Fluctuation Strength Research Articles

The impact of outdoor soundscapes at nursing homes on physiological indicators in older adults

This research explores the impact of outdoor soundscapes at nursing homes on the physiological health of older adults. Using virtual reality, the study recreated the outdoor environments at nursing homes for 57 seniors in a lab setting, continuously monitoring physiological indicators such as skin conductance level, heart rate, low to high-frequency heart rate variability ratio, respiratory frequency, blink frequency, and pupil diameter. The comparison of these indicators with corresponding soundscapes revealed the diverse effects of different nursing home outdoor scenarios on the physiological health of older adults. Furthermore, analysis of the temporal marginal effects of these indicators highlighted the significant influence of time on the physiological responses of seniors in various soundscapes, showing fluctuations in each indicator at different times. Finally, to understand the channels of impact, the study examined how acoustic features at nursing homes affect seniors' physiological indicators. The findings suggest that increased loudness and roughness in soundscapes elevate seniors' heart rates and cardiovascular risks, while a moderate increase in LAeq and fluctuation strength in dynamic scenarios might have positive stimulative effects on the physiological functions of the older adults.

Car Door Sound Quality Assessment - A Review for NVH Performance Research

Customer comfort in terms of NVH is a tangible and in-tangible effect. NVH is directly and indirectly connected to the psychoacoustics of human beings and lives. As a part of the advanced NVH analysis, the effects of noise have been studied in terms of psychoacoustic parameters such as loudness, sharpness, roughness, fluctuation strength, tonality, etc. Car door or door assembly is an integral part of the car or vehicle. The door is softly and flexibly connected to the main body of the vehicle; it protects passengers from weather effects and accidental impacts. Because of the inherent flexibility of the door, its flexible connections, sharp - transient closing, and vehicle operational excitations, the door assembly is one of the main sources of noise and vibration in vehicles. It is a prime requirement to understand the NVH effect of doors on vehicles, its analysis and ways of improvement. To understand the current status of the basic and advanced NVH analysis of the door, an extensive survey and in detail study was conducted. The main focus is given on technical papers published related to noise/ sound quality (SQ) during the last two decades, i.e., between 1999 – 2022. Total 31 technical papers were scrutinized and summarized in different categories. Broadly divided into: the number of papers published each year, Number of papers on types of SQ assessment, and the number of papers discussed SQ parameters. This study of these 31 papers published between 1999 – 2022 has given a ready reference for the work done on sound quality, mainly related to the vehicle and its door NVH. The total number of parameters considered by different researchers and approaches used by them to assess the psychoacoustic parameters of noise/ sound. Finally, these parameters and their level help to determine the quality of the sound produced or generated by any source.

Weak interannual variability of sea–air carbon flux in the Tropical Pacific Ocean simulated by CMIP6 models

Air–sea carbon fluxes (FCO2) simulated by 20 CMIP6 models in the pre-industrial control experiments are analyzed. 13 models can simulate the dominant role of the equatorial Pacific (EP) in the interannual variation of global FCO2, which is related to ENSO. Compared with CMIP5, CMIP6 has improved the simulation performance of interannual variation of global FCO2, while for the simulation of FCO2 in the tropical Pacific, most CMIP6 models inherit some biases of their CMIP5 versions. For example, the simulated interannual fluctuation of precipitation leads to excessive interannual variations of the dissolved inorganic carbon (DIC) concentration and then of the partial pressure of CO2 at the sea surface (pCO2sea) in the western tropical Pacific, especially in the warm pool. Another inherited disadvantage is the underestimated interannual fluctuation of FCO2 in the central tropical Pacific from 120ºW to 180ºW. The underestimation includes two aspects: the simulated intensity of the fluctuation is weak, and the negative response region of CO2 outgassing to the ENSO index is narrow. There are two main reasons for the weak interannual fluctuation strength of FCO2 in the models. One is that most models cannot represent the strong interannual variation of 10 m wind speed (vm10) in the central tropical Pacific, and the other is that the interannual fluctuation of pCO2sea in the central tropical Pacific in most models is too weak, which is related to the overestimated interannual variation of sea surface temperature (SST) here. The underestimated spatial range of negative response of CO2 outgassing to the ENSO index is mainly induced by the simulated interannual variations of the vm10 and of the vertical transport of DIC which is related to the vertical upwelling rate. According to the simulation results of CMIP6, the improvement of the simulation performance of the interannual variations of the global and tropical Pacific FCO2 is still dependent on the improvement of the simulation performance of physical climate, such as wind fields, SST, and the entrainment velocity at the bottom of the mixed layer.

