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Accurate wavelet thresholding method for ECG signals

Yu K, Feng L, Chen Y, Wu M, Zhang Y, Zhu P, et al.

Comput Biol Med, 2024 Feb;169:107835.
PMID: 38096762 DOI: 10.1016/j.compbiomed.2023.107835

Current wavelet thresholding methods for cardiogram signals captured by flexible wearable sensors face a challenge in achieving both accurate thresholding and real-time signal denoising. This paper proposes a real-time accurate thresholding method based on signal estimation, specifically the normalized ACF, as an alternative to traditional noise estimation without the need for parameter fine-tuning and extensive data training. This method is experimentally validated using a variety of electrocardiogram (ECG) signals from different databases, each containing specific types of noise such as additive white Gaussian (AWG) noise, baseline wander noise, electrode motion noise, and muscle artifact noise. Although this method only slightly outperforms other methods in removing AWG noise in ECG signals, it far outperforms conventional methods in removing other real noise. This is attributed to the method's ability to accurately distinguish not only AWG noise that is significantly different spectrum of the ECG signal, but also real noise with similar spectra. In contrast, the conventional methods are effective only for AWG noise. In additional, this method improves the denoising visualization of the measured ECG signals and can be used to optimize other parameters of other wavelet methods to enhancing the denoised periodic signals, thereby improving diagnostic accuracy.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Prenatal auditory stimulation induces physiological stress responses in developing embryos and newly hatched chicks

Hanafi SA, Zulkifli I, Ramiah SK, Chung ELT, Kamil R, Awad EA

Poult Sci, 2023 Feb;102(2):102390.
PMID: 36608455 DOI: 10.1016/j.psj.2022.102390

Prenatal stress may evoke considerable physiological consequences on the developing poultry embryos and neonates. The present study aimed to determine prenatal auditory stimulation effects on serum levels of ceruloplasmin (CPN), alpha-1-acid glycoprotein (AGP), corticosterone (CORT), and heat shock protein 70 (Hsp70) regulations in developing chicken embryos and newly hatched chicks. Hatching eggs were subjected to the following auditory treatments; 1) control (no additional sound treatment other than the background sound of the incubator's compressors at 40 dB), 2) noise exposure (eggs were exposed to pre-recorded traffic noise at 90 dB) (NOISE), and 3) music exposure (eggs were exposed to Mozart's Sonata for Two Pianos in D Major, K 488 at 90 dB) (MUSIC). The NOISE and MUSIC treatments were for 20 min/h for 24 h (a total of 8 h/d), starting from embryonic days (ED) 12 to hatching. The MUSIC (1.37 ± 0.1 ng/mL) and NOISE (1.49 ± 0.2 ng/mL) treatments significantly elevated CPN at ED 15 compared to the Control (0.82 ± 0.04 ng/mL) group and post-hatch day 1 (Control, 1.86 ± 0.2 ng/mL; MUSIC, 2.84 ± 0.4 ng/mL; NOISE, 3.04 ± 0.3 ng/mL), AGP at ED 15 (Control, 39.1 ± 7.1 mg/mL; MUSIC, 85.5 ± 12.9 mg/mL; NOISE, 85.4 ± 15.1 mg/mL) and post-hatch day 1 (Control, 20.4 ± 2.2 mg/mL; MUSIC, 30.5 ± 4.7 mg/mL; NOISE, 30.3 ± 1.4 mg/mL). CORT significantly increased at ED 15 in both MUSIC (9.024 ± 1.4 ng/mL) and NOISE (12.15 ± 1.6 ng/mL) compared to the Control (4.39 ± 0.7 ng/mL) group. On the other hand, MUSIC exposed embryos had significantly higher Hsp70 expression than their Control and NOISE counterparts at ED 18 (Control, 12.9 ± 1.2 ng/mL; MUSIC, 129.6 ± 26.4 ng/mL; NOISE, 13.3 ± 2.3 ng/mL) and post-hatch day 1 (Control, 15.2 ± 1.7 ng/mL; MUSIC, 195.5 ± 68.5 ng/mL; NOISE, 13.2 ± 2.7 ng/mL). In conclusion, developing chicken embryos respond to auditory stimulation by altering CPN, AGP, CORT, and Hsp70. The alterations of these analytes could be important in developing embryos and newly hatched chicks to cope with stress attributed to auditory stimulation.

