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Article

Sound-Quality Perception in Hair Dryers: Functional Near-Infrared Spectroscopy Evidence of Left-Lateralized Dorsolateral Prefrontal Cortex Activation

by
Shuang Xu
1,
Zenggen Ren
2,* and
Qingxing Qu
1
1
School of Business Administration, Northeastern University, Shenyang 110167, China
2
College of Economics and Management, Taiyuan University of Technology, Taiyuan 030024, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(8), 4278; https://doi.org/10.3390/app15084278
Submission received: 4 March 2025 / Revised: 7 April 2025 / Accepted: 11 April 2025 / Published: 12 April 2025
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Abstract

:
This study investigates how the sound of a hair dryer influences users’ perceptions of its quality, using functional near-infrared spectroscopy (fNIRS) to measure prefrontal cortex (PFC) activation. Eighteen participants were involved in a within-subject evaluation experiment where they assessed the perceived quality of hair dryers with three different sound levels: no sound, low sound, and high sound. The results show that hair dryers with high sound levels were rated as having higher quality and caused greater increases in oxygenated hemoglobin (HbO) concentration in the dorsolateral prefrontal cortex (DLPFC) compared to soundless hair dryers. In contrast, when participants evaluated low-sound hair dryers, differential activation between the left and right hemispheres was observed, with increased left-brain activity. These findings highlight the significant role of multisensory factors, such as sound, in shaping product perception. Moreover, DLPFC activity, especially in the left hemisphere, emerges as a potential marker for evaluating product quality, contributing new insights to the understanding of sensory-driven decision-making in product evaluation.

1. Introduction

With the advent of modern technologies, the proliferation of functionally analogous products has posed a challenge for consumers in distinguishing and making optimal selections [1]. As a result, users are increasingly focusing on both the utilitarian and emotional aspects of products, a phenomenon that has garnered heightened attention [2]. To address users’ emotional needs concerning products, numerous studies have employed emotional design methods, such as kansei engineering, to enhance the design of various products, including the ear thermometer [3], outdoor leisure chairs [4], and webpages [5], among others. These studies underscore the significant role that product appearance plays in the evaluation of perceived quality. However, while visual perception is widely acknowledged to dominate human experience, it does not necessarily imply that people consider visual stimuli as the most crucial sensory input in all interactions with products. The relative importance of different sensory modalities may vary depending on the type of product and the tasks performed [6]. Users often evaluate products not solely through visual cues but also through other sensory modalities, such as auditory, tactile, gustatory, and olfactory sensations, to assess the overall product experience. For instance, consumers may evaluate a product’s perceived quality based on its appearance, sound, and other elements. Multisensory design strategies have been proposed to explore how various sensory inputs in a product and its services interact to shape user perception, with research indicating that users’ perceptions of a product can be enhanced or diminished by different sensory combinations [7]. Within multisensory designs, researchers have extensively emphasized the impact of auditory information on the perceived quality of a product, complementing visual aspects [8,9]. For example, irregular or non-smooth sounds, such as squeaks and rattles in automobiles, are typically interpreted as signs of poor quality and are common sources of customer complaints [10]. In contrast, engine noise is often associated with vehicle power and performance rather than discomfort [11]. Atamer and Altinsoy [12] investigated dishwasher sound quality using four psychoacoustic descriptors—loudness, sharpness, roughness, and pitch—and found that loudness and clarity played key roles in user evaluations.
To objectively assess the influence of sound on perceived product quality, the present study employs functional near-infrared spectroscopy (fNIRS) to investigate the impact of product sound using a hair dryer as the target object. fNIRS is a non-invasive neuroimaging technique that uses near-infrared light to monitor changes in oxygenated and deoxygenated hemoglobin (ΔHbO and ΔHbR) in the cerebral cortex [13,14]. It offers a favorable balance between spatial and temporal resolution while remaining portable, user-friendly, and well-suited for product-related studies conducted in realistic settings [15,16]. Although fNIRS has been widely applied in cognitive and affective research, its use in the domain of product sound evaluation remains limited.
To fulfill the research objectives, three different levels of hair dryer sound intensity were devised. During the evaluation of the hair dryer’s perceived quality, participants were presented with both the visual depiction and sound of the hair dryer, while their fNIRS signals and perceived quality assessments were concurrently recorded. The PFC has consistently been identified as a key cortical region involved in cognition, playing a crucial role in cognitive control and emotional regulation [17,18]. In particular, activity changes in the bilateral DLPFC are especially responsive to stimulation. As a result, this study monitored only ΔHbO and ΔHbR signals in the PFC. The primary aims of this study were twofold: (1) to examine the influence of hair dryer sound intensity on users’ perceptual quality ratings, providing product designers and manufacturers with critical insights into consumer preferences, and (2) to analyze alterations in fNIRS metrics during the evaluation of perceived product quality, offering a novel approach to understanding neural responses associated with sound intensity. The outcomes of this investigation are anticipated to offer insights into the design of products such as hair dryers, as well as to provide methodologies for the assessment of perceived quality in product design.