Computational model for predicting sound quality metrics using loudness model based on gammatone/gammachirp auditory filterbank and its applications

Sound quality metrics (SQMs), such as sharpness, roughness, and fluctuation strength, have been utilized to study the perceived pleasantness or unpleasantness of sounds. Computational models for predicting SQMs have been proposed, commonly based on Zwicker's loudness method (ISO 532B:1975). ISO 532 was revised in 2017; Moore & Glasberg's loudness method for stationary sound was adopted in ISO 532-2:2017, while Zwicker's loudness method for stationary and time-varying sound was revised in ISO 532-1:2017. There are a few important differenterences between the two methods, such as the frequency scale (Bark scale or ERB scale) and filter shape (symmetry or asymmetry). It therefore might be necessary to revise these computational models for predicting SQMs on the basis of these revisions. We previously proposed a time-domain computational model for predicting SQMs on the basis of a loudness method using the time-domain auditory filterbank. This loudness method can be regarded as a time-domain version of Moore & Glasberg's method in ISO 532-2:2017, using gammatone/gammachirp auditory filterbanks instead of the roex auditory filterbank, which does not have any time-domain representations. In this paper, we introduce calculations for three SQMs (sharpness, roughness, and fluctuation strength) using the proposed model for predicting SQMs.

Design of alert sound for electric vehicle based on fluctuation strength for amplitude fluctuation

The motor sound of an electric vehicle is quiet at low speeds. Thus, it is difficult for pedestrians to detect vehicles approaching them. This is not only a particular problem for visually impaired people but also for any people who cannot see the approaching vehicle, for example, in a situation where the vehicle comes from behind or an obstacle object. Therefore, the vehicle was designed to provide an alert sound to solve this problem. The UN Regulation No.138 on Quiet Road Transport Vehicles was adopted and published in 2016. The regulation introduces a minimum sound level, spectrum, and frequency shift depending on the speed of the vehicle. However, the regulation of the amplitude fluctuation has not been defined. In this study, it is assumed that pedestrians are aware of approaching gasoline vehicles by hearing the amplitude fluctuations in the exhaust sound. We propose that they can be aware of approaching EV by hearing amplitude fluctuation sounds. Our previous studies found that fluctuation frequency, non-periodic fluctuation, and amplitude envelope influence the sensation of hearing fluctuation or fluctuation strength. Their effects on pedestrian detectability were assessed in an actual environment. The results indicate that these characteristics are effective in detecting approaching vehicles.

Annoyance Prediction of Civil Aircraft Cabin Noise Based on Generalized Additive Models

Noise in civil aircraft cabin is a major contributor to passenger comfort. It is of great significance to predict the noise annoyance by developing a model. However, the low accuracy of linear model and the poor intelligibility of the neural network are the critical problems to be solved. Generalized additive models (GAMs) have become a leading choice for explainable machine learning. This study examines the effectiveness of GAMs in noise annoyance prediction. First, the annoyance of the cabin noise was collected through subjective listening test. Subsequently, three physical acoustic features (sound pressure level, A-weighted sound pressure level, preferred speech interference level) and five psychoacoustic features (loudness, sharpness, roughness, fluctuation strength, tonality) were applied to describe the stimuli. In the third step, three algorithms were used to construct GAMs based on annoyance (dependent variable) and feature parameters (independent variables), and the prediction accuracy was computed by ten-fold cross-validation. The result indicated that GAMs have higher prediction accuracy than linear regression model. The importance of features was evaluated, which is more intelligible than the neural network. This study provides the first assessment of GAMs in the annoyance prediction of civil aircraft cabin noise, and the findings may be of assistance to engineering noise control.

SQAT: a MATLAB-based toolbox for quantitative sound quality analysis

Literature suggests that psychoacoustic metrics, which are established by models firmly based on the human auditory system, are able to better approximate perceptual attributes of sounds in a quantitative manner than conventional metrics based on the sound pressure level. Therefore, psychoacoustic metrics are commonly used as sound quality indicators in practical applications, such as product design or environmental noise assessment, in which human perception plays an important role. However, their calculation is not straightforward and the non-availability of verified, well-documented, open-source implementations in a single environment poses a challenge to reproducible research. In this contribution, we introduce the sound quality analysis toolbox (SQAT), an open-source compilation of MATLAB codes containing the implementation of the following key psychoacoustic metrics: loudness (ISO 532-1:2017), sharpness (DIN 45692:2009), roughness (Daniel & Weber's model), fluctuation strength (Osses et al. model), and tonality (Aures' model). A comprehensive description of the implemented psychoacoustic metrics is provided. Furthermore, a verification study is presented in order to demonstrate the reliability of the implementations, supporting the use of SQAT as a reliable tool for future works in the field of sound quality assessment based on psychoacoustic metrics.

