n = 3) and quality assurance (n = 1). There was a positive and significant correlation between the NIHL and the excessive noise exposure in the cement plants (r = 0.89, p = 0.04).

MEMS-Based Electrochemical Seismometer Relying on a CAC Integrated Three-Electrode Structure

This study developed a MEMS-based electrochemical seismometer relying on a cathode–anode–cathode (CAC) integrated three-electrode structure where two cathodes were positioned on two surfaces of a silicon wafer, while one anode was positioned on the sidewalls of the through holes of the silicon wafer. Device design and numerical simulations were conducted to model the functionality of the three-electrode structure in detecting vibration signals with the key geometrical parameters optimized. The CAC integrated three-electrode structure was then manufactured by microfabrication, which demonstrated a simplified fabrication process in comparison with conventional four-electrode structures. Device characterization shows that the sensitivity of the CAC microseismometer was an order of magnitude higher than that of the CME6011 (a commercially available four-electrode electrochemical seismometer), while the noise level was comparable. Furthermore, in response to random vibrations, a high correlation coefficient between the CAC and the CME6011 (0.985) was located, validating the performance of the developed seismometer. Thus, the developed electrochemical microseismometer based on an integrated three-electrode structure may provide a new perspective in seismic observations and resource explorations.

The Effect of Noise Levels in the Operating Room on the Stress Levels and Workload of the Operating Room Team

PURPOSE

The research was conducted to evaluate the noise levels and the effect of noise on the workload and stress levels of the operating room (OR) staff of a public hospital.

DESIGN

Descriptive and cross-sectional study.

METHODS

The data were obtained by measuring ambient noise during 403 orthopaedic, urological, and general surgeries on weekdays between July and October 2019. We measured the noise by dividing the surgery into three phases. These phases are as follows: from the entry of the patient, induction of anesthesia, and preparation of the surgical area until the start of the procedure (Phase I), from the incision until the completion of closure and dressing application (Phase II), from the completion of closure and dressing application until the exit of the patient (Phase III). Furthermore, the workload and stress levels of 45 OR staff who work in the general surgery, orthopaedics, and urology ORs were measured. Data were collected using a CA 834 noise measurement device, State-Trait Anxiety Inventory (STAI Form TX-I), the National Aeronautics and Space Administration (NASA) Task Load Index Workload Scale, and Information form related to surgery and ORs.

FINDINGS

The noise in the OR was higher than 35 dB, A-weighted [dB(A)], the limit proposed by the World Health Organization for hospitals. Phase I average noise level was 63.00 ± 3.50, Phase II average noise level was 62.94 ± 3.75, and Phase III average noise level was 63.67 ± 2.81. The mean anxiety score was 34.50 ± 6.09. The total workload level was found to be 56.91 ± 15.67. Anxiety scores and workload scores had positive weak and moderate correlations with noise levels (P < .01).

CONCLUSIONS

The noise in the OR was high, and anxiety scores and workload scores correlated positively with noise levels.

How did the 'state of emergency' declaration in Japan due to the COVID-19 pandemic affect the acoustic environment in a rather quiet residential area?

The COVID-19 pandemic caused lockdowns in many countries worldwide. Acousticians have made surveys to monitor how cities became quieter under the lockdown, mainly in central areas in cities. However, there have been few studies on the changes in the acoustic environment due to the pandemic in the usually quieter residential areas. It may be expected to be different from the effect in 'originally noisy' areas. Also, the effect could be different in Japan, because the 'state of emergency' declaration there was different to lockdowns elsewhere. Considering these circumstances, this article reports the results of noise monitoring and makes some observations on the acoustic environment in residential areas far from city centres, to provide an example of how the acoustic environment was affected by the state of emergency declaration due to the COVID-19 pandemic in Japan. The results showed that the reduction of noise levels was somewhat less than that reported in large cities. Also, comparing the results after the cancellation of the state of emergency, the noise level increased again. However, observations of noise sources imply that a possible change in human behaviour may have also affected the acoustic environment.

Sound levels with aural suctioning: Effects of suction size, canal moisture, and distance from the eardrum

OBJECTIVE

To determine sound levels resulting from aural suctioning of the external auditory canal.