2. Related Work

2.1. Effects of Product Sound Design

Research has demonstrated that users’ perceptions of a product can be either enhanced or diminished by various sensory stimuli [7]. Sound quality testing has emerged as a crucial design consideration for products, including machinery, appliances, and assemblies [19]. For instance, the interior sound quality significantly influences vehicle quality assessment, shaping users’ overall impressions of vehicles and affecting consumers’ purchase intentions [20]. Several studies have highlighted the adverse effects of sound during product usage, such as refrigerator noise [21], air conditioner noise [22], and small motors for automotive interior components [23]. However, attitudes toward product sound may vary among users. For example, some studies indicate that loud hair dryers are perceived as noisy and discomforting [19], and reducing hair dryer noise can increase users’ willingness to purchase the product [24]. Conversely, certain studies propose that noise levels are sometimes misinterpreted by users as indicative of product capacity, implying that the right amount of loudness correlates with better usability [25,26]. Similarly, Symanczyk [27] noted a paradox concerning vacuum cleaner sounds: “you can make them very silent, but then they will not be perceived as very powerful”. Therefore, further investigation is warranted into the impact of product sound on consumers’ perceived quality, particularly for products like hair dryers and vacuum cleaners.

2.2. Methods of Evaluating Perceived Quality of Product

Numerous studies have employed subjective measures to evaluate the perceived quality of products [3,28,29]. Participants’ perceptions of product characteristics are often quantified using a Likert scale [30]. Although subjective measures provide convenience and direct insights, their outcomes can be influenced by internal participant factors like emotional state, motivation, and social environment [31]. With the rapid advancement of technologies in human–robot interaction (HRI), some studies have sought to incorporate physiological measures to investigate participants’ internal states, offering alternative avenues for assessing users’ perceptions of products. These objective measures include a range of techniques for assessing perceived product quality, including eye-tracking, electroencephalography (EEG), electrocardiogram (ECG), and functional near-infrared spectroscopy (fNIRS), among others. For example, eye-tracking technology has been utilized in numerous studies to evaluate users’ perceptions of products such as phones [32], LED desk lamps [33], and watches [34]. Furthermore, existing studies have confirmed that auditory stimuli can indeed lead to changes in EEG signals across different brain regions [35,36]. Xie et al. [37] explored users’ perceptions of vehicle acceleration sounds using EEG. Although these studies have endeavored to evaluate the perceived quality of products through physiological measurement techniques like EEG and eye-tracking, the majority of these inquiries have remained fixated on unidimensional aspects such as product appearance or sound. This tendency has resulted in a noticeable gap in the examination of multisensory product design. Moreover, while EEG signals offer high temporal resolution information, their experimental manipulation is complex, and their signal quality is vulnerable to external environmental influences. Consequently, many researchers have turned to fNIRS as an alternative to EEG for investigating neural activity related to cognition [38,39]. fNIRS offers unique advantages compared to fMRI and EEG, including portability, convenience, minimal physical constraints on participants, and a favorable balance between temporal and spatial resolutions [15,16]. Despite its widespread use in studies related to cognitive activity, there have been relatively few investigations utilizing fNIRS to explore product perceived quality. Only Wang et al. [40] examined the relationship between fNIRS signals and product aesthetic evaluation. However, these studies did not account for the impact of sound features on perceived product quality.

3. Materials and Methods

3.1. Participants

The study randomly recruited 18 college students, of whom 9 were females, from a nearby university. College students were chosen for their availability and homogeneity in terms of cognitive and sensory responsiveness, which helped control inter-individual variability. The participants ranged in age from 21 to 25 years, and all confirmed being right-handed, in good health, and free from psychiatric disorders [41]. Only right-handed participants were recruited to reduce inter-subject variability in cortical activation patterns, as handedness is known to influence hemispheric lateralization of brain functions, particularly in the prefrontal cortex, which was the focus of our fNIRS measurements. Table 1 presents the demographic information of the participants. Before commencing the study, each participant gave informed consent. The study protocol was approved by the Northeastern University Research Ethics Committee (approval number: NEU-EC-2023B011S).

3.2. Stimuli

To control for other product characteristics, such as weight, that might influence quality evaluations, this study used only picture displays with accompanying sound effects without allowing participants to handle the actual products. Pictures of three hair dryers with similar design styles were selected as stimulus material for the study, as hair dryers are commonly used in everyday scenarios and have been favored by many researchers investigating perceived product quality [42]. To mitigate the potential influence of product size on users’ evaluations of perceived quality, referring to the study of Yanagisawa and Miyazaki [26], the experiment utilized pictures of handheld hair dryers as the stimulus material, as depicted in Figure 1. All stimulus images were standardized to identical dimensions (1440 × 900 pixels), presented against a black background, and uniformly colored white. This ensured consistency across visual stimuli and minimized the influence of color or background on participants’ perception. The sounds of the hair dryers were recorded using a microphone positioned near a typical hair dryer. Subsequently, the recorded sounds were adjusted to 50 dB (low sound) and 75 dB (high sound) using Praat software (Version 5.3.85; Paul Boersma and David Weenink, Amsterdam, The Netherlands) [43]. The “low” and “high” sound levels were selected based on the typical operating noise levels of the hair dryers. Each picture stimulus was paired with a no-sound stimulus, a low-sound stimulus, and a high-sound stimulus, respectively.

3.3. Procedure

The evaluation experiment was conducted in a specialized university laboratory dedicated to fNIRS research, maintaining controlled noise and lighting conditions. Upon arrival, participants were provided with a concise overview of the experimental protocol and completed a questionnaire containing demographic information such as age and gender. Afterward, they were seated in a comfortable position facing a 22-inch LCD monitor with a resolution of 1440 × 900 pixels and a refresh rate of 60 Hz, through which the experimental stimuli were displayed. Participants were then equipped with the fNIRS experimental equipment. Clear instructions were provided to ensure participants understood the task, following which stimuli were presented in a randomized sequence. Each stimulus was displayed for 6 s [18], accompanied by the product sound played through a Bluetooth stereo connected to the experimental computer, while participants observed the hair dryer product. Prior to each stimulus, a blank screen with a cross was shown for 10 s to allow participants’ blood oxygen signals to return to baseline [44]. Baseline regression is a critical step in ensuring the reliability of neural activity measurements [45]. Following each stimulus, participants were instructed to evaluate the overall impression of the hair dryer using a numerical scale ranging from 1 to 7 on the keyboard, where higher numbers denoted higher perceived quality. The experiment lasted approximately 40 min, including the pre-experimental setup. During the experiment, each stimulus was repeated six times to ensure reliable data collection and to account for variability in participants’ responses. The six repetitions of each stimulus were presented in a randomized order to minimize potential order effects and habituation biases. The experimental procedure was programmed and controlled using E-Prime 2.0 (Psychology Software Tools, Inc., Pittsburgh, PA, USA), and the experimental design is shown in Figure 2.

3.4. fNIRS Data Acquisition and Analysis

A portable LIGHTNIRS system manufactured by Shimadzu Corp. in Kyoto, Japan, was utilized to record ΔHbO and ΔHbR in the PFC, as illustrated in Figure 3.
In this experiment, eight optode emitters and eight detectors were strategically placed to cover the PFC, resulting in 22 measurement channels, as depicted in Figure 4. Specifically, channel 19 was aligned with the Fpz point according to the 10–20 international system. The sampling frequency for signals was set at 13.33 Hz. Additionally, a 3D Fastrak digitizer was utilized to accurately determine the spatial coordinates of optical probes using four anchor points (NZ, CZ, AL, and RL) as references [46].
The fNIRS data underwent processing using the NIRS_KIT toolbox v3.0 [47] within MATLAB (R2021a, MathWorks, Inc., Natick, MA, USA). Processing steps encompassed detrending, motion correction based on Temporal Derivative Distribution Repair (TDDR) [48], and filtering with a bandpass filter set between 0.01 and 0.08 Hz. The decision to use 0.08 Hz as the low-pass cutoff was based on common practices in fNIRS and neuroimaging studies, where this frequency range is typically selected to remove low-frequency noise and physiological artifacts, such as respiration and heart rate, while preserving the neural activity signals of interest [47]. Then, the ΔHbO and ΔHbR signals of each channel were averaged across the entire task period of 6 s for each stimulus presentation. Based on the estimation results in Montreal Neurological Institute (MNI) spatial coordinates to obtain the corresponding Brodmann areas (BAs) [49], two regions of interest were delineated, comprising the left and right DLPFC, as outlined in Table 2. The ΔHbO and ΔHbR of the left and the right DLPFC were computed by averaging the ΔHbO and ΔHbR data from these channels.

3.5. Statistical Analyses

All collected data underwent normality testing using the Shapiro–Wilk test before proceeding to further analysis, confirming that they followed a normal distribution. Subsequently, the repeated measures analysis of variance (RMANOVA) was employed, with partial eta squared (ηp2) utilized as the measure of effect size. The RMANOVA pertaining to perceived quality scores involved sound at three levels (no sound vs. low sound vs. high sound), while the RMANOVA concerning fNIRS data included sound at three levels (no sound vs. low sound vs. high sound) and sites (left DLPFC vs. right DLPFC). Post hoc analyses with Bonferroni corrections were used for multiple comparisons. All statistical analyses were performed using IBM SPSS Statistics for Windows, Version 23.0 (Armonk, NY, USA: IBM Corp.), with a significance level (α) set at 0.05.

4. Results

4.1. Perceived Quality Scores

Figure 5 displays the mean and standard error of perceived quality scores. The results of the one-way RMANOVA revealed a significant impact of sound on the perceived quality of the hair dryer [F(2,34) = 5.057, p = 0.012, ηp2 = 0.229]. Post hoc tests indicated that the hair dryer with high sound had the highest perceived quality score (M = 5.61, SD = 0.99), whereas the hair dryer with no sound had the lowest perceived quality score (M = 4.85, SD = 1.13). The difference between these two conditions was statistically significant (p = 0.01). Notably, no significant differences were observed between the low sound condition (M = 5.28, SD = 0.89) and the high sound condition (p = 0.518) or between the low sound condition and the no sound condition (p = 0.252).

4.2. fNIRS Data

Figure 6 illustrates the changes in HbO and HbR concentrations of CH10 over time during a typical task trial, and Figure 7 illustrates the cerebral activity of users during no sound, low sound, and high sound stimuli. The results of the two-way RMANOVA revealed that the main effect of sound approached significance [F(2,34) = 3.264, p = 0.051, ηp2 = 0. 161], and a significant interaction effect between sound and brain area was observed [F(2,34) = 4.256, p = 0.022, ηp2 = 0.200]. Analyzing the simple effect of sound, it was found that the high sound of the hair dryer induced a nearly higher ΔHbO in users’ left DLPFC compared to no sound (p = 0.053). However, no significant differences were detected in users’ left DLPFC between low sound and high sound (p = 1) or between low sound and no sound (p = 0.105). Similarly, high sound induced a nearly higher ΔHbO in users’ right DLPFC than no sound (p = 0.076). Yet, no significant differences were observed in users’ right DLPFC between low sound and high sound (p = 0.357) or between low sound and no sound (p = 1). In terms of brain area, the ΔHbO in users’ left DLPFC was higher than in users’ right DLPFC when the product had low sound (p = 0.029). However, no significant differences were found between left DLPFC and right DLPFC when the product had high sound (p = 0.877) or no sound (p = 0.443).
The results of the two-way RMANOVA indicated that neither the main effect of brain area [F(1,17) = 0.465, p = 0.505, ηp2 = 0.027], the main effect of sound [F(2,34) = 0.390, p = 0.680, ηp2 = 0. 022], nor the interaction between sound and brain area [F(2,34) = 0.04, p = 0.961, ηp2 = 0.002] were significant. Figure 8 illustrates the block-average ΔHbO and ΔHbR of DLPFC in different experimental conditions.