Beyond noise levels: vehicle classification using psychoacoustic indicators from pass-by road traffic noise and their correlations with speed and temperature

Environmental noise control regulations typically employ noise level descriptors to set limits for noise exposure. However, other characteristics of noise, such as frequency content, temporal patterns and masking, have been proven to influence the perception of acoustic environments. In this sense, psychoacoustic indicators offer an objective means of establishing relationships between physical characteristics of noise and the human auditory sensation phenomena. This study explored psychoacoustic indicators of pass-by vehicle noise across different vehicle categories, driving speeds, and temperatures. Moreover, the indicators were exploited as features to train a classification algorithm to predict vehicle category. Over 2000 vehicle noise samples were collected using the Statistical Pass-By (SPB) method, categorized into three classes according to ISO 11819-1, besides an additional class for delivery vans. Correction coefficients were obtained for temperature and speed to noise levels, loudness, roughness, sharpness and fluctuation strength. The differences in these indicators based on vehicle category were then discussed. A vehicle-category predictive model using the three vehicle categories defined in ISO 11819-1 yielded 84% accuracy. Including vans as an extra vehicle category dropped accuracy to 72% due to their misclassification with passenger cars. Combining these two categories increased overall accuracy to 86%. These findings could enable a less visual-dependent vehicle categorization so that vehicle fleets worldwide are more consistently classified in terms of noise. Additionally, psychoacoustic indicators appear to be valuable features for vehicle classification systems aimed to resemble the human auditory experience.

Neurovascular coupling dysfunction of visual network organization in Parkinson's disease

Parkinson's disease (PD) has been showed perfusion and neural activity alterations in specific regions, such as the motor and visual networks; however, the clinical significance of coupling changes is still unknown. To identify how neurovascular coupling changes during the pathophysiology of PD, patients and healthy controls underwent multiparametric magnetic resonance imaging to measure neural activity organization of segregation and integration using amplitude of low-frequency fluctuation (ALFF) and functional connectivity strength (FCS), and measure vascular responses using cerebral blood flow (CBF). Neurovascular coupling was calculated as the global CBF-ALFF and CBF-FCS coupling and the regional CBF/ALFF and CBF/FCS ratio. Correlations and dynamic causal modeling was then used to evaluate relationships with disease-alterations to clinical variables and information flow. Neurovascular coupling was impaired in PD with decreased global CBF-ALFF and CBF-FCS coupling, as well as decreased CBF/ALFF in the parieto-occipital cortex (dorsal visual stream) and CBF/FCS in the temporo-occipital cortex (ventral visual stream); these decouplings were associated with motor and non-motor impairments. The distinctive patterns of neurovascular coupling alterations within the dorsal and ventral visual streams of the visual system could potentially provide additional understanding into the pathophysiological mechanisms of PD.

Altered Neurovascular Coupling in Patients With Mitochondrial Myopathy, Encephalopathy, Lactic Acidosis, and Stroke-Like Episodes (MELAS): A Combined Resting-State fMRI and Arterial Spin Labeling Study.