METHODS

Unweighted decibels (dB) and A-weighted decibels (dBA) sound pressure level measurements were recorded using a retrotympanic microphone in cadaveric human temporal bones. Sound measurements were made with common otologic suctions, size 3, 5, and 7 French, within the external ear canal at the tympanic membrane, 5, and 10 mm from the tympanic membrane in the dry condition. In the wet condition, the ear canal was filled with fluid and completely suctioned clear to determine sound effects of suctioning liquid from the ear canal.

RESULTS

Sound levels generated from ear canal suctioning ranged from 68.3 to 97 dB and 62.6 to 95.1 dBA. Otologic suctions positioned closer to the tympanic membrane resulted in louder sound levels, but was not statistically significant (P > .05). Using larger diameter suctions generated louder dB and dBA sound levels (P < .001) and the addition of liquid in the ear canal during the suction process generated louder dB and dBA sound levels (P < .001).

CONCLUSIONS

Smaller caliber suction sizes and nonsuctioning techniques should be utilized for in-office aural toilet to reduce noise trauma and patient discomfort.

LEVEL OF EVIDENCE

5.

Assessment of occupational noise-related hearing impairment among dental health personnel

Objectives

The purpose of the study was to examine hearing thresholds among dental personnel. The secondary aim was to evaluate sound levels among dental equipment that dental personnel are exposed to.

Methods

Two hundred forty‐four dentists, dental technicians, dental assistants, and dental students participated. Sixty‐two participated as a control group. Audiological thresholds for the test groups were compared to the control group. All participants were from Jordan University Hospital. Participants completed a questionnaire in addition to their audiometric testing. Otoscopy, tympanometry, and pure tone audiometry were included in their assessment. Three‐factor ANOVA and t tests were utilized to assess the statistical differences of hearing thresholds among the groups and between the two ears. Pearson correlation test was used to assess the effect of age, experience, and duration of exposure on the degree of hearing loss in the test groups for both ears.

Results

The authors reported statistically significant differences among hearing thresholds between the control group and others. Left hearing thresholds were noted to be significantly poorer in the left versus right ear at 1000, 2000, 4000, and 8000 Hz in dental assistants. The authors also reported a significant relationship between the degree of hearing impairment among dental assistants and the daily duration of exposure to dental occupational noise, followed by age.

Conclusion

Hearing impairment was higher among dental professionals than the control group and especially among dental assistants and technicians. The authors recommended screening guidelines and adapting hearing protection methods for dental professionals and particularly for dental assistants and technicians.

Exploring on the Sensitivity Changes of the LC Resonance Magnetic Sensors Affected by Superposed Ringing Signals

LC resonance magnetic sensors are widely used in low-field nuclear magnetic resonance (LF-NMR) and surface nuclear magnetic resonance (SNMR) due to their high sensitivity, low cost and simple design. In magnetically shielded rooms, LC resonance magnetic sensors can exhibit sensitivities at the fT/√Hz level in the kHz range. However, since the equivalent magnetic field noise of this type of sensor is greatly affected by the environment, weak signals are often submerged in practical applications, resulting in relatively low signal-to-noise ratios (SNRs). To determine why noise increases in unshielded environments, we analysed the noise levels of an LC resonance magnetic sensor (L ≠ 0) and a Hall sensor (L ≈ 0) in different environments. The experiments and simulations indicated that the superposed ringing of the LC resonance magnetic sensors led to the observed increase in white noise level caused by environmental interference. Nevertheless, ringing is an inherent characteristic of LC resonance magnetic sensors. It cannot be eliminated when environmental interference exists. In response to this problem, we proposed a method that uses matching resistors with various values to adjust the quality factor Q of the LC resonance magnetic sensor in different measurement environments to obtain the best sensitivity. The LF-NMR experiment in the laboratory showed that the SNR is improved significantly when the LC resonance magnetic sensor with the best sensitivity is selected for signal acquisition in the light of the test environment. (When the matching resistance is 10 kΩ, the SNR is 3.46 times that of 510 Ω). This study improves LC resonance magnetic sensors for nuclear magnetic resonance (NMR) detection in a variety of environments.