5. Discussion

5.1. Perceived Quality Evaluation Results

Some studies have indicated that the loudness of hair dryer noise contributes to discomfort [19], and reducing the sound of a hair dryer may enhance users’ willingness to purchase the product [24]. However, contrary to these findings, our study revealed that hair dryers with high sound had the highest perceived quality score, while those with no sound had the lowest. Perceived quality ratings for low-sound hair dryers fell between those for high-sound and no-sound variants. Kumar, Wing, and Lee [25] suggested that higher noise levels are sometimes psychologically interpreted by users as indicative of greater product capacity. Evidently, in evaluating the perceived quality of the hair dryer, users may consider the sound of the blowing process as an indicator of the dryer’s capabilities. When information from multiple sensory modalities conflicted, potentially eliciting a surprise response, products with appropriate incongruity were more enjoyable and preferred [50]. The hair dryers utilized in our experiments were compact, and when paired with high sound stimuli, they may have evoked a sense of surprise among users, thereby enhancing their perception of the product’s quality.

5.2. fNIRS Results

Previous research has shown that increases in ΔHbO are often associated with decreases in ΔHbR [16,51]. This relationship is explained by the link between increased blood flow, higher ΔHbO levels, and lower ΔHbR levels [52]. Notably, ΔHbO is typically more sensitive than ΔHbR during neurovascular coupling [16,51,53]. These findings align with the results of this study, which found significant differences between conditions in the ΔHbO metric but not in the ΔHbR metric.
Weder et al. [54] explored the correlation between the intensity of acoustic stimuli and fNIRS responses, revealing that high-intensity stimulation elicits robust near-infrared spectral responses. However, they also suggested that brain activation in response to varying stimulus intensities is more influenced by individual perceptions of loudness rather than the physical properties of the stimulus. Our study yielded similar findings. Specifically, we observed a significant interaction effect between sound and brain area. High sound induced a notably higher ΔHbO in both the left and right DLPFC compared to no sound. Previous studies have suggested that elevated cognitive workload can result in increased ΔHbO in the DLPFC [55,56]. One possible explanation is that users expend more cognitive resources when perceiving pictures accompanied by sound stimuli, particularly as the loudness of the sound increases. Additionally, variations in ΔHbO could arise from different emotional responses elicited by the stimuli. Previous studies have shown that both positive and negative emotional states can trigger activation in the PFC [57,58]. The introduction of appropriate incongruity in a product enhances enjoyment and favorability [50]. Hence, it is plausible that the high-sounding hair dryer, compared to the soundless one, evoked a positive emotional experience, leading to variations in ΔHbO in the DLPFC, a hypothesis supported by the perceived quality score of the product.
The study revealed that ΔHbO in users’ left DLPFC was higher than that in the right DLPFC when the product emitted low sound. However, no significant differences were observed between the left and right DLPFC when the product emitted high sound or no sound. Research on emotion processing suggests that activation in the left DLPFC is more pronounced during positive affective states, whereas activation in the right DLPFC is more prominent during negative affective states [59,60,61]. When users were exposed to soundless pictures or high sound stimuli, both hemispheres processed the information similarly. However, when confronted with low sound stimuli, certain positive feelings were elicited in users, resulting in increased activity in the left brain regions. While our findings reveal significant correlations between fNIRS signals and perceived product quality, these results do not imply causality. The observed neural activations may reflect processes associated with, but not necessarily causing, changes in perceived quality. Future studies employing causal inference methods or experimental manipulations would be needed to establish directional relationships.