Coupling between neuronal activity and blood perfusion is termed neurovascular coupling (NVC), and it provides a potentially new mechanistic perspective into understanding numerous brain diseases. Although abnormal brain activity and blood supply have been separately reported in mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes (MELAS), whether anomalous NVC would be present is unclear. To investigate NVC changes and potential neural basis in MELAS by combining resting-state functional MRI (rs-fMRI) and arterial spin labeling (ASL). Prospective. Twenty-four patients with MELAS (age: 29.8 ± 7.3 years) in the acute stage and 24 healthy controls (HCs, age: 26.4 ± 8.1 years). Additionally, 12 patients in the chronic stage were followed up. 3.0 T, resting-state gradient-recalled echo-planar imaging and pseudo-continuous 3D ASL sequences. Amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and functional connectivity strength (FCS) were calculated from rs-fMRI, and cerebral blood flow (CBF) was computed from ASL. Global NVC was assessed by correlation coefficients of CBF-ALFF, CBF-fALFF, CBF-ReHo, and CBF-FCS. Regional NVC was also evaluated by voxel-wise and lesion-wise ratios of CBF/ALFF, CBF/fALFF, CBF/ReHo, and CBF/FCS. Two-sample t-test, paired-sample t-test, Gaussian random fields correction. A P value <0.05 was considered statistically significant. Compared with HC, MELAS patients in acute stage showed significantly reduced global CBF-ALFF, CBF-fALFF, CBF-ReHo, and CBF-FCS coupling (P < 0.001). Altered CBF/ALFF, CBF/fALFF, CBF/ReHo, and CBF/FCS ratios were found mainly distributed in the middle cerebral artery territory in MELAS patients. In addition, significantly increased NVC ratios were found in the acute stroke-like lesions in acute stage (P < 0.001), with a recovery trend in chronic stage. This study showed dynamic alterations in NVC in MELAS patients from acute to chronic stage, which may provide a novel insight for understanding the pathogenesis of MELAS. 2 TECHNICAL EFFICACY: Stage 1.

Realisation of Fractal Grid-Induced Turbulence Strength with PTFV: Effects of Grid Geometry

The unravelling of multilength-scale insert-generated turbulence, particularly, the induced-forcing plays critical role in the fundamental comprehension of energy formation and decay as a function of grid conformation. This study experimentally investigates the flow mechanical characteristics at ReDh = 4.1 × 104 for a regular-grid (RG), single-square-grid (SSG) and six 2D planar space-filling square-fractal-grids (SFG) of different fractal iterations (N), thickness ratios (tr) and blockage ratios (σ) via piezoelectric thin-film flapping velocimetry (PTFV). Thin-film’s tip-deflection (δrms) and voltage response (Vrms) analysis along the grids’ centreline reveals increasing flow fluctuation strength with increasing σ, tr and decreasing N, owing to higher shedding intensity of lower frequency, larger scale energy-containing vortices from thicker first iteration bar. However, higher: energy dissipation rate, centreline mean velocity decrement rate and local deceleration experienced in the turbulence decay region of larger tr grid, along with additional fractal scales lead to less potent flow-structure-interplay on thin-film undulation. More importantly, SSG-generated turbulence enables the generation of average (Vrms, δrms) and millinewton turbulence forcing Frms that are respectively, 9× and 5× larger than RG of similar σ, and 2× larger than the best performing N = 3 SFG. Our findings disclose the importance of grid geometrical management for effective utilisation of turbulence-generating grids in engineering applications.

Acoustic and psychoacoustic characterisation of small-scale contra-rotating propellers

This paper reports an experimental investigation of noise radiation and psychoacoustic evaluation of contra-rotating propellers with different blade counts over multiple emission angles and thrust settings. A series of aeroacoustic and psychoacoustic tests were performed with a contra-rotating propeller rig at the University of Salford, UK, where both propellers’ blade count and their axial separation z were varied at static conditions and constant thrust. The sounds were analysed using conventional acoustic metrics, such as Sound Pressure Level (SPL) and Sound Power Level for tonal, broadband, and overall noise, and using the psychoacoustic Sound Quality Metrics (SQMs) Loudness, Fluctuation Strength, Roughness, Tonality, and Impulsiveness. Configurations with axial separation-to-diameter ratio z/D between 0.2–0.4 exhibited a balance between tonal and broadband noise generation mechanisms, resulting in reduced noise levels and reduced annoyance for on-axis observers. The number of blades played a secondary role on determining noise levels: higher blade counts resulted in lower overall noise levels at larger axial separations, although at shorter distances (z/D<0.2) increasing the blade count led to higher noise levels. The SQMs Loudness, Fluctuation Strength, and Tonality were found to also reach a minimum at z/D=0.3, although increasing the number of propeller blades led to a decrease in Loudness but not in Fluctuation Strength and Tonality. The dominant noise generation mechanisms observed here present a directivity null perpendicular to the propellers’ axis, and no clear trends were observed for acoustic and psychoacoustic metrics at this emission angle. A listening experiment was set up to validate the results of the acoustic and psychoacoustic analysis, and its results suggest that the reported noise annoyance is driven by Loudness, Fluctuation Strength and Tonality metrics (p<0.01) at on-axis radiation, while at 90° emission angle, Loudness (p<0.01) and Tonality (p<0.05) are the main contributors to noise annoyance.

