Biocybernetics and Biomedical Engineering最新文献

{"title":"The effect of familiarity and repetition on neural activity during visual face perception","authors":"Fatemeh Ghorbani,&nbsp;Andry Rakotonirainy,&nbsp;Mohammed Elhenawy","doi":"10.1016/j.bbe.2025.05.005","DOIUrl":"10.1016/j.bbe.2025.05.005","url":null,"abstract":"<div><div>This study examined the temporal dynamics of face perception using event-related potentials (ERPs) to investigate how familiarity and repetition influence early and late stages of face processing. A generalised linear mixed-effects (GLME) model was employed to assess the amplitude and latency of the P100, N170, and N250 ERP components across three stimulus types (famous, non-famous, and scrambled faces), three repetition conditions (first presentation, immediate repeat, delayed repeat), and two brain hemispheres. The P100 component, associated with early visual processing, showed no significant modulation by stimulus familiarity or repetition, suggesting stable perceptual encoding across conditions. In contrast, N170 and N250 amplitudes were significantly affected by repetition, indicating enhanced neural responses during repeated exposure, particularly in the right hemisphere. Latency analyses revealed that N250 component was also sensitive to repetition timing, with delayed repetitions eliciting shorter response time, implying shifts in processing efficiency and memory engagement. Multivariate time-series decoding further demonstrated higher discriminability between scrambled and familiar faces compared to non-famous faces, particularly during first and delayed repeat conditions. Notably, decoding performance declined for immediate repeats, suggesting reduced neural differentiation during short-interval repetition. These findings provide new insights into how repetition and familiarity modulate the neural underpinnings of face perception, emphasizing the role of temporal dynamics and hemispheric specialization in face processing.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 3","pages":"Pages 399-413"},"PeriodicalIF":5.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence models for wound infection recognition and their comparison with human results","authors":"Piotr Foltynski ,&nbsp;Karolina Kruszewska ,&nbsp;Arkadiusz Krakowiecki ,&nbsp;Bozena Czarkowska-Paczek ,&nbsp;Piotr Ladyzynski","doi":"10.1016/j.bbe.2025.08.003","DOIUrl":"10.1016/j.bbe.2025.08.003","url":null,"abstract":"<div><div>Recognizing an infected wound based solely on a photograph can be a challenge and the aim of this work was to develop a machine learning model that would enable that. We selected 899 wound photographs taken at PODOS Wound Care Clinic (Warsaw, Poland). There were 445 photographs showing uninfected wounds, whereas 454 photographs showed infected wounds with positive microbiological test and antibiotic treatment. A test set was created by randomly selecting 82 photographs representing 42 uninfected and 40 infected wounds. From the remaining photographs, 154 were randomly selected for the validation set, and the remaining 663 formed the training set. Initially we used five pretrained YOLO models from generation 8 and five from generation 11. The 8th generation models performed better than 11th generation models and were then compared with the results of 6 experts and 6 nursing students. The post-hoc analysis revealed that AI models outperformed both specialists and students in terms of mean averaged precision (mAP), accuracy and F1 score, while the results of specialists and students did not differ significantly. For specialists, the medians of mAP, F1 score, and accuracy were 74.1 %, 76.4 %, and 74.4 %, respectively. For Students the medians were 68.4 %, 59.4 %, and 67.7 %, respectively; and for AI models the medians were 92.7 %, 92.9 %, and 92.7 %, respectively. The highest accuracy of 95.1 % of YOLOv8n model was significantly higher than the best specialist’s result of 84.1 %. These results suggest that artificial intelligence can significantly help caregivers recognize wound infection, so they can take appropriate action more quickly.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 3","pages":"Pages 572-579"},"PeriodicalIF":6.