5.3. Implications and Limitations

This study explored the impact of hair dryer sound on users’ perceived product quality using fNIRS measurements. Our findings indicate that high-sound hair dryers received higher perceived quality scores and induced greater changes in users’ ΔHbO in the DLPFC compared to soundless hair dryers. When participants evaluated the perceived quality of low-sound hair dryers, differential activation between the left and right hemispheres was observed, with increased left-brain activity relative to the right hemisphere. These findings emphasize the beneficial impact of multisensory product design on perceived quality. Additionally, the study provides an objective method for assessing product design quality through fNIRS measurements, with DLPFC activity, particularly in the left hemisphere, serving as a potential marker for evaluating product quality. The study contributes to the literature on multisensory product design and neuroscience applications in perceived quality and product development. By identifying that higher sound levels can correlate with increased perceptions of quality, the article challenges the conventional preference for quieter designs. This is particularly relevant in contexts where sound conveys functionality or power. While the study focuses on hair dryers, its findings could be extended to other industries, such as automotive design, where sound plays a crucial role in conveying quality (e.g., engine or interior component noises).
However, the study has several limitations that warrant acknowledgment. Firstly, only three small hair dryers were used as stimulus materials; it is important to acknowledge that in real-world scenarios, different hair dryers typically possess distinct spectral signatures. These spectral differences can influence user perception and product evaluation. Future research could explore how varying spectral characteristics across devices contribute to perceived quality, offering a more ecologically valid assessment. Secondly, the study solely focused on the effect of sound loudness on perceived quality, neglecting other design features of hair dryer sound, such as pitch. Future research could explore the effects of specific sound frequencies or intensities on DLPFC activity to provide a more comprehensive understanding of the neural mechanisms involved in auditory processing and its relationship with emotional responses. Thirdly, the participants recruited for this study were all college students, which limits the generalizability of the findings. The relatively small sample size in this study may limit the statistical power of the analysis. Future research should consider recruiting a large number of participants from diverse age groups and backgrounds to enhance the applicability of the results and statistical power of the analysis. Fourthly, this study focused solely on the PFC without a whole-brain assessment. Future research should consider examining activity in other brain regions during product quality evaluations. Additionally, perceived quality is heavily influenced by numerous factors, including the environmental context in which the product is used, and the study’s controlled laboratory conditions may not fully capture real-world scenarios. Future research should focus on conducting evaluations in more realistic settings to validate the findings.

6. Conclusions

This study investigated how the sound of a hair dryer influences users’ perceptions of the product’s quality using fNIRS measurements. The results indicated that hair dryers emitting high sound levels received higher perceived quality scores and induced more pronounced changes in users’ ΔHbO in the DLPFC compared to soundless hair dryers. However, the differences between low-sound hair dryers and high-sound hair dryers, as well as between low-sound hair dryers and those with no sound, were not statistically significant. Interestingly, when users assessed the perceived quality of the low-sound hair dryer, there was differential activation between the left and right hemispheres, with greater left-brain activity relative to the right hemisphere. These findings underscore the advantageous impact of multisensory product design on perceived quality, implying that DLPFC activity, particularly in the left hemisphere, could serve as a marker for evaluating product quality.

Author Contributions

Conceptualization, S.X. and Q.Q.; methodology, S.X. and Z.R.; formal analysis, S.X. and Z.R.; investigation, S.X. and Z.R.; writing—original draft preparation, S.X.; writing—review and editing, Q.Q.; visualization, Z.R.; supervision, Q.Q.; funding acquisition, Q.Q. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China, grant number 72301061.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Northeastern University Research Ethics Committee (protocol code: NEU-EC-2023B011S, approval date: 13 March 2023).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets generated during the current study are available through the following link: https://github.com/neurzg/fNIRS_data (accessed on 10 April 2025). This repository contains all the relevant data and materials that support the findings of our study.

Acknowledgments

We would like to acknowledge the participants of the study for their time and involvement in the experiment.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AOIArea of Interest
DLPFCDorsolateral prefrontal cortex
ECGElectrocardiogram
EEGElectroencephalography
fMRIFunctional Magnetic Resonance Imaging
fNIRSFunctional near-infrared spectroscopy
HbOOxygenated hemoglobin
HbRDeoxygenated hemoglobin
HRIHuman–robot interaction
LCDLiquid Crystal Display
LEDLight-Emitting Diode
SDStandard Deviation
TDDRTemporal Derivative Distribution Repair

