{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:38:26Z","timestamp":1760150306442,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,10,25]],"date-time":"2023-10-25T00:00:00Z","timestamp":1698192000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The main application scenario for wearable sensors involves the generation of data and monitoring metrics. fNIRS (functional near-infrared spectroscopy) allows the nonintrusive monitoring of human visual perception. The quantification of visual perception by fNIRS facilitates applications in engineering-related fields. This study designed a set of experimental procedures to effectively induce visible alterations and to quantify visual perception in conjunction with the acquisition of Hbt (total hemoglobin), Hb (hemoglobin), and HbO2 (oxygenated hemoglobin) data obtained from HfNIRS (high-density functional near-infrared spectroscopy). Volunteers completed the visual task separately in response to different visible changes in the simulated scene. HfNIRS recorded the changes in Hbt, Hb, and HbO2 during the study, the time point of the visual difference, and the time point of the task change. This study consisted of one simulated scene, two visual variations, and four visual tasks. The simulation scene featured a car driving location. The visible change suggested that the brightness and saturation of the car operator interface would change. The visual task represented the completion of the layout, color, design, and information questions answered in response to the visible change. This study collected data from 29 volunteers. The volunteers completed the visual task separately in response to different visual changes in the same simulated scene. HfNIRS recorded the changes in Hbt, Hb, and HbO2 during the study, the time point of the visible difference, and the time point of the task change. The data analysis methods in this study comprised a combination of channel dimensionality reduction, feature extraction, task classification, and score correlation. Channel downscaling: This study used the data of 15 channels in HfNIRS to calculate the mutual information between different channels to set a threshold, and to retain the data of the channels that were higher than those of the mutual information. Feature extraction: The statistics derived from the visual task, including time, mean, median, variance, extreme variance, kurtosis, bias, information entropy, and approximate entropy were computed. Task classification: This study used the KNN (K-Nearest Neighbors) algorithm to classify different visual tasks and to calculate the accuracy, precision, recall, and F1 scores. Scoring correlation: This study matched the visual task scores with the fluctuations of Hbt, Hb, and HbO2 and observed the changes in Hbt, Hb, and HbO2 under different scoring levels. Mutual information was used to downscale the channels, and seven channels were retained for analysis under each visual task. The average accuracy was 96.3% \u00b1 1.99%; the samples that correctly classified the visual task accounted for 96.3% of the total; and the classification accuracy was high. By analyzing the correlation between the scores on different visual tasks and the fluctuations of Hbt, Hb, and HbO2, it was found that the higher the score, the more obvious, significant, and higher the fluctuations of Hbt, Hb, and HbO2. Experiments found that changes in visual perception triggered changes in Hbt, Hb, and HbO2. HfNIRS combined with Hbt, Hb, and HbO2 recorded by machine learning algorithms can effectively quantify visual perception. However, the related research in this paper still needs to be further refined, and the mathematical relationship between HfNIRS and visual perception needs to be further explored to realize the quantitative study of subjective and objective visual perception supported by the mathematical relationship.<\/jats:p>","DOI":"10.3390\/s23218696","type":"journal-article","created":{"date-parts":[[2023,10,25]],"date-time":"2023-10-25T06:19:58Z","timestamp":1698214798000},"page":"8696","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["High-Density Functional Near-Infrared Spectroscopy and Machine Learning for Visual Perception Quantification"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1142-1455","authenticated-orcid":false,"given":"Hongwei","family":"Xiao","sequence":"first","affiliation":[{"name":"School of Automotive Engineering, Jilin University, Changchun 130022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Public Health, Jilin University, Changchun 130021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuting","family":"Zhou","sequence":"additional","affiliation":[{"name":"China Academy of Engineering Physics, Mianyang 621900, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenhai","family":"Gao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/0304-3940(93)90181-J","article-title":"Near infrared spectroscopy (NIRS): A new tool to study hemodynamic changes during activation of brain function in human adults","volume":"154","author":"Villringer","year":"1993","journal-title":"Neurosci. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2915","DOI":"10.1364\/AO.42.002915","article-title":"Near-infrared light propagation in an adult head model. II. Effect of superficial tissue thickness on the sensitivity of the near-infrared spectroscopy signal","volume":"42","author":"Okada","year":"2003","journal-title":"Appl. Opt."},{"key":"ref_3","unstructured":"Maniscalco, B.S. (2014). High-Level Cognitive and Neural Contributions to Conscious Experience and Metacognition in Visual Perception. [Ph.D. Thesis, Columbia University]."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1192\/S0368315X00229290","article-title":"The Study of the Human Mind from a Physiological ViewThe Study of the Human Mind from a Physiological View","volume":"20","author":"Wilks","year":"2018","journal-title":"J. Ment. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1068\/p3601rvw","article-title":"Review: Basic Vision: An Introduction to Visual Perception","volume":"36","author":"Meese","year":"2007","journal-title":"Perception"},{"key":"ref_6","first-page":"785","article-title":"Semantic and action influences on visual perception: The role of action affordances and object functionality in visual selection, memory encoding and post-perceptual processes","volume":"14","author":"Tsagkaridis","year":"2011","journal-title":"J. Health Commun."},{"key":"ref_7","unstructured":"Ye, P. (2016). Research on Style Visualisation Based on Visual Perception. [Ph.D. Thesis, Suzhou Universisty]."