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144860747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rhythmic physical exercise as a protocol to study synchronization phenomenon","authors":"Judyta Sobiech,&nbsp;Teodor Buchner","doi":"10.1016/j.bbe.2025.05.007","DOIUrl":"10.1016/j.bbe.2025.05.007","url":null,"abstract":"<div><div>The phenomenon of synchronization, which appears during the coupling of two or more oscillators, is often observed in nature and many fields of science. The case of several rhythms is particularly interesting, as the synchronizations may compete. In this work, we report the occurrence of the phase coupling between three biological rhythms: heart rate, respiration and locomotor rhythm. We analyzed its appearance during cycling on a stationary bike with stepwise increasing speed. Presence of synchronization was investigated using the synchrogram in order to detect phase-locking epochs.</div><div>Study group consisted of 21 young healthy volunteers (15 women and 6 men). Specific subgroups were also defined.</div><div>During exercise synchronization between all rhythms appeared in all subjects. Cardiolocomotor synchronization occurred significantly more often, which underlines the role of cardiac entrainment to phasic baroreflex input. In cardiolocomotor synchronization we observed a direct phase coupling (1:1) lasting at least 20 s. It occurred in 76 % of subjects, which manifests a dominant role of this type of synchronization. Additionally, we observed subjects, in whom epochs of simultaneous synchronization of all rhythms appeared.</div><div>Total duration of synchronization was significantly larger in men than in women and in less experienced cyclists. No significant difference in age or BMI was observed, however the group was relatively uniform. During the post-exercise epoch, cardiorespiratory synchronization appeared in nine subjects. Due to its frequent occurence, synchronization is a good candidate for an objective estimator of physical stress, applicable in diagnostic, therapeutical and lifestyle scenarios.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 3","pages":"Pages 380-389"},"PeriodicalIF":5.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144107325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward the integration of mixed reality and brain-computer interfaces based on code-modulated visual evoked potentials","authors":"Selene Moreno-Calderón ,&nbsp;Víctor Martínez-Cagigal ,&nbsp;Ana Martín-Fernández ,&nbsp;Eduardo Santamaría-Vázquez ,&nbsp;Roberto Hornero","doi":"10.1016/j.bbe.2025.06.003","DOIUrl":"10.1016/j.bbe.2025.06.003","url":null,"abstract":"<div><div><em>Background and objective</em>: Brain-computer interface (BCI) systems can assist individuals with severe motor disabilities by enabling communication through their brain signals using spellers, which allow selecting commands from a set of options. For this technology, accuracy, speed and user comfort are essential. Code-modulated visual evoked potentials (c-VEPs) have demonstrated promising performance in BCI control. Integrating BCI systems with mixed reality (MR) could provide portability and autonomy. However, to the best of our knowledge, no existing studies have explored the feasibility of combining MR with c-VEP-based BCIs. This study aims to: (1) evaluate the performance of integrating MR with c-VEP-based BCIs and (2) study the visual fatigue induced by c-VEPs compared to traditional screen. <em>Methods</em>: Twenty participants used a 36-character speller to select words in both MR and traditional screen conditions. Metrics like accuracy and information transfer rate (ITR) were measured. Usability and eyestrain were evaluated through questionnaires. <em>Results</em>: The integration of MR with c-VEPs achieved an accuracy of 96.71 % and an ITR of 27.55 bits/min, compared to 95.98 % accuracy and 27.10 bits/min for the conventional screen condition. The questionnaires revealed minimal levels of visual fatigue in both conditions and high usability. No significant differences were observed between conditions in terms of performance or visual fatigue. <em>Conclusions</em>: The c-VEP-based speller with MR-BCI technology proved feasible, achieving performance levels similar to the conventional setup, with high accuracy in both conditions. The study also found comparable visual fatigue between MR and traditional screens, supporting the practicality of MR integration in BCI systems.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 3","pages":"Pages 528-538"},"PeriodicalIF":5.