A Flexible Sensing Unit Manufacturing Method of Electrochemical Seismic Sensor

This paper presents an electrochemical seismic sensor in which paraylene was used as a substrate and insulating layer of micro-fabricated electrodes, enabling the detection of seismic signals with enhanced sensitivities in comparison to silicon-based counterparts. Based on microfabrication, paralene-based electrochemical seismic sensors were fabricated in which the thickness of the insulating spacer was 6.7 μm. Compared to silicon-based counterparts with ~100 μm insulating layers, the parylene-based devices produced higher sensitivities of 490.3 ± 6.1 V/(m/s) vs. 192.2 ± 1.9 V/(m/s) at 0.1 Hz, 4764.4 ± 18 V/(m/s) vs. 318.9 ± 6.5 V/(m/s) at 1 Hz, and 4128.1 ± 38.3 V/(m/s) vs. 254.5 ± 4.2 V/(m/s) at 10 Hz. In addition, the outputs of the parylene vs. silicon devices in response to two transit inputs were compared, producing peak responses of 2.97 V vs. 0.22 V and 2.41 V vs. 0.19 V, respectively. Furthermore, the self-noises of parylene vs. silicon-based devices were compared as follows: -82.3 ± 3.9 dB vs. -90.4 ± 9.4 dB at 0.1 Hz, -75.7 ± 7.3 dB vs. -98.2 ± 9.9 dB at 1 Hz, and -62.4 ± 7.7 dB vs. -91.1 ± 8.1 dB at 10 Hz. The developed parylene-based electrochemical seismic sensors may function as an enabling technique for further detection of seismic motions in various applications.

Noise Exposure From High-Flow Nasal Cannula Oxygen Therapy: A Bench Study on Noise Reduction

BACKGROUND

High-flow nasal cannula (HFNC) oxygen therapy produces noise at a level such that patients often complain. However, the noise level has not been measured digitally.

METHODS

We evaluated 3 types of HFNCs without filters and 2 types with filters attached for noise reduction. Optiflow (with and without a filter), MaxVenturi (with and without a filter) and AIRVO2 (without a filter only) were positioned at the center of a hospital room. We measured the noise levels at the distance of 1 m from the equipment at various total flows (30, 40, 50, 60 L/min) and F_IO2 (0.40, 0.60, and 0.90).

RESULTS

Noise levels were increased with the AIRVO2 and MaxVenturi when total flow and F_IO2 were increased. Noise levels decreased with the MaxVenturi when a filter was used. The noise level did not change with the Optiflow when total flow and F_IO2 were increased. The noise level decreased in the groups with AIRVO2 and Optiflow compared with MaxVenturi without a filter.

CONCLUSIONS

The findings in this study show that the noise level of HFNC/Venturi could be reduced by attaching an intake filter. However, the noise level of HFNC/blender and HFNC/turbine decreased in comparison with HFNC/Venturi without an intake filter.

The Effects of Bit Wear on Respirable Silica Dust, Noise and Productivity: A Hammer Drill Bench Study

Objectives

Hammer drills are used extensively in commercial construction for drilling into concrete for tasks including rebar installation for structural upgrades and anchor bolt installation. This drilling task can expose workers to respirable silica dust and noise. The aim of this pilot study was to evaluate the effects of bit wear on respirable silica dust, noise, and drilling productivity.

Method

Test bits were worn to three states by drilling consecutive holes to different cumulative drilling depths: 0, 780, and 1560 cm. Each state of bit wear was evaluated by three trials (nine trials total). For each trial, an automated laboratory test bench system drilled 41 holes 1.3 cm diameter, and 10 cm deep into concrete block at a rate of one hole per minute using a commercially available hammer drill and masonry bits. During each trial, dust was continuously captured by two respirable and one inhalable sampling trains and noise was sampled with a noise dosimeter. The room was thoroughly cleaned between trials.

Results

When comparing results for the sharp (0 cm) versus dull bit (1560 cm), the mean respirable silica increased from 0.41 to 0.74 mg m-3 in sampler 1 (P = 0.012) and from 0.41 to 0.89 mg m-3 in sampler 2 (P = 0.024); levels above the NIOSH recommended exposure limit of 0.05 mg m-3. Likewise, mean noise levels increased from 112.8 to 114.4 dBA (P < 0.00001). Drilling productivity declined with increasing wear from 10.16 to 7.76 mm s-1 (P < 0.00001).

Discussion

Increasing bit wear was associated with increasing respirable silica dust and noise and reduced drilling productivity. The levels of dust and noise produced by these experimental conditions would require dust capture, hearing protection, and possibly respiratory protection. The findings support the adoption of a bit replacement program by construction contractors.