Elastic response of colloidal smectic liquid crystals: Insights from microscopic theory.

Elongated colloidal rods at sufficient packing conditions are known to form stable lamellar or smectic phases. Using a simplified volume-exclusion model, we propose a generic equationof state for hard-rod smectics that is robust against simulation results and is independent of the rod aspect ratio. We then extend our theory by exploring the elastic properties of a hard-rod smectic, including the layer compressibility (B) and bending modulus (K_{1}). By introducing weak backbone flexibility we are able to compare our predictions with experimental results on smectics of filamentous virus rods (fd) and find quantitative agreement between the smectic layer spacing, the out-of-plane fluctuation strength, as well as the smectic penetration length λ=sqrt[K_{1}/B]. We demonstrate that the layer bending modulus is dominated by director splay and depends sensitively on lamellar out-of-plane fluctuations that we account for on the single-rod level. We find that the ratio between the smectic penetration length and the lamellar spacing is about two orders of magnitude smaller than typical values reported for thermotropic smectics. We attribute this to the fact that colloidal smectics are considerably softer in terms of layer compression than their thermotropic counterparts while the cost of layer bending is of comparable magnitude.

Procedure for calculating fluctuation strength for marimba tremolo

Procedure for calculating fluctuation strength for marimba tremolo

Predicting vehicle category using psychoacoustic indicators from road traffic pass-by noise

A set of road traffic pass-by noises containing more than 2000 vehicles was recorded following the Statistical Pass-By (SPB) methodology (ISO 11819-1:2022). Besides the acoustic descriptors, psychoacoustic indicators (loudness, sharpness, roughness, fluctuation strength) were retrieved for each pass-by of the three vehicle categories defined in the standard (passenger cars, dual-axles and multi-axles heavy vehicles). A fourth vehicle category, comprised of delivery vans, was also investigated. All psychoacoustic indicators significantly differed among vehicle categories, meaning that not only intensity descriptors but also temporal and spectral features of pass-by noise distinguish those classes. With enough instances and a balanced dataset across groups, a machine-learning classification algorithm was trained with 70% of the dataset to predict vehicle categories using the psychoacoustic indicators. Classification accuracy on the test set reached 72.5%. Accuracy losses were primarily caused by 25% of the actual passenger cars being misclassified as vans and vice-versa. Pooling these two categories increased accuracy to 82%. With more descriptors from road traffic pass-by noise than uniquely its maximum noise level, limiting definitions of vehicle categories may be overcome. As a result, measurements such as the SPB can become broader and vehicle fleets worldwide more consistently represented in terms of noise perception.

Psychoacoustic characteristics of different brake creep groan classes and their subjective noise annoyance in vehicle and half-axle tests

Brake creep groan is a severely annoying noise and vibration phenomenon. Especially on the Asian market, customer feedback about creep groan is common, indicating creep groan’s impact towards the quality impression of a car. Hence, treatment of these stick–slip-related creep groan phenomena is necessary. As numerous design conflicts exist for brake and axle, a complete mitigation of the phenomenon is often not possible. A reduction of creep groan’s annoyance by changing the noise’s level and characteristics is therefore typically aspired. One approach towards this goal could include the usage of psychoacoustics: This work deals with psychoacoustic characteristics of different creep groan classes. Low-frequency groan, high-frequency groan, and transition groan classes are compared regarding loudness, sharpness, roughness, fluctuation strength, and tonality. Standard statistic methods as well as machine learning approaches are applied on signals from vehicle tests and half-axle tests. Test results depict the different characteristics of each creep groan class. By mapping the results to the subjective rating of trained test drivers, the annoyance of different classes is compared. Low-frequency groan, dominated by longitudinal axle vibrations, is found to be least annoying. This low annoyance is best depicted by the psychoacoustic parameters loudness and roughness. Presented results allow an optimization of brake system design to reduce creep groan’s annoyance, leading to higher customer satisfaction and a more goal-oriented treatment of this NVH problem.

Sound quality metric indicators of rotorcraft noise annoyance using multilevel analysis.

It is hypothesized that sound quality metrics, particularly loudness, sharpness, tonality, impulsiveness, fluctuation strength, and roughness, could all be possible indicators of the reported annoyance to helicopter noise. To test this hypothesis, a psychoacoustic test was conducted in which subjects rated their annoyance levels to synthesized helicopter sounds. After controlling for loudness, a previous analysis using linear regression identified sharpness and tonality as important factors in predicting annoyance, followed by fluctuation strength. The current work focuses on multilevel regression techniques in which the regression slopes and intercepts are assumed to take on normal distributions across subjects. The importance of each metric is evaluated, and the variation of regression parameters among subjects is evaluated using simple models. Then more complete models are investigated, which include the combination of selected metrics and subject-specific effects. While the conclusions from linear regression analysis are affirmed by multilevel analysis, other important effects emerge. In particular, subject-specific intercepts are shown to be more important than subject-specific slopes. In addition, subject-specific slopes for fluctuation strength and sharpness are more important than for tonality. Using a multilevel framework, the relative importance of sound quality metrics is reexamined, and the potential for modeling human annoyance to helicopter noise based on sound quality metrics is explored.

A virtual reality tool to aid in soundscapes in the built environment (SiBE) through machine learning

Regarding the function and context of the space, virtual reality (VR) can be used for soundscapes design if the user behavior is predictable. This study enables the acoustic characterization of VR development tools to measure auditory perception based on user behavior. The research question is whether soundscapes can be modeled according to the variable acoustic environments defined by the existing architectural features (e.g., prismatic, courtyard, vault, arched, mezzanine). A sound simulation algorithm in MATLAB was developed to extract room impulse response (RIR) of the test environment in a virtual environment and to compare it with the real environment (RE). In the developed program, image source model (ISM) and ray trace were used to be performed the real-time acoustic source generation and real-time signal recording, image functions, data processing, metric calculation operations (e.g., tonality and spectrogram). B&amp;K 4292 omni-power loudspeaker, B&amp;K 2716 power amplifier, and B&amp;K 2250 hand-held analyzer were used to measure RIR in the RE. In addition to RIR and RT30, psychoacoustic metrics (e.g., loudness, sharpness, roughness, and fluctuation strength) were measured in both environments. The results showed that sound simulation, based on ISM, demonstrates the validity and can be used for the acoustic characterization of VR development environments.

Optimization of a contra-rotating propeller rig for reduced psychoacoustic impact

With unmanned aerial vehicles emerging as potential alternatives for people and cargo transport, their noise impact will be a determining factor in their acceptance by the general public. Contra-rotating propeller configurations are often explored due to their improved aerodynamic performance and redundancy in case of failure compared to conventional single-propeller aircraft, but can be much noisier than their single-propeller equivalent. This work describes the optimization of a custom-made contra-rotating propeller rig for reduced psychoacoustic impact. The rig consists of two electric motors mounted on a rotating stand, positioned inside an anechoic chamber. A far-field microphone arc is used to collect acoustic pressure data, and a load cell is used to measure total thrust. The axial distance between the propellers is varied between 0.1 and 1 rotor diameters, and the number of blades is varied between 2 and 6 on both propellers. Meanwhile, the rpm is adjusted to maintain constant thrust across the different configurations. Acoustic pressure signals are investigated in terms of their physical acoustic characteristics and psychoacoustic features (such as Loudness, Sharpness, Tonality, Fluctuation Strength, Roughness and Impulsiveness) in order to determine the trade-offs and optimal choices in reducing the psychoacoustic impact of the rig.

Relationship between the shape of amplitude envelope and the hearing sensation of fluctuation on the simulated exhaust sound of motorbikes

Previous study showed that procedure for estimating Fluctuation Strength (FS) observing both constant fluctuation and deviation for time and amplitude approximately estimated the hearing sensation of fluctuation from tremolo played on the mandolin. Moreover, another one presented another procedure for estimating FS from exhaust sound of various motorbikes by proposing new indexes about the shape of amplitude envelope. However, the procedure was targeted only the recorded exhaust sound of those motorbikes, wasn't clarified the relationship between the shape and sensation hearing of fluctuation yet. Here, this paper explores acoustic characteristics represent the shape of amplitude envelope and investigates relationship between those characteristics and sensation hearing of fluctuation. Investigations were carried out by using amplitude-fluctuated white noise which were designed to have various acoustic characteristics for the shape. Those white noise have characteristics of amplitude fluctuations in motorbikes. Then, the hearing sensation of fluctuation on those sounds were assessed, investigated relationship between those characteristics and sensation hearing of fluctuation. Concretely, multiple regression analysis was conducted using subjective evaluation results and those characteristics, where slope for rising and falling, duration for rising and falling were calculated. Results showed that those characteristics, especially slope for rising, influences the hearing sensation of fluctuation.