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MRS thermometry – Importance of scanner-specific calibrations for accurate brain temperature estimations","authors":"Marcin Sińczuk ,&nbsp;Jacek Rogala ,&nbsp;Piotr Bogorodzki","doi":"10.1016/j.bbe.2025.06.001","DOIUrl":"10.1016/j.bbe.2025.06.001","url":null,"abstract":"<div><div>This study explores the importance of scanner-specific calibration measurements for Magnetic Resonance Spectroscopy Thermometry (MRST) in human brain temperature estimations. Data acquisition was conducted on a 3-T GE scanner. Calibration constants for the water-chemical shift were obtained using a temperature-controlled phantom containing an aqueous solution of N-acetyl aspartate (NAA), Creatine (Cr), and Choline (Cho), and data from three different research groups using the same metabolites. Temperatures were estimated utilizing correlation of water chemical shift with NAA, Cr and Cho. For data acquisition, commercially available single-voxel point-resolved spectroscopy (PRESS) sequences were used for calibrations and in vivo temperature estimations. Each sequence included spectras without (WU) and with (WS) water suppression. In vivo study consisted of two PRESS sequences, one before and one after extensive 30-minute fMRI task acquisition. Significant differences were found between absolute brain temperatures measured using scanner-specific calibrations and those from other researchers, varying from −0.68 °C to + 0.37 °C for NAA, −0.92 °C to 0.37 °C for Cr, and −0.78 °C to 0.7 °C for Cho. Each method reported a similar temperature decrease of −0.26 ∓ 0.03 °C between before and after fMRI measurements. These findings suggest that while absolute temperatures from non-scanner specific calibrations may be inaccurate, comparative estimates are valid.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 3","pages":"Pages 451-456"},"PeriodicalIF":5.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144489482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A potential approach to detecting of gastrointestinal slow waves based on optically pumped magnetometers array","authors":"Yixiang Zhang ,&nbsp;Xinlei He ,&nbsp;Haoyue Li ,&nbsp;Linke Zhang ,&nbsp;Bing Yan ,&nbsp;Yuming Peng ,&nbsp;Qinggang Ge ,&nbsp;Ming Ding ,&nbsp;Yuxin Leng","doi":"10.1016/j.bbe.2025.08.001","DOIUrl":"10.1016/j.bbe.2025.08.001","url":null,"abstract":"<div><div>Gastrointestinal slow wave (SW) can be used to evaluate human gastrointestinal function. Compared with electrogastrogram and electroenterogram, SW magnetic signals measurement can obtain higher-quality results. Optically pumped magnetometers (OPMs) based on the spin exchange relaxation-free method have comparable weak magnetic detection capabilities to superconducting quantum interference devices, and does not require liquid helium. Therefore, this study developed a gastrointestinal SW signals measurement system using OPM sensors. Our system measured rat intestinal SW signals with a frequency of approximately 34.24 cpm, and simultaneously extracted human gastric SW signals of approximately 3 cpm and intestinal SW signals of 8–12 cpm for the first time. It was also observed that the postprandial gastrointestinal SW signals were significantly enhanced compared with the fasting state. The results exhibited consistent power and time–frequency characteristics with previous reports. In summary, the gastrointestinal SW signals measurement system based on OPM provides a new technical approach for detecting gastrointestinal SWs and diagnosing related diseases.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 3","pages":"Pages 549-559"},"PeriodicalIF":6.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cytoplasm and nuclei as a basis for Bethesda cell cluster classification in cervical smears","authors":"Antonina Pater ,&nbsp;Lukasz Roszkowiak ,&nbsp;Krzysztof Siemion ,&nbsp;Jakub Zak ,&nbsp;Karol Deptuch ,&nbsp;Anna Korzynska","doi":"10.1016/j.bbe.2025.04.004","DOIUrl":"10.1016/j.bbe.2025.04.004","url":null,"abstract":"<div><div>Population screening in the form of cervical smears was introduced to reduce cervical cancer morbidity. However, the manual evaluation of cervical smears is a labour-intensive and meticulous task. This challenge has led to the development of various computer-aided cell identification methods aimed at improving the quality of evaluations and reducing the time required for slide analysis. These supportive tools for pathologists should adhere to the Bethesda classification system for cell types, facilitating integration with established clinical practices. Despite advances, the automatic classification of clustered cells in cervical smears remains a significant challenge for both automated and semiautomated methods that utilize classical image processing and deep learning techniques.