Noise level measurement, a new method to evaluate effectiveness of sedation in pediatric dentistry

OBJECTIVES

Pediatric dentists perform moderate sedation frequently to facilitate dental treatment in uncooperative children. Assessing the depth and quality of sedation is an important factor in the clinical utilization of moderate sedation. We aimed to determine if the level of noise, created by the children who are undergoing moderate sedation during dental procedures, could be used as a nonsubjective measurement of the depth of sedation and compare it to the Ohio State Behavior Rating Score (OSBRS).

METHODS

Following Institutional Review Board approval and after receiving informed consent, we studied 51 children with a mean age of 4.2 years and average weight of 18.5 kg, who were undergoing restorative or extractive dental procedures, requiring moderate sedation. Sedation efficacy was assessed using OSBRS at several stages of the procedure. The noise level was measured by using a NoisePRO logging device to record the noise level at a rate of every second throughout the procedure.

RESULTS

The depth of sedation assessed by OSBRS during the operative procedure was significantly correlated with noise level. The act of administering the local anesthesia and the operative procedure itself were two phases of the encounter that were significantly associated with higher OSBRS as well as noise levels.

CONCLUSION

Measurement of noise level can be used as an effective guide to quantify the depth of sedation at different stages of the dental procedure. It is a nonsubjective and continuous measurement, which could be useful in clinical practice for the administration of moderate sedation during dental procedures. By using noise level analysis we are able to determine successful, poor, and failed sedation outcome.

Sample entropy reveals high discriminative power between young and elderly adults in short fMRI data sets

Some studies have placed Sample entropy on the same data length constraint of 10^m–20^m (m: pattern length) as approximate entropy, even though Sample entropy is largely independent of data length and displays relative consistency over a broader range of possible parameters (r, tolerance value; m, pattern length; N, data length) under circumstances where approximate entropy does not. This is particularly erroneous for some fMRI experiments where the working data length is less than 100 volumes (when m = 2). We therefore investigated whether Sample entropy is able to effectively discriminate fMRI data with data length, N less than 10^m (where m = 2) and r = 0.30, from a small group of 10 younger and 10 elderly adults, and the whole cohort of 43 younger and 43 elderly adults, that are significantly (p < 0.001) different in age. Ageing has been defined as a loss of entropy; where signal complexity decreases with age. For the small group analysis, the results of the whole brain analyses show that Sample entropy portrayed a good discriminatory ability for data lengths, 85 ≤ N ≤ 128, with an accuracy of 85% at N = 85 and 80% at N = 128, at q < 0.05. The regional analyses show that Sample entropy discriminated more brain regions at N = 128 than N = 85 and some regions common to both data lengths. As data length, N increased from 85 to 128, the noise level decreased. This was reflected in the accuracy of the whole brain analyses and the number of brain regions discriminated in the regional analyses. The whole brain analyses suggest that Sample entropy is relatively independent of data length, while the regional analyses show that fMRI data with length of 85 volumes is consistent with our hypothesis of a loss of entropy with ageing. In the whole cohort analysis, Sample entropy discriminated regionally between the younger and elderly adults only at N = 128. The whole cohort analysis at N = 85 was indicative of the ageing process but this indication was not significant (p > 0.05).

The ultrasound elastography inverse problem and the effective criteria

The elastography (elasticity imaging) is one of the recent state-of-the-art methods for diagnosis of abnormalities in soft tissue. The idea is based on the computation of the tissue elasticity distribution. This leads to the inverse elasticity problem; in that, displacement field and boundary conditions are known, and elasticity distribution of the tissue is aimed for computation. We treat this problem by the Gauss-Newton method. This iterative method results in an ill-posed problem, and therefore, regularization schemes are required to deal with this issue. The impacts of the initial guess for tissue elasticity distribution, contrast ratio between elastic modulus of tumor and normal tissue, and noise level of the input data on the estimated solutions are investigated via two different regularization methods. The numerical results show that the accuracy and speed of convergence vary when different regularization methods are applied. Also, the semi-convergence behavior has been observed and discussed. At the end, we signify the necessity of a clever initial guess and intelligent stopping criteria for the iterations. The main purpose here is to highlight some technical factors that have an influence on elasticity image quality and diagnostic accuracy, and we have tried our best to make this article accessible for a broad audience.