Matched MeSH terms: Noise/adverse effects
Fulltext Identification of Noise Levels for Skill Training Activities, Equipment, Machines and Power Tools at TVET Institutes in Malaysia

Abdul Rahim KA, Jewaratnam J, Che Hassan CR

Int J Environ Res Public Health, 2022 Nov 27;19(23).
PMID: 36497858 DOI: 10.3390/ijerph192315783

The use of various machines, equipment and power tools at TVET Institute causes the institute's environment to be exposed to noise hazards that are similar to the industry. However, not much data has been published regarding noise exposure at TVET institutes. This study was carried out to document the noise exposure of work activities training in public TVET institutes in Malaysia that implement skill training programs in metal fabrication, furniture manufacturing and automotive maintenance. The identification of excessive noise, task-based noise exposure monitoring and source measurement was conducted. The noise contribution from each work activity to the daily A-weighted noise exposure level and sound pressure level emitted by machines and equipment was documented. The findings of this study recorded 20 activities with task-based noise contribution to the daily A-weighted noise exposure level between 75.3 dB and 95 dB. Based on the findings, the training environment at the TVET institutes has a risk of operating with excessive noise. The documented data can be used in planning the implementation of suitable noise control measures in TVET institutes.

Matched MeSH terms: Noise; Noise, Occupational*
Fulltext Different bimodal neuromodulation settings reduce tinnitus symptoms in a large randomized trial

Conlon B, Hamilton C, Meade E, Leong SL, O Connor C, Langguth B, et al.

Sci Rep, 2022 Jun 30;12(1):10845.
PMID: 35773272 DOI: 10.1038/s41598-022-13875-x

More than 10% of the population suffers from tinnitus, which is a phantom auditory condition that is coded within the brain. A new neuromodulation approach to treat tinnitus has emerged that combines sound with electrical stimulation of somatosensory pathways, supported by multiple animal studies demonstrating that bimodal stimulation can elicit extensive neural plasticity within the auditory brain. More recently, in a large-scale clinical trial, bimodal neuromodulation combining sound and tongue stimulation drove significant reductions in tinnitus symptom severity during the first 6 weeks of treatment, followed by diminishing improvements during the second 6 weeks of treatment. The primary objective of the large-scale randomized and double-blinded study presented in this paper was to determine if background wideband noise as used in the previous clinical trial was necessary for bimodal treatment efficacy. An additional objective was to determine if adjusting the parameter settings after 6 weeks of treatment could overcome treatment habituation effects observed in the previous study. The primary endpoint at 6-weeks involved within-arm and between-arm comparisons for two treatment arms with different bimodal neuromodulation settings based on two widely used and validated outcome instruments, Tinnitus Handicap Inventory and Tinnitus Functional Index. Both treatment arms exhibited a statistically significant reduction in tinnitus symptoms during the first 6-weeks, which was further reduced significantly during the second 6-weeks by changing the parameter settings (Cohen's d effect size for full treatment period per arm and outcome measure ranged from - 0.7 to - 1.4). There were no significant differences between arms, in which tongue stimulation combined with only pure tones and without background wideband noise was sufficient to reduce tinnitus symptoms. These therapeutic effects were sustained up to 12 months after the treatment ended. The study included two additional exploratory arms, including one arm that presented only sound stimuli during the first 6 weeks of treatment and bimodal stimulation in the second 6 weeks of treatment. This arm revealed the criticality of combining tongue stimulation with sound for treatment efficacy. Overall, there were no treatment-related serious adverse events and a high compliance rate (83.8%) with 70.3% of participants indicating benefit. The discovery that adjusting stimulation parameters overcomes previously observed treatment habituation can be used to drive greater therapeutic effects and opens up new opportunities for optimizing stimuli and enhancing clinical outcomes for tinnitus patients with bimodal neuromodulation.

Matched MeSH terms: Noise
Fulltext A Study on Distortion Estimation Based on Image Gradients

Chin SC, Chow CO, Kanesan J, Chuah JH

Sensors (Basel), 2022 Jan 14;22(2).
PMID: 35062601 DOI: 10.3390/s22020639

Image noise is a variation of uneven pixel values that occurs randomly. A good estimation of image noise parameters is crucial in image noise modeling, image denoising, and image quality assessment. To the best of our knowledge, there is no single estimator that can predict all noise parameters for multiple noise types. The first contribution of our research was to design a noise data feature extractor that can effectively extract noise information from the image pair. The second contribution of our work leveraged other noise parameter estimation algorithms that can only predict one type of noise. Our proposed method, DE-G, can estimate additive noise, multiplicative noise, and impulsive noise from single-source images accurately. We also show the capability of the proposed method in estimating multiple corruptions.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Noise Eliminated Ensemble Empirical Mode Decomposition Scalogram Analysis for Rotating Machinery Fault Diagnosis

Faysal A, Ngui WK, Lim MH, Leong MS

Sensors (Basel), 2021 Dec 04;21(23).
PMID: 34884120 DOI: 10.3390/s21238114

Rotating machinery is one of the major components of industries that suffer from various faults due to the constant workload. Therefore, a fast and reliable fault diagnosis method is essential for machine condition monitoring. In this study, noise eliminated ensemble empirical mode decomposition (NEEEMD) was used for fault feature extraction. A convolution neural network (CNN) classifier was applied for classification because of its feature learning ability. A generalized CNN architecture was proposed to reduce the model training time. A sample size of 64×64×3 pixels RGB scalograms are used as the classifier input. However, CNN requires a large number of training data to achieve high accuracy and robustness. Deep convolution generative adversarial network (DCGAN) was applied for data augmentation during the training phase. To evaluate the effectiveness of the proposed feature extraction method, scalograms from related feature extraction methods such as ensemble empirical mode decomposition (EEMD), complementary EEMD (CEEMD), and continuous wavelet transform (CWT) are classified. The effectiveness of scalograms is also validated by comparing the classifier performance using grayscale samples from the raw vibration signals. All the outputs from bearing and blade fault classifiers showed that scalogram samples from the proposed NEEEMD method obtained the highest accuracy, sensitivity, and robustness using CNN. DCGAN was applied with the proposed NEEEMD scalograms to further increase the CNN classifier's performance and identify the optimal number of training data. After training the classifier using augmented samples, the results showed that the classifier obtained even higher validation and test accuracy with greater robustness. The proposed method can be used as a more generalized and robust method for rotating machinery fault diagnosis.

Matched MeSH terms: Noise
Comparison of continuous sampling with active noise cancelation and sparse sampling for cortical and subcortical auditory functional MRI

Dewey RS, Hall DA, Plack CJ, Francis ST

Magn Reson Med, 2021 11;86(5):2577-2588.
PMID: 34196020 DOI: 10.1002/mrm.28902

PURPOSE: Detecting sound-related activity using functional MRI requires the auditory stimulus to be more salient than the intense background scanner acoustic noise. Various strategies can reduce the impact of scanner acoustic noise, including "sparse" temporal sampling with single/clustered acquisitions providing intervals without any background scanner acoustic noise, or active noise cancelation (ANC) during "continuous" temporal sampling, which generates an acoustic signal that adds destructively to the scanner acoustic noise, substantially reducing the acoustic energy at the participant's eardrum. Furthermore, multiband functional MRI allows multiple slices to be collected simultaneously, thereby reducing scanner acoustic noise in a given sampling period.
METHODS: Isotropic multiband functional MRI (1.5 mm) with sparse sampling (effective TR = 9000 ms, acquisition duration = 1962 ms) and continuous sampling (TR = 2000 ms) with ANC were compared in 15 normally hearing participants. A sustained broadband noise stimulus was presented to drive activation of both sustained and transient auditory responses within subcortical and cortical auditory regions.
RESULTS: Robust broadband noise-related activity was detected throughout the auditory pathways. Continuous sampling with ANC was found to give a statistically significant advantage over sparse sampling for the detection of the transient (onset) stimulus responses, particularly in the auditory cortex (P < .001) and inferior colliculus (P < .001), whereas gains provided by sparse over continuous ANC for detecting offset and sustained responses were marginal (p ~ 0.05 in superior olivary complex, inferior colliculus, medial geniculate body, and auditory cortex).
CONCLUSIONS: Sparse and continuous ANC multiband functional MRI protocols provide differing advantages for observing the transient (onset and offset) and sustained stimulus responses.

Matched MeSH terms: Noise*
Correlation between 18F-FDG dosage and SNR on various BMI patient groups tested in NEMA IEC PET phantom

Waeleh N, Saripan MI, Musarudin M, Mashohor S, Ahmad Saad FF

Appl Radiat Isot, 2021 Oct;176:109885.
PMID: 34385090 DOI: 10.1016/j.apradiso.2021.109885

The present study was conducted to determine quantitatively the correlation between injected radiotracer and signal-to-noise ratio (SNR) based on differences in physiques and stages of cancer. Eight different activities were evaluated with modelled National Electrical Manufacturers Association (NEMA) of the International Electrotechnical Commission (IEC) PET's phantom with nine different tumour-to-background ratio (TBR). The findings suggest that the optimal value of dosage is required for all categories of patients in the early stages of cancer diagnosis.

Matched MeSH terms: Signal-To-Noise Ratio
Dorsal Hand Vein Image Enhancement Using Fusion of CLAHE and Fuzzy Adaptive Gamma

Yakno M, Mohamad-Saleh J, Ibrahim MZ

Sensors (Basel), 2021 Sep 27;21(19).
PMID: 34640769 DOI: 10.3390/s21196445

Enhancement of captured hand vein images is essential for a number of purposes, such as accurate biometric identification and ease of medical intravenous access. This paper presents an improved hand vein image enhancement technique based on weighted average fusion of contrast limited adaptive histogram equalization (CLAHE) and fuzzy adaptive gamma (FAG). The proposed technique is applied using three stages. Firstly, grey level intensities with CLAHE are locally applied to image pixels for contrast enhancement. Secondly, the grey level intensities are then globally transformed into membership planes and modified with FAG operator for the same purposes. Finally, the resultant images from CLAHE and FAG are fused using improved weighted averaging methods for clearer vein patterns. Then, matched filter with first-order derivative Gaussian (MF-FODG) is employed to segment vein patterns. The proposed technique was tested on self-acquired dorsal hand vein images as well as images from the SUAS databases. The performance of the proposed technique is compared with various other image enhancement techniques based on mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measurement (SSIM). The proposed enhancement technique's impact on the segmentation process has also been evaluated using sensitivity, accuracy, and dice coefficient. The experimental results show that the proposed enhancement technique can significantly enhance the hand vein patterns and improve the detection of dorsal hand veins.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Digital Filtering Techniques for Performance Improvement of Golay Coded TDM-FBG Sensor

Elgaud MM, Zan MSD, Abushagur AAG, Hamzah AE, Mokhtar MHH, Arsad N, et al.

Sensors (Basel), 2021 Jun 23;21(13).
PMID: 34201845 DOI: 10.3390/s21134299

For almost a half-decade, the unique autocorrelation properties of Golay complementary pairs (GCP) have added a significant value to the key performance of conventional time-domain multiplexed fiber Bragg grating sensors (TDM-FBGs). However, the employment of the unipolar form of Golay coded TDM-FBG has suffered from several performance flaws, such as limited improvement of the signal-to-noise ratio (SNIR), noisy backgrounds, and distorted signals. Therefore, we propose and experimentally implement several digital filtering techniques to mitigate such limitations. Moving averages (MA), Savitzky-Golay (SG), and moving median (MM) filters were deployed to process the signals from two low reflectance FBG sensors located after around 16 km of fiber. The first part of the experiment discussed the sole deployment of Golay codes from 4 bits to 256 bits in the TDM-FBG sensor. As a result, the total SNIR of around 8.8 dB was experimentally confirmed for the longest 256-bit code. Furthermore, the individual deployment of MA, MM, and SG filters within the mentioned decoded sequences secured a further significant increase in SNIR of around 4, 3.5, and 3 dB, respectively. Thus, the deployment of the filtering technique alone resulted in at least four times faster measurement time (equivalent to 3 dB SNIR). Overall, the experimental analysis confirmed that MM outperformed the other two techniques in better signal shape, fastest signal transition time, comparable SNIR, and capability to maintain high spatial resolution.

Matched MeSH terms: Signal-To-Noise Ratio*
Auditory attentional filter in the absence of masking noise

Anandan ES, Husain R, Seluakumaran K

Atten Percept Psychophys, 2021 May;83(4):1737-1751.
PMID: 33389676 DOI: 10.3758/s13414-020-02210-z