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Figure 1. The hair dryer pictures used in the experiment. (a) hair dryer 1; (b) hair dryer 2; (c) hair dryer 3. All the hair dryers are grasped by right hands, and each picture was paired with three sound levels: no sound, low sound, and high sound.
Figure 1. The hair dryer pictures used in the experiment. (a) hair dryer 1; (b) hair dryer 2; (c) hair dryer 3. All the hair dryers are grasped by right hands, and each picture was paired with three sound levels: no sound, low sound, and high sound.
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Figure 2. The schema of the experimental paradigm.
Figure 2. The schema of the experimental paradigm.
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Figure 3. Portable functional near-infrared spectral imaging equipment.
Figure 3. Portable functional near-infrared spectral imaging equipment.
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Figure 4. Schematic diagram of optode emitters (red), detector (blue), and channel (yellow).
Figure 4. Schematic diagram of optode emitters (red), detector (blue), and channel (yellow).
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Figure 5. Perceived quality scores for each condition. Error bars represent the standard error of the mean. A rating of 7 indicates the highest perceived quality, and 0 indicates the lowest. * denotes statistical significance at p < α = 0.05.
Figure 5. Perceived quality scores for each condition. Error bars represent the standard error of the mean. A rating of 7 indicates the highest perceived quality, and 0 indicates the lowest. * denotes statistical significance at p < α = 0.05.
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Figure 6. The changes in HbO and HbR concentrations of CH10 over time during a typical task trial.
Figure 6. The changes in HbO and HbR concentrations of CH10 over time during a typical task trial.
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Figure 7. Cerebral activity of users during (a) no sound, (b) low sound, and (c) high sound stimulus. HbO = oxygenated hemoglobin; HbR = deoxygenated hemoglobin.
Figure 7. Cerebral activity of users during (a) no sound, (b) low sound, and (c) high sound stimulus. HbO = oxygenated hemoglobin; HbR = deoxygenated hemoglobin.
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Figure 8. Cerebral activity of users in different experimental conditions: (a) ΔHbO, (b) ΔHbR, * depicts p < 0.05. HbO = oxygenated hemoglobin; HbR = deoxygenated hemoglobin.
Figure 8. Cerebral activity of users in different experimental conditions: (a) ΔHbO, (b) ΔHbR, * depicts p < 0.05. HbO = oxygenated hemoglobin; HbR = deoxygenated hemoglobin.
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Table 1. Participant demographics and characteristics.
Table 1. Participant demographics and characteristics.
CharacteristicDetails
Sample Size18
Age (M ± SD)22.61 ± 0.98
Age Range21~25 years
Gender DistributionMale: 50%; Female: 50%
Health StatusAll participants reported no psychiatric or neurological disorders.
Left-hander/right-handerAll participants were right-handed.
Experience with Hair Dryers100% of participants reported prior experience using hair dryers.
Table 2. The MIN coordinates of fNIRS channels and corresponding brain regions.
Table 2. The MIN coordinates of fNIRS channels and corresponding brain regions.
Area of Interest (AOI)ChannelMNI CoordinatesBrodmann Area (BA)Overlap
XYZ
Right DLPFCCH0325.1353.2037.93BA9—DLPFC0.75
CH1037.6955.1924.78BA46—DLPFC0.95
CH1747.3750.7412.48BA46—DLPFC0.82
Left DLPFCCH05−20.1354.0938.59BA9—DLPFC0.80
CH13−32.0457.4324.35BA46—DLPFC0.90
CH21−41.6355.2410.02BA46—DLPFC0.75
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Xu, S.; Ren, Z.; Qu, Q. Sound-Quality Perception in Hair Dryers: Functional Near-Infrared Spectroscopy Evidence of Left-Lateralized Dorsolateral Prefrontal Cortex Activation. Appl. Sci. 2025, 15, 4278. https://doi.org/10.3390/app15084278

AMA Style

Xu S, Ren Z, Qu Q. Sound-Quality Perception in Hair Dryers: Functional Near-Infrared Spectroscopy Evidence of Left-Lateralized Dorsolateral Prefrontal Cortex Activation. Applied Sciences. 2025; 15(8):4278. https://doi.org/10.3390/app15084278

Chicago/Turabian Style

Xu, Shuang, Zenggen Ren, and Qingxing Qu. 2025. "Sound-Quality Perception in Hair Dryers: Functional Near-Infrared Spectroscopy Evidence of Left-Lateralized Dorsolateral Prefrontal Cortex Activation" Applied Sciences 15, no. 8: 4278. https://doi.org/10.3390/app15084278

APA Style

Xu, S., Ren, Z., & Qu, Q. (2025). Sound-Quality Perception in Hair Dryers: Functional Near-Infrared Spectroscopy Evidence of Left-Lateralized Dorsolateral Prefrontal Cortex Activation. Applied Sciences, 15(8), 4278. https://doi.org/10.3390/app15084278

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