},{"key":"ref_8","first-page":"111","article-title":"Simulation of Dynamic Process of scene Light and Dark Adaptation Based on Human Visual Perception","volume":"21","author":"Wang","year":"2010","journal-title":"J. Softw."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1016\/j.ecoleng.2014.07.071","article-title":"Changes in the visual preference after stream remediation using an image power spectrum: Stone revetment construction in the Nan-Shi-Ken stream, Taiwan","volume":"71","author":"Ho","year":"2014","journal-title":"Ecol. Eng."},{"key":"ref_10","first-page":"423","article-title":"The Appearance Intrusions Questionnaire: A Self-Report Questionnaire to Assess the Universality and Intrusiveness of Preoccupations About Appearance Defects","volume":"35","author":"Belloch","year":"2017","journal-title":"Eur. J. Psychol. Assess."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"e341","DOI":"10.1016\/j.jfo.2020.09.001","article-title":"Psychometric validation of an Assessment Questionnaire on the Perception of and Adaptation to Visual Handicap in Adults (QUEPAHVA)","volume":"43","author":"Bernard","year":"2020","journal-title":"J. Fran\u00e7ais D\u2019ophtalmol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"102781","DOI":"10.1016\/j.apgeog.2022.102781","article-title":"Visual attention and ethnic landscape perception: A case of three cities in the Guangdong\u2013Hong Kong\u2013Macao greater bay area","volume":"147","author":"Yuan","year":"2022","journal-title":"Appl. Geogr."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"108678","DOI":"10.1016\/j.buildenv.2021.108678","article-title":"Effects of lighting CCT and illuminance on visual perception and task performance in immersive virtual environments","volume":"209","author":"Ma","year":"2022","journal-title":"Build. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"e10118","DOI":"10.1016\/j.heliyon.2022.e10118","article-title":"Three-dimensional characterization and calculation of highway space visual perception","volume":"8","author":"Jia","year":"2022","journal-title":"Heliyon"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"108772","DOI":"10.1016\/j.ecolind.2022.108772","article-title":"Indicator selection combining audio and visual perception of urban green spaces","volume":"137","author":"Xiang","year":"2022","journal-title":"Ecol. Indic."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"107066","DOI":"10.1016\/j.aap.2023.107066","article-title":"An interpretable prediction model of illegal running into the opposite lane on curve sections of two-lane rural roads from drivers\u2019 visual perceptions","volume":"186","author":"He","year":"2023","journal-title":"Accid. Anal. Prev."},{"key":"ref_17","first-page":"190","article-title":"A study of urban spatial visual quality by integrating subjective evaluation and eye movement analysis","volume":"S2","author":"Li","year":"2020","journal-title":"J. Archit."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"113784","DOI":"10.1016\/j.bbr.2022.113784","article-title":"Functional integration of mirror neuron system and sensorimotor cortex under virtual self-actions visual perception","volume":"423","author":"Fan","year":"2022","journal-title":"Behav. Brain Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"100982","DOI":"10.1016\/j.aohep.2023.100982","article-title":"P-91 Changes in Early Visual Perception in Patients with Minimal Hepatic Encephalopathy","volume":"28","author":"Orozco","year":"2023","journal-title":"Ann. Hepatol."},{"key":"ref_20","unstructured":"Bitian, W. (2017). Research on the Brain Function Evaluation Technology of Drivers Based on Virtual Reality and Near-Infrared Cerebral Oxygen Signal. [Master\u2019s Thesis, Shandong University]."},{"key":"ref_21","first-page":"800","article-title":"Functional brain imaging of hemiplegic gait after stroke based on near-infrared spectroscopy","volume":"21","author":"Chen","year":"2023","journal-title":"J. Integr. Tradit. Chin. West. Med. Cardiocerebral Vasc. Dis."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhou, X., Burg, E., Kan, A., and Litovsky, R.Y. (2022). Investigating effortful speech perception using fNIRS and pupillometry measures. Curr. Res. Neurobiol., 3.","DOI":"10.1016\/j.crneur.2022.100052"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"137072","DOI":"10.1016\/j.neulet.2023.137072","article-title":"Brain activation and individual differences of emotional perception and imagery in healthy adults: A functional near-infrared spectroscopy (fNIRS) study","volume":"797","author":"Zhou","year":"2023","journal-title":"Neurosci. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"108266","DOI":"10.1016\/j.triboint.2023.108266","article-title":"Tactile perception of fractal surfaces: An EEG-fNIRS study","volume":"180","author":"Chen","year":"2023","journal-title":"Tribol. Int."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1038\/s41398-022-01820-5","article-title":"The amplitude of fNIRS hemodynamic response in the visual cortex unmasks autistic traits in typically developing children","volume":"12","author":"Mazziotti","year":"2022","journal-title":"Transl. Psychiatry"},{"key":"ref_26","unstructured":"Zhou, H., Yang, T., Wang, W., Li, L., Li, Y., and Shen, Q. (2022). A DRDoS Attack Detection Method Based on Machine Learning and Feature Selection. (CN113206860B)."},{"key":"ref_27","unstructured":"Cao, Q., Zuo, M., Jiang, T., Ma, C., and Wang, M. (2021). A User Attribute Feature Selection Method Based on Mutual Information and Improved Genetic Algorithm. (CN112906890A)."},{"key":"ref_28","unstructured":"Wang, L. (2019). Research and Implementation of Streaming Data Clustering Algorithm Based on Storm. [Master\u2019s Thesis, Qilu University of Technology]."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Xun, S., Li, D., Zhu, H., Chen, M., Wang, J., Li, J., Chen, M., Wu, B., Zhang, H., and Chai, X. (2022). Generative adversarial networks in medical image segmentation: A review. Comput. Biol. Med., 140.","DOI":"10.1016\/j.compbiomed.2021.105063"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/21\/8696\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:11:18Z","timestamp":1760130678000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/21\/8696"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,25]]},"references-count":29,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2023,11]]}},"alternative-id":["s23218696"],"URL":"https:\/\/doi.org\/10.3390\/s23218696","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2023,10,25]]}}}