</div><div>This study introduces a novel method for fragmenting clusters to improve the classification of clustered cells in digital images of Papanicolaou smears. The proposed method integrates explainable AI and marker-guided watershed segmentation ensuring both interpretability and versatility of an overall pipeline for diagnostician support in smear evaluation. Validation of the method was performed on a recently developed Papanicolaou cytology Bialystok dataset, as well as the publicly available CRIC dataset, demonstrating the method’s generalizability across different datasets.</div><div>The cell classification pipeline, enhanced by the proposed declustering method, improved the overall harmonic mean of recall and precision (F1 score) by 13.27 percentage points compared with the results obtained without this additional processing. The improvement in classifying the most critical cell type according to the Bethesda system (HSIL cell class) was even more significant, with an increase of 35.72 percentage points compared with classifying the entire cluster.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 3","pages":"Pages 414-425"},"PeriodicalIF":5.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144166979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative and interpretable framework to unveil the neurophysiological fingerprint of Alzheimer’s disease and mild cognitive impairment: A machine learning-SHAP approach","authors":"Víctor Gutiérrez-de Pablo ,&nbsp;María Herrero-Tudela ,&nbsp;Marina Sandonís-Fernández ,&nbsp;Jesús Poza ,&nbsp;Aarón Maturana-Candelas ,&nbsp;Víctor Rodríguez-González ,&nbsp;Miguel Ángel Tola-Arribas ,&nbsp;Mónica Cano ,&nbsp;Hideyuki Hoshi ,&nbsp;Yoshihito Shigihara ,&nbsp;Roberto Hornero ,&nbsp;Carlos Gómez","doi":"10.1016/j.bbe.2025.05.011","DOIUrl":"10.1016/j.bbe.2025.05.011","url":null,"abstract":"<div><div>Dementia and mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) are neurological pathologies associated with disruptions in brain electromagnetic activity, typically studied using magnetoencephalography (MEG) and electroencephalography (EEG). To quantify diverse brain properties, different families of parameters can be computed from MEG and EEG (i.e., spectral, non-linear, morphological, functional connectivity, or network structure and organisation). However, studying these characteristics separately overlooks the complex nature of brain activity. Integrative frameworks can be useful to unveil the intricate neurophysiological fingerprint, as well as to characterise pathological conditions comprehensively. To that purpose, data fusion methodologies are crucial, despite their interpretational challenges. In this study, Machine Learning (ML) models were trained to discriminate between groups of severity, whereas the SHapley Additive eXplanations (SHAP) algorithm was afterwards utilised to assess the relevance of the input characteristics into the output classification. Three databases were analysed: MEG (55 healthy controls, HC, 42 MCI patients, and 86 AD patients), EEG1 (51 HC, 52 MCI, and 100 AD), and EEG2 (45 HC, 69 MCI, and 82 AD). The best results for the three-class classification problem were obtained by Gradient Boosting for the MEG database: 3-class Cohen’s kappa coefficient of 0.5452 and accuracy of 72.63 %. Afterwards, using SHAP on Gradient Boosting, it has been shown that spectral features were identified as highly relevant across all databases. Furthermore, morphology measures presented high relevance for the MEG database, whereas EEG1 and EEG2 databases showed functional connectivity and multiplex organisation measures, respectively, as relevant subgroups of parameters. Finally, commonly relevant features across databases were selected using SHAP to generate the neurophysiological fingerprints of AD and MCI. This study highlights the relevance of different MEG and EEG parameters in characterising neurological pathologies. The proposed framework, based on MEG and EEG, can be used to generate interpretable, robust, and accurate neurophysiological fingerprints of AD and MCI.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 3","pages":"Pages 438-450"},"PeriodicalIF":5.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relevance of harmonic content findings of hand motor (dys)functionalities in Parkinson’s disease revