Peaks In Frequency Bands Research Articles

Analysis of vibration signals near ground surface during blasting excavation of a tunnel in fractured rock

This study aims to analyze the vibration signals near the ground surface due to the underneath drilling and blasting activities in a fissured rock tunnel. Blasting induced vibration on the ground surface was continuously monitored in a fissured rock tunnel drilling and blasting excavation project in field. Wavelet packet analysis of the vibration signals using Matlab was carried out for signal denoising, differential blasting delay time interval identification, and three-way time-frequency energy analysis. The results show that within a 30 m range from the palm face, the dominant frequency bands of blasting-induced vibrations on the ground surface were concentrated in the range of 0–130 Hz. Two prominent peak frequency bands were identified at 31.25–39.063 Hz (low-frequency band) and 93.75–101.56 Hz (high-frequency band), accounting for 12% of the total energy. Among the three directions of ground surface vibrations, the energy decay was the most significant in the x-direction (tunnel excavation direction), which amounted to 54.29% of the overall energy decay with increasing distance. The energy decay within the 50–80 Hz range was the most pronounced (more than 90%), when the angle between the vibration propagation direction and the fissure or joint direction was 75°. The conclusions provide the insights in the attenuation of blast-induced vibrations in fissured rock and can potentially assist in the design of blasting vibration control.

A preliminary study on generation of axle box vibration spectra for metro vehicles in China using the developed spectral synthesis method

ABSTRACT In-service metro vehicles in China exhibit diverse vibration behaviours. This study focuses on analysing the vibration characteristics of these vehicles, with a particular focus on the complex non-stationary axle box vibrations measured on-site, as they closely correlate with wheel-rail interaction dynamics. A developed PSD-based synthesis method is first proposed to quantify the axle box vibration. The axle box vibration spectra of the metro vehicles in China are then generated from the measurements for various vehicles. Furthermore, a multi-line segment flat spectrum, designed specifically for the shaker loading, has been produced. The results show that the proposed method can determine the parameters (segment number, quantile) by the energy conservation law, which avoids the empirical value selection in previous methods and can be effectively utilized to generate the vibration spectra of the axle box. In addition, a notable distinction exists between the IEC 61,373 standard spectrum and the axle box vibration spectra of Chinese metro vehicles. While the former represents a single-peak spectrum ranging from 20 ~ 100 Hz, the latter consists of a multi-peak spectrum with peak frequency bands exceeding 100 Hz. The wear condition of the wheel-rail surface has a pronounced contribution to the vibration spectral magnitude. In cases of wheel-rail surface severe wear, the vibration spectrum values in the Z direction surpass the standard spectrum values across most frequencies, with the highest spectral value notably observed within 50 ~ 200 Hz. Such observations should be thoroughly taken into account in the analysis of fatigue damage to mounted equipment.

Analysis of noise reduction measures in a noise workshop handover control room

Objective: To explore the sound insulation, sound absorption and other noise reduction transformation methods in a noise workshop handover control room. Methods: In December 2021, through the occupational health investigation and on-site testing of the handover control room of a noise workshop, the causes of excessive noise were analyzed, and the transformation design scheme to reduce noise was proposed and the effect was analyzed. Results: Before the transformation, the peak frequency band noise intensity of the noise workshop handover control room was 112.8 dB (A), and the peak frequency was 1000 Hz. After noise reduction, the theoretical calculated control value was 61.0 dB (A), and the measured noise intensity was 59.8 dB (A) . Conclusion: The noise intensity of the handover control room is reduced after noise reduction, which is in line with the contact limit requirements of the control room in GBZ 1-2010 "Hygienic Standards for the Design of Industrial Enterprises", and has reference significance for noise control engineering.

Numerical Analysis of the Flow-induced Whistling Noise of Ventilation Wall Based on Fluid-structure Coupling Method

As a widely used device in the field of air cooling and heat dissipation of electronic equipment, ventilation walls often have the problem of whistling caused by airflow. This paper presents a numerical study on the flow-induced whistling noise of a ventilation wall. Firstly, the interior flow field of the ventilation wall under typical working conditions was calculated. Secondly, the structure wet mode of the ventilation wall was calculated considering the airflow influence on the structural vibration. Thirdly, taking the fluid pressure fluctuation at the surfaces of the ventilation wall as excitation source, the structural vibration and radiation noise of ventilation wall was simulated, respectively. Finally, the structure of the ventilation wall was optimized to reduce the whistling noise. The results show that the high velocity airflow causes strong fluid-structure coupling of the ventilation wall. Besides, the peak frequency band of whistling noise ranges from 112Hz to 125Hz, and the maximum sound pressure level (SPL) reaches 87.3dB. Moreover, by improving the structure of ventilation wall, the maximum SPL of whistling noise deceases about 10.5dB, which significantly reduces the flow-induced noise. In conclusion, this paper could provide a method for reducing the flow-induced noise of ventilation walls.

Ultrathin self-assembly MXene/Co-based bimetallic oxide heterostructures as superior and modulated microwave absorber

• The customized flower-like Co-based heterostructures (CoO/MCo 2 O 4 , M=Fe, Cu, Zn) were successfully synthesis through identical hydrothermal route. • The introduction of different metal ions enables to modulate the components, heterogeneous interfaces and defects for tailoring the electromagnetic parameters. • The permittivity decreases gradually in the order of Fe 2+ , Cu 2+ , Zn 2+ , making it possible to tune absorption peak position and frequency band. • When filler content is 10 wt%, the CoO/CuCo 2 O 4 possesses RL min of –52.67 dB and corresponding EAB of 4.48 GHz at 1.90 mm. Lightweight and high-efficiency absorbing materials equipped with tunable electromagnetic properties are the foremost important factors for driving applications of 5G smart era and military stealth. Stimulated by the remarkable merits of heterogeneous interface engineering, a series of unique flower-like Co-based multiphases nanostructures were successfully synthesized through identical hydrothermal method, and subsequently anchored on the Ti 3 C 2 T x nanosheets. The suitable metal ion modulation is feasible to regulate the components, heterogeneous interfaces and defects for tailoring the electromagnetic parameters and microwave absorption (MA) property. Notably, the permittivity decreases of CMOT (CoO/MCo 2 O 4 /Ti 3 C 2 T x , M=Fe, Cu, Zn) composites proceed gradually in the order of Fe 2+ , Cu 2+ , Zn 2+ , while the MA performance with tunable absorption peak could be modulated subtly. The as-obtained CFOT-12 (10 wt%), CCOT-15(10 wt%) and CZOT-15 (15 wt%) exhibit excellent MA capacity with a minimum reflection loss (RL min ) of –41.06, –52.67, –52.52 dB and corresponding effective absorption bandwidth (EAB) of 3.68, 4.48, 3.92 GHz at 2.10, 1.90, 1.80 mm, respectively. This work expands a novel approach to construct multicomponent heterostructure for tuning the EM parameters and absorbing property, as well as realize the high efficient and light weight.

100-MW-Level Experiments of a Gyromagnetic Nonlinear Transmission Line System

The wideband high-power microwave systems have the advantages of wide energy spectrum, electron beam independence, compactness, and low cost. The gyromagnetic nonlinear transmission line (GNLTL) has drawn much attention for its potential as a novel solid-state, frequency-agile, and compact wideband source. The working mechanism of GNLTL is different from that of the traditional electric vacuum tubes, and the strong dispersion and nonlinear characteristics make it difficult to be accurately theoretically calculated and simulated. In this article, a 100-MW-level GNLTL system based on a Tesla-type driver was designed and constructed. A series of test experiments were then carried out to investigate the effects of different configurations, including delay line length, ferrite cores’ assembly orientation, transmission line length, bias magnetic field magnitude, and excitation voltage. The changing laws of the key parameters of the output microwaves including the peak power, modulation depth, center frequency, and percentage band are summarized and the underlying physical mechanisms are analyzed. The results may be instructive for the predesign of GNLTLs, especially for the devices operating at high power. In addition, a multiple center frequency points’ phenomenon was discovered in the output signal, which may bring new application possibilities for GNLTL.

Fabrication and characteristics of electret using fine silica powder and its application of ultrasonic sensor

Electrets were prepared by spin-coating the dispersion of fine silica powders, and their charge retention characteristics were investigated. Finer silica aggregates were formed on the PTFE surface layer by spin-coating the dispersed solution of fine silica powder than those formed by spray-coating colloidal silica. Electrets using fine silica powder also showed better charge retention characteristics than those using colloidal silica. Such an improvement in the charge retention might be due to the suppression of discharge in the excessive gap caused by coarse silica aggregates. Then, ECSs were fabricated using the prepared electrets, and their transmitting and receiving characteristics of airborne ultrasound were also investigated. The peak sensitivity of the ECS using a spin coating of fine powdered silica dispersion was slightly improved from those using spray coating of colloidal silica. On the other hand, the peak frequency and frequency band were greatly improved using spin coating of fine powdered silica dispersion. Therefore, ECS using fine silica powder is expected to be applied as a broadband airborne ultrasonic sensor.

Induced gravitational waves from the cosmic coincidence

The induced gravitational wave (GW) background from enhanced primordial scalar perturbations is one of the most promising observational consequences of primordial black hole (PBH) formation from inflation. We investigate the induced GW spectrum ΩIGW from single-field inflation in the general ultra-slow-roll (USR) framework, restricting the peak frequency band to be inside 10-3-1 Hz and saturating PBH abundance to comprise all dark matter (DM) in the ultralight asteroid-mass window. By invoking successful baryogenesis driven by USR inflation, we verify the viable parameter space for the specific density ratio between baryons and PBH DM observed today, the so-called “cosmic coincidence.” We show that the cosmic coincidence requirement bounds the spectral index n UV in the high frequency limit, ΩIGW(f ≫ 1) ∝ f -2n UV , into 0 < n UV < 1, which implies that baryogenesis triggered by USR inflation for PBHs in the mass range of 10-16-10-12 M⊙ can be tested by upcoming Advanced LIGO and Virgo data and next generation experiments such as LISA, Einstein Telescope, TianQin and DECIGO.

A novel crank inerter with simple realization: Constitutive model, experimental investigation and effectiveness assessment

The inerter-based device is of increasing interest to scholars in the field of structural vibration control, which is characterized by apparent mass and negative stiffness effects. With this regard, it is potential to develop variable negative stiffness characteristics with the technology of inerter, which is promising to provide improved performance for structural vibration isolation and vibration suppression. In this study, the theoretical analysis and experimental investigation of a novel inerter element, named crank inerter, is performed. The presented crank inerter is proposed to generate a variable negative stiffness effect, which is realized on the basis of a crank mechanism. A constitutive model of crank inerter is developed to predict its mechanical behavior. For an in-depth understanding of the inertial property of the crank inerter, a parametric analysis is conducted on the inertia force calculation of the crank inerter. A prototype crank inerter is fabricated and tested under sinusoidal excitations to verify the proposed constitutive model. A variable negative stiffness of the crank inerter is reflected from the proposed constitutive model. The theoretical results calculated with the proposed constitutive model match well with the experimental data, which verifies that the proposed model can predict the mechanical behavior of the crank inerter. The dynamic analysis of a vibration isolator with a crank inerter is conducted to illustrate its effectiveness using the proposed constitutive model. The analysis results preliminarily show that the isolator with crank inerter can improve the structural performances regarding the peak force transmissibility and frequency band. Based on the presented investigations, a crank inerter with a simple configuration is summarized to be effective for providing an apparent mass effect and variable negative stiffness.

Transient neural oscillations reveal new biomarkers for therapeutic transcranial magnetic stimulation for comorbid MDD and PTSD

Abstract Repetitive transcranial magnetic stimulation (TMS) is a therapy for major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). TMS effectiveness varies across patients and optimal protocols are unknown. Electroencephalography (EEG) examines brain dynamics associated with TMS often in highly averaged data (Zandvakili et al, 2019). In non-averaged signals, EEG oscillations may emerge as high power transients, coined “events” (Jones, 2016; Shin et al, 2017). We applied methods to analyze event features to describe biomarkers of TMS and their relationship to clinical outcomes. We collected resting 8-channel EEG before and after therapeutic TMS for 23 patients with comorbid MDD and PTSD targeting the left dorsolateral prefrontal cortex. Using our open-source toolbox (https://github.com/jonescompneurolab/SpectralEvents), we tested if resting state oscillations can be quantified as events in non-averaged data using 2-second windows. We assessed if event characteristics – event rate, power, duration, frequency span – changed after TMS or correlated with symptom improvement. Averaged omnibus power spectral density revealed peaks in frequency bands including delta/theta (1-6 Hz), alpha (7-14 Hz), and beta (15-29 Hz). Transient high-power events emerged from non-averaged data. Overall, frontal delta/theta and alpha event number and medial delta/theta event duration decreased after TMS (all p < 0.05). Pretreatment event characteristics correlated with subsequent clinical response. Frontal delta/theta event frequency span negatively correlated with MDD & PTSD improvement; medial alpha event power and duration positively correlated with MDD improvement, whereas medial alpha event rate and duration positively correlated with PTSD improvement; and frontal beta duration negatively correlated with PTSD improvement (all r2 > 0.15). Novel methods to characterize spectral events in non-averaged signals identified periods of high power activity in resting EEG data and revealed changes in event features potentially predictive of TMS response. EEG-recorded events ultimately may provide new biomarkers of response and a better mechanistic understanding of TMS. Keywords: Transcranial magnetic stimulation, Resting state EEG, Major depressive disorder, Post-traumatic stress disorder

Acoustic emission behavior of polyvinyl alcohol (PVA) fiber reinforced calcium sulphoaluminate cement mortar under flexural load

The purpose of this study was to study the failure mechanism, fiber bridging and slip mechanism of PVA fiber reinforced calcium sulphoaluminate cement mortar (CSAM) under bending load. Firstly, the flexural toughness performance of PVA fiber reinforced CSAM was studied. Then, the change of acoustic emission (AE) behaviors was studied, including the change of AE parameters (counts and energy), the cracking mode reflected by the average frequency (AF) and RA values, the peak frequency and Ib value. The results showed that PVA fiber could significantly improve the flexural properties of CSAM. In contrast to PVA0, the AE count and energy of fiber reinforced CSAM remained at a high level after the peak load. The excellent bonding property between fibers and MPC paste didn't always lead to the strong local maximum of RA and the strong local minimum of AF at the time of main fracture. Compared with PVA fiber reinforced CSAM, the failure of specimen PVA0 was only controlled by tensile cracks. The peak frequency bands of 20–50 kHz, 90–110 kHz and 290–320 kHz, respectively corresponded to the friction and pull-out of the fiber, the matrix cracking of CSAM and the propagation and development of macro-cracks.

Optimization of Damage Equivalent Accelerated Test Spectrum Derivation Using Multiple Non‐Gaussian Vibration Data

The response spectra are widely used in the damage assessment of non‐Gaussian random vibration environments and the derivation of damage equivalent accelerated test spectrum. The effectiveness of the latter is strongly affected by modal parameter uncertainties, multiple field data processing, and the nonsmooth shape of the derived power spectral density (PSD). Optimization of accelerated test spectrum derivation based on dynamic parameter selection and iterative update of spectrum envelope is presented in this paper. The extreme response spectrum (ERS) envelope of the field data is firstly taken as the limiting spectrum, and the corresponding relationship between damping coefficient, fatigue exponent, and damage equivalent PSD under different test times is constructed to achieve the dynamic selection of uncertain parameters in the response spectrum model. Then, an iterative update model based on the weighted sum of fatigue damage spectrum (FDS) error is presented to reduce the error introduced by the nonsmooth shape of the derived PSD. The case study shows that undertest can be effectively avoided by the dynamic selection of model parameters. The weighted error is reduced from 80.1% to 7.5% after 7 iterations. Particularly, the error is close to 0 within the peak and valley frequency band.

Nondestructive detection of the interfacial failure of steel-polymer sandwich composites during forming process

Steel-polymer composites have low density, high specific flexural stiffness and vibration damping properties over other metal materials. However, the weak interfaces between steel and polymer sheet are the typical locations where the failure occurs. Furthermore, interfacial failure is a fatal reason of the degradation of mechanical properties. Therefore, predicting interfacial failure of the final product is an important technology in commercialization of steel-polymer composites. In this study, we built forming limit diagram (FLD) based on two different failure modes: failure of the bottom skin steel and interfacial failure between the skin steel and core polymer. Acoustic emission (AE) technique was conducted to observe the interfacial failure moment. Peak frequency was found to be the key feature to distinguish interfacial failure. Peak frequency band that indicates interfacial failure was from 300 kHz to 500 kHz. This peak frequency band made it possible to build FLD considering the interfacial failure.

Methodology and experimental validation for generating periodic focused waves in a wave flume

A new methodology is proposed for generating multiple focused waves within a relatively short time. This can improve the efficiency of the hydrodynamic testing of coastal and offshore structures under extreme wave conditions with strong nonlinearity and randomness, such as in extreme wave impact testing of vessels and offshore platforms. In this study, two methods for generating periodic focused waves were proposed based on a first-order wavemaker theory and Schäffer's second-order wavemaker theory. Periodic focused waves were generated in a wave flume with an intermediate water depth with different peak frequencies, wave amplitudes, frequency bands, frequency resolutions, and nominal periods using the first-order and second-order wavemaker theories. The test results demonstrate that both first-order and second-order wavemaker methods can produce repetitive focused wave groups within a short time period. However, the second-order wavemaker method can reduce the influence of second-order free harmonics. The frequency band and resolution only slightly influence the envelope of the focused wave group for the NewWave-type focused waves in the present study. It is possible to generate periodic focused waves with any equivalent or different time intervals, but the interactions between different focused wave groups should be examined to determine an optimal nominal period.

An Experimental Investigation of White Matter Venous Hemodynamics: Basic Physiology and Disruption in Neuroinflammatory Disease.

The white matter is highly vascularised by the cerebral venous system. In this paper, we describe a unique blood oxygen-level dependent (BOLD) signal within the white matter using functional MRI and spatial independent components analysis. The signal is characterized by a narrow peak frequency band between 0.05 and 0.1 Hz. Hypercapnia, induced transient increases in white matter venous BOLD that disrupted the oscillation indicative of a vasocontractile mechanism. Comparison of the white matter venous BOLD oscillations between 14 healthy subjects and 18 people with perivenular inflammation due to multiple sclerosis (MS), revealed loss of power in the white matter venous BOLD signal in the peak frequency band (patients = 6.70 ± 0.94 dB/Hz vs. controls = 7.64 ± 0.71 dB/Hz; p = 0.006). In MS, lower power was associated with greater levels of neuroinflammatory activity (R = −0.64, p = 0.006). Using a signal modeling technique, we assessed the anatomical distribution of white matter venous BOLD signal abnormalities and detected reduced power in the periventricular white matter, a region of known venous damage in MS. These results demonstrate a novel link between neuroinflammation and vascular physiological dysfunction in the cerebral white matter, and could indicate enduring loss of vascular compliance associated with imperfect repair of blood-brain barrier damage after resolution of acute neuroinflammation.

Alterations of medial prefrontal cortex bioelectrical activity in experimental model of isoprenaline-induced myocardial infarction.

BackgroundClinical and animal studies have found that anxiety and depression are significantly more common after acute myocardial infarction (AMI). The medial prefrontal cortex (PFC) has a dual role: in higher brain functions and in cardiovascular control, making it a logical candidate for explaining the perceived bidirectional heart-brain connection. We used parallel Electrocardiography (ECG) and Electrocorticography (ECoG) registration to investigate AMI-induced changes in medial PFC bioelectrical activity in a rat model of AMI.Materials and methodsAdult male Wistar albino rats were used in the study. Gold-plated recording electrodes were implanted over the frontal cortex for ECoG recording. ECG was recorded via two holter electrodes attached on the skin of the back fixed in place by a jacket. Induction of AMI was performed by isoprenaline (150 mg/kg, i.p.). ECoG and ECG signals were registered at baseline, during 3 hours after isoprenaline administration and at 24 hours after isoprenaline administration.ResultsSignificant increases of theta, alpha, and beta electroencephalographic (EEG) band power were observed in different time intervals after isoprenaline administration. Significant increase of theta band peak frequency was also observed during the first hour after isoprenaline administration. No statistically significant differences in band-power activity were found between the pre-isoprenaline measurements and 24 hours after administration.ConclusionOur results demonstrate significant increases in EEG band power of alpha beta and theta bands during isoprenaline-induced AMI model. These are the first findings to connect heart damage during isoprenaline- induced AMI to disturbances in the cortical bioelectrical activity.

Optimisation of acoustic emission wavestreaming for structural health monitoring

Structural health monitoring has gained wide appeal for applications with high inspection costs, such as aircraft and wind turbines. As the structures and materials used in these industries evolve, so too must the technologies used to monitor them. Acoustic emission is a passive method of detecting damage which lends itself well to structural health monitoring. One form of acoustic emission monitoring, known as wavestreaming, involves intermittently recording data for set periods of time and using the sequential recordings to detect changes in the state of the structure. However, at present, there is no standard method for selecting appropriate wavestream recording parameters, such as their length or their interval of collection. This article investigates a method of optimising acoustic emission wavestreaming for structural health monitoring purposes by introducing the novel concept of adjoining consecutive discrete acoustic emission hit signals to create synthetic wavestreams. To this end, a pre-notched 492 mm × 67.5 mm × 20 mm, 300M grade steel cantilever specimen was subject to cyclic loading and both acoustic emission hit data and conventional wavestreams were collected as a crack grew in the notched region; crack growth activity was also monitored using digital image correlation for comparison. To demonstrate the proposed optimisation process, four sets of synthetic wavestreams were created from the hit data, 0.25, 0.5, 1.0 and 1.5 s in length, and compared with the 1.5-s-long conventional wavestreams. The activity of the peak frequency and frequency centroid bands of interest within the conventional and synthetic wavestreams were examined to determine whether or not cracking activity could be inferred through them. Across comparisons of all data, it was found that the 0.5-s-long synthetic wavestreams contained enough information to identify the same trends as the conventional wavestreams for this application; thus, the use of synthetic wavestreams as a tool for selecting an appropriate wavestream recording length was demonstrated.

Acoustic properties of fracture of dental restorative materials and endocrown restorations under quasi-static loading

Objectives(1) To investigate the properties of acoustic emission (AE) signals from fracture of dental materials and endocrown restorations during quasi-static compression using the continuous wavelet transform analysis. (2) To determine by the parameters of AE signals in which structural element of tooth-endocrown system the fracture starts. MethodsFive restorative materials (zirconium dioxide (Prettau zirconia), ceramics (IPS e.max Press), metal ceramics (GC Initial MC+Nicrallium N2 BCS), composite resin (Nano Q), luting cement (Relyx™ U200)) were manufactured into discs, 13mm diameter, 5mm thick, which were divided into 5 groups (Group B, C, D, E, F, respectively) and included into Type 1. Twenty-five extracted human molars were divided into 5 groups and included into Type 2: Group A (control, no restoration); BE (tooth restored by zirconium dioxide endocrowns); CE (restored by ceramic endocrowns); DE (restored by metal ceramic endocrowns); EE (restored by composite resin endocrowns). An increasing load was applied to the center of the samples with a hard steel ball until a fracture occurred. The loading rate was 0.12mm/min. Two-channel AE detection system was used to record the AE activity during testing. The parameters including the peak frequency, bandwidth, duration time and energy of AE signals were analyzed. ResultsThe restorative materials (Type 1) differ from each other by acoustic properties such as the peak frequency main bands and energy of AE signals. The detected AE signals correspond to the different fracture types. The dominant fracture mechanism of Group C, E and F specimens was the macrocracking (brittle fracture), and of Group D specimens was the microcracking, which alternated with the plastic deformation and macrocracking. For the number of events corresponding to the brittle fracture, statistically significant differences (p<0.05) were found between all group pairs. AE signals were not released during compression test of the zirconium dioxide samples, thus the fracture was not detected.All the AE signals detected during compression test of the different endocrown systems (Type 2) had two peak frequency bands. The fracture of Groups A, BE, CE and DE samples characterized by alternating the micro- and macrocracking with plastic deformation, and the brittle fracture was the dominant fracture mechanism. The restorations of Group EE fractured without plastic deformation. For the number of events corresponding to the brittle fracture, statistically insignificant differences (p>0.05) were found between Groups A vs CE and A vs EE, and statistically significant differences (p<0.05) were found between Groups A vs BE and A vs DE. SignificanceThe initiation of fracture in the restorations with endocrowns made from different materials begins with the tooth damage. The metal ceramic endocrown restoration showed the highest fracture resistance, what is especially important for clinical use.

Study of Metrics that Could be Considered as Inputs to an Intelligent System for Diagnosing Schizophrenia based on an Electroencephalogram (EEG)

Intelligent systems are now part of human daily life. This justifies its application in various fields. However, the field of psychiatry still seems to be at a disadvantage. In this paper, we are interested in measures that can be used as input to an intelligent system for detecting brain diseases using an electroencephalogram (EEG). Indeed, spectral analysis and the study of brain connectivity are two methods of EEG analysis that can be used to characterize schizophrenia. The spectral analysis allows to calculate the power (absolute and relative), the frequency peak among others. Concerning the study of cerebral connectivity, the Phase Lag Index (PLI), which is an adjacency matrix ; which is an adjacency matrix used to assess brain connectivity. Once the PLI is obtained, units such as degree, density and strength on each channel are calculated. These units are evaluated on twenty (28) EEGs, fourteen (14) of people suffering from schizophrenia and fourteen (14) of healthy people. Once the PLI is obtained, units such as degree, density and strength on each channel are calculated. These units are evaluated on twenty (28) EEGs, fourteen (14) of people suffering from schizophrenia and fourteen (14) of healthy people. On the other hand, the value of strength is always lower in sick people than in healthy people. This is true regardless of the frequency band or channel used. This study shows that values such as degree, density, strength of a predefined adjacency matrix, then power, peak frequency band can be used as input values of an intelligent system for diagnosing psychiatric or brain diseases such as schizophrenia.

Study of Metrics that Could be Considered as Inputs to an Intelligent System for Diagnosing Schizophrenia based on an Electroencephalogram (EEG)

Intelligent systems are now part of human daily life. This justifies its application in various fields. However, the field of psychiatry still seems to be at a disadvantage. In this paper, we are interested in measures that can be used as input to an intelligent system for detecting brain diseases using an electroencephalogram (EEG). Indeed, spectral analysis and the study of brain connectivity are two methods of EEG analysis that can be used to characterize schizophrenia. The spectral analysis allows to calculate the power (absolute and relative), the frequency peak among others. Concerning the study of cerebral connectivity, the Phase Lag Index (PLI), which is an adjacency matrix ; which is an adjacency matrix used to assess brain connectivity. Once the PLI is obtained, units such as degree, density and strength on each channel are calculated. These units are evaluated on twenty (28) EEGs, fourteen (14) of people suffering from schizophrenia and fourteen (14) of healthy people. Once the PLI is obtained, units such as degree, density and strength on each channel are calculated. These units are evaluated on twenty (28) EEGs, fourteen (14) of people suffering from schizophrenia and fourteen (14) of healthy people. On the other hand, the value of strength is always lower in sick people than in healthy people. This is true regardless of the frequency band or channel used. This study shows that values such as degree, density, strength of a predefined adjacency matrix, then power, peak frequency band can be used as input values of an intelligent system for diagnosing psychiatric or brain diseases such as schizophrenia.