Signals containing attended frequencies are facilitated while those with unexpected frequencies are suppressed by an auditory filtering process. The neurocognitive mechanism underlying the auditory attentional filter is, however, poorly understood. The olivocochlear bundle (OCB), a brainstem neural circuit that is part of the efferent system, has been suggested to be partly responsible for the filtering via its noise-dependent antimasking effect. The current study examined the role of the OCB in attentional filtering, particularly the validity of the antimasking hypothesis, by comparing attentional filters measured in quiet and in the presence of background noise in a group of normal-hearing listeners. Filters obtained in both conditions were comparable, suggesting that the presence of background noise is not crucial for attentional filter generation. In addition, comparison of frequency-specific changes of the cue-evoked enhancement component of filters in quiet and noise also did not reveal any major contribution of background noise to the cue effect. These findings argue against the involvement of an antimasking effect in the attentional process. Instead of the antimasking effect mediated via medial olivocochlear fibers, results from current and earlier studies can be explained by frequency-specific modulation of afferent spontaneous activity by lateral olivocochlear fibers. It is proposed that the activity of these lateral fibers could be driven by top-down cortical control via a noise-independent mechanism. SIGNIFICANCE: The neural basis for auditory attentional filter remains a fundamental but poorly understood area in auditory neuroscience. The efferent olivocochlear pathway that projects from the brainstem back to the cochlea has been suggested to mediate the attentional effect via its noise-dependent antimasking effect. The current study demonstrates that the filter generation is mostly independent of the background noise, and therefore is unlikely to be mediated by the olivocochlear brainstem reflex. It is proposed that the entire cortico-olivocochlear system might instead be used to alter the hearing sensitivity during focus attention via frequency-specific modulation of afferent spontaneous activity.

Matched MeSH terms: Noise*
Fulltext Optimization of Thermal and Structural Design in Lithium-Ion Batteries to Obtain Energy Efficient Battery Thermal Management System (BTMS): A Critical Review

Fayaz H, Afzal A, Samee ADM, Soudagar MEM, Akram N, Mujtaba MA, et al.

Arch Comput Methods Eng, 2021 Apr 26.
PMID: 33935484 DOI: 10.1007/s11831-021-09571-0

Covid-19 has given one positive perspective to look at our planet earth in terms of reducing the air and noise pollution thus improving the environmental conditions globally. This positive outcome of pandemic has given the indication that the future of energy belong to green energy and one of the emerging source of green energy is Lithium-ion batteries (LIBs). LIBs are the backbone of the electric vehicles but there are some major issues faced by the them like poor thermal performance, thermal runaway, fire hazards and faster rate of discharge under low and high temperature environment,. Therefore to overcome these problems most of the researchers have come up with new methods of controlling and maintaining the overall thermal performance of the LIBs. The present review paper mainly is focused on optimization of thermal and structural design parameters of the LIBs under different BTMSs. The optimized BTMS generally demonstrated in this paper are maximum temperature of battery cell, battery pack or battery module, temperature uniformity, maximum or average temperature difference, inlet temperature of coolant, flow velocity, and pressure drop. Whereas the major structural design optimization parameters highlighted in this paper are type of flow channel, number of channels, length of channel, diameter of channel, cell to cell spacing, inlet and outlet plenum angle and arrangement of channels. These optimized parameters investigated under different BTMS heads such as air, PCM (phase change material), mini-channel, heat pipe, and water cooling are reported profoundly in this review article. The data are categorized and the results of the recent studies are summarized for each method. Critical review on use of various optimization algorithms (like ant colony, genetic, particle swarm, response surface, NSGA-II, etc.) for design parameter optimization are presented and categorized for different BTMS to boost their objectives. The single objective optimization techniques helps in obtaining the optimal value of important design parameters related to the thermal performance of battery cooling systems. Finally, multi-objective optimization technique is also discussed to get an idea of how to get the trade-off between the various conflicting parameters of interest such as energy, cost, pressure drop, size, arrangement, etc. which is related to minimization and thermal efficiency/performance of the battery system related to maximization. This review will be very helpful for researchers working with an objective of improving the thermal performance and life span of the LIBs.

Matched MeSH terms: Noise
Fulltext A Heuristic Approach for Optical Transceiver Placement to Optimize SNR and Illuminance Uniformities of an Optical Body Area Network

Masroor K, Jeoti V, Drieberg M, Cheab S, Rajbhandari S

Sensors (Basel), 2021 Apr 22;21(9).
PMID: 33922288 DOI: 10.3390/s21092943

The bi-directional information transfer in optical body area networks (OBANs) is crucial at all the three tiers of communication, i.e., intra-, inter-, and beyond-BAN communication, which correspond to tier-I, tier-II, and tier-III, respectively. However, the provision of uninterrupted uplink (UL) and downlink (DL) connections at tier II (inter-BAN) are extremely critical, since these links serve as a bridge between tier-I (intra-BAN) and tier-III (beyond-BAN) communication. Any negligence at this level could be life-threatening; therefore, enabling quality-of-service (QoS) remains a fundamental design issue at tier-II. Consequently, to provide QoS, a key parameter is to ensure link reliability and communication quality by maintaining a nearly uniform signal-to-noise ratio (SNR) within the coverage area. Several studies have reported the effects of transceiver related parameters on OBAN link performance, nevertheless the implications of changing transmitter locations on the SNR uniformity and communication quality have not been addressed. In this work, we undertake a DL scenario and analyze how the placement of light-emitting diode (LED) lamps can improve the SNR uniformity, regardless of the receiver position. Subsequently, we show that using the principle of reciprocity (POR) and with transmitter-receiver positions switched, the analysis is also applicable to UL, provided that the optical channel remains linear. Moreover, we propose a generalized optimal placement scheme along with a heuristic design formula to achieve uniform SNR and illuminance for DL using a fixed number of transmitters and compare it with an existing technique. The study reveals that the proposed placement technique reduces the fluctuations in SNR by 54% and improves the illuminance uniformity up to 102% as compared to the traditional approach. Finally, we show that, for very low luminous intensity, the SNR values remain sufficient to maintain a minimum bit error rate (BER) of 10-9 with on-off keying non-return-to-zero (OOK-NRZ) modulation format.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Susceptibility to Residual Inhibition Is Associated With Hearing Loss and Tinnitus Chronicity

Hu S, Anschuetz L, Hall DA, Caversaccio M, Wimmer W

Trends Hear, 2021 3 6;25:2331216520986303.
PMID: 33663298 DOI: 10.1177/2331216520986303

Residual inhibition, that is, the temporary suppression of tinnitus loudness after acoustic stimulation, is a frequently observed phenomenon that may have prognostic value for clinical applications. However, it is unclear in which subjects residual inhibition is more likely and how stable the effect of inhibition is over multiple repetitions. The primary aim of this work was to evaluate the effect of hearing loss and tinnitus chronicity on residual inhibition susceptibility. The secondary aim was to investigate the short-term repeatability of residual inhibition. Residual inhibition was assessed in 74 tinnitus subjects with 60-second narrow-band noise stimuli in 10 consecutive trials. The subjects were assigned to groups according to their depth of suppression (substantial residual inhibition vs. comparator group). In addition, a categorization in normal hearing and hearing loss groups, related to the degree of hearing loss at the frequency corresponding to the tinnitus pitch, was made. Logistic regression was used to identify factors associated with susceptibility to residual inhibition. Repeatability of residual inhibition was assessed using mixed-effects ordinal regression including poststimulus time and repetitions as factors. Tinnitus chronicity was not associated with residual inhibition for subjects with hearing loss, while a statistically significant negative association between tinnitus chronicity and residual inhibition susceptibility was observed in normal hearing subjects (odds ratio: 0.63; p = .0076). Moreover, repeated states of suppression can be stably induced, reinforcing the use of residual inhibition for within-subject comparison studies.

Matched MeSH terms: Noise
Fulltext Experimental Analysis of Heat-Affected Zone (HAZ) in Laser Cutting of Sugar Palm Fiber Reinforced Unsaturated Polyester Composites

Masoud F, Sapuan SM, Ariffin MKAM, Nukman Y, Bayraktar E

Polymers (Basel), 2021 Feb 26;13(5).
PMID: 33652612 DOI: 10.3390/polym13050706

In this paper, the influence of processing input parameters on the heat-affected zone (HAZ) of three different material thicknesses of sugar palm fiber reinforced unsaturated polyester (SPF-UPE) composites cut with a CO2 laser was investigated. Laser power, traverse speed, and gas pressure were selected as the most influential input parameters on the HAZ to optimize the HAZ response with fixing all of the other input parameters. Taguchi's method was used to determine the levels of parameters that give the best response to the HAZ. The significance of input parameters was also determined by calculating the max-min variance of the average of the signal-to-noise ratio (S/N) ratio for each parameter. Analysis of variation (ANOVA) was used to determine each input parameter's contribution to the influence on HAZ depth. The general results show that the minimum levels of laser power and the highest levels of traverse speed and gas pressure gave the optimum response to the HAZ. Gas pressure had the most significant effect on the HAZ, with contribution decreases as the material thickness increased, followed by the traverse speed with contribution increases with the increase in material thickness. Laser power came third, with a minimal contribution to the effect on the HAZ, and it did not show a clear relationship with the change in material thickness. By applying the optimum parameters, the desired HAZ depth could be obtained at relatively low values.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Underwater Object Detection and Reconstruction Based on Active Single-Pixel Imaging and Super-Resolution Convolutional Neural Network

Li M, Mathai A, Lau SLH, Yam JW, Xu X, Wang X

Sensors (Basel), 2021 Jan 05;21(1).
PMID: 33466530 DOI: 10.3390/s21010313

Due to medium scattering, absorption, and complex light interactions, capturing objects from the underwater environment has always been a difficult task. Single-pixel imaging (SPI) is an efficient imaging approach that can obtain spatial object information under low-light conditions. In this paper, we propose a single-pixel object inspection system for the underwater environment based on compressive sensing super-resolution convolutional neural network (CS-SRCNN). With the CS-SRCNN algorithm, image reconstruction can be achieved with 30% of the total pixels in the image. We also investigate the impact of compression ratios on underwater object SPI reconstruction performance. In addition, we analyzed the effect of peak signal to noise ratio (PSNR) and structural similarity index (SSIM) to determine the image quality of the reconstructed image. Our work is compared to the SPI system and SRCNN method to demonstrate its efficiency in capturing object results from an underwater environment. The PSNR and SSIM of the proposed method have increased to 35.44% and 73.07%, respectively. This work provides new insight into SPI applications and creates a better alternative for underwater optical object imaging to achieve good quality.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext An efficient post-processing adaptive filtering technique to rectifying the flickering effects

Gandam A, Sidhu JS, Verma S, Jhanjhi NZ, Nayyar A, Abouhawwash M, et al.

PLoS One, 2021;16(5):e0250959.
PMID: 33970949 DOI: 10.1371/journal.pone.0250959

Compression at a very low bit rate(≤0.5bpp) causes degradation in video frames with standard decoding algorithms like H.261, H.262, H.264, and MPEG-1 and MPEG-4, which itself produces lots of artifacts. This paper focuses on an efficient pre-and post-processing technique (PP-AFT) to address and rectify the problems of quantization error, ringing, blocking artifact, and flickering effect, which significantly degrade the visual quality of video frames. The PP-AFT method differentiates the blocked images or frames using activity function into different regions and developed adaptive filters as per the classified region. The designed process also introduces an adaptive flicker extraction and removal method and a 2-D filter to remove ringing effects in edge regions. The PP-AFT technique is implemented on various videos, and results are compared with different existing techniques using performance metrics like PSNR-B, MSSIM, and GBIM. Simulation results show significant improvement in the subjective quality of different video frames. The proposed method outperforms state-of-the-art de-blocking methods in terms of PSNR-B with average value lying between (0.7-1.9db) while (35.83-47.7%) reduced average GBIM keeping MSSIM values very close to the original sequence statistically 0.978.

Matched MeSH terms: Signal-To-Noise Ratio*
Fulltext InNetGAN: Inception Network-Based Generative Adversarial Network for Denoising Low-Dose Computed Tomography

Kulathilake KASH, Abdullah NA, Bandara AMRR, Lai KW

J Healthc Eng, 2021;2021:9975762.
PMID: 34552709 DOI: 10.1155/2021/9975762

Low-dose Computed Tomography (LDCT) has gained a great deal of attention in clinical procedures due to its ability to reduce the patient's risk of exposure to the X-ray radiation. However, reducing the X-ray dose increases the quantum noise and artifacts in the acquired LDCT images. As a result, it produces visually low-quality LDCT images that adversely affect the disease diagnosing and treatment planning in clinical procedures. Deep Learning (DL) has recently become the cutting-edge technology of LDCT denoising due to its high performance and data-driven execution compared to conventional denoising approaches. Although the DL-based models perform fairly well in LDCT noise reduction, some noise components are still retained in denoised LDCT images. One reason for this noise retention is the direct transmission of feature maps through the skip connections of contraction and extraction path-based DL modes. Therefore, in this study, we propose a Generative Adversarial Network with Inception network modules (InNetGAN) as a solution for filtering the noise transmission through skip connections and preserving the texture and fine structure of LDCT images. The proposed Generator is modeled based on the U-net architecture. The skip connections in the U-net architecture are modified with three different inception network modules to filter out the noise in the feature maps passing over them. The quantitative and qualitative experimental results have shown the performance of the InNetGAN model in reducing noise and preserving the subtle structures and texture details in LDCT images compared to the other state-of-the-art denoising algorithms.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Gaussian smoothing and modified histogram normalization methods to improve neural-biomarker interpretations for dyslexia classification mechanism

Usman OL, Muniyandi RC, Omar K, Mohamad M

PLoS One, 2021;16(2):e0245579.
PMID: 33630876 DOI: 10.1371/journal.pone.0245579

Achieving biologically interpretable neural-biomarkers and features from neuroimaging datasets is a challenging task in an MRI-based dyslexia study. This challenge becomes more pronounced when the needed MRI datasets are collected from multiple heterogeneous sources with inconsistent scanner settings. This study presents a method of improving the biological interpretation of dyslexia's neural-biomarkers from MRI datasets sourced from publicly available open databases. The proposed system utilized a modified histogram normalization (MHN) method to improve dyslexia neural-biomarker interpretations by mapping the pixels' intensities of low-quality input neuroimages to range between the low-intensity region of interest (ROIlow) and high-intensity region of interest (ROIhigh) of the high-quality image. This was achieved after initial image smoothing using the Gaussian filter method with an isotropic kernel of size 4mm. The performance of the proposed smoothing and normalization methods was evaluated based on three image post-processing experiments: ROI segmentation, gray matter (GM) tissues volume estimations, and deep learning (DL) classifications using Computational Anatomy Toolbox (CAT12) and pre-trained models in a MATLAB working environment. The three experiments were preceded by some pre-processing tasks such as image resizing, labelling, patching, and non-rigid registration. Our results showed that the best smoothing was achieved at a scale value, σ = 1.25 with a 0.9% increment in the peak-signal-to-noise ratio (PSNR). Results from the three image post-processing experiments confirmed the efficacy of the proposed methods. Evidence emanating from our analysis showed that using the proposed MHN and Gaussian smoothing methods can improve comparability of image features and neural-biomarkers of dyslexia with a statistically significantly high disc similarity coefficient (DSC) index, low mean square error (MSE), and improved tissue volume estimations. After 10 repeated 10-fold cross-validation, the highest accuracy achieved by DL models is 94.7% at a 95% confidence interval (CI) level. Finally, our finding confirmed that the proposed MHN method significantly outperformed the normalization method of the state-of-the-art histogram matching.

Matched MeSH terms: Signal-To-Noise Ratio
The quantification of PET-CT radiotracers to determine minimal scan time using quadratic formulation

Said MA, Musarudin M, Zulkaffli NF

Ann Nucl Med, 2020 Dec;34(12):884-891.
PMID: 33141408 DOI: 10.1007/s12149-020-01543-x

OBJECTIVE: 18F is the most extensively used radioisotope in current clinical practices of PET imaging. This selection is based on the several criteria of pure PET radioisotopes with an optimum half-life, and low positron energy that contributes to a smaller positron range. In addition to 18F, other radioisotopes such as 68Ga and 124I are currently gained much attention with the increase in interest in new PET tracers entering the clinical trials. This study aims to determine the minimal scan time per bed position (Tmin) for the 124I and 68Ga based on the quantitative differences in PET imaging of 68Ga and 124I relative to 18F.
METHODS: The European Association of Nuclear Medicine (EANM) procedure guidelines version 2.0 for FDG-PET tumor imaging has adhered for this purpose. A NEMA2012/IEC2008 phantom was filled with tumor to background ratio of 10:1 with the activity concentration of 30 kBq/ml ± 10 and 3 kBq/ml ± 10% for each radioisotope. The phantom was scanned using different acquisition times per bed position (1, 5, 7, 10 and 15 min) to determine the Tmin. The definition of Tmin was performed using an image coefficient of variations (COV) of 15%.
RESULTS: Tmin obtained for 18F, 68Ga and 124I were 3.08, 3.24 and 32.93 min, respectively. Quantitative analyses among 18F, 68Ga and 124I images were performed. Signal-to-noise ratio (SNR), contrast recovery coefficients (CRC), and visibility (VH) are the image quality parameters analysed in this study. Generally, 68Ga and 18F gave better image quality as compared to 124I for all the parameters studied.
CONCLUSION: We have defined Tmin for 18F, 68Ga and 124I SPECT CT imaging based on NEMA2012/IEC2008 phantom imaging. Despite the long scanning time suggested by Tmin, improvement in the image quality is acquired especially for 124I. In clinical practice, the long acquisition time, nevertheless, may cause patient discomfort and motion artifact.

Matched MeSH terms: Signal-To-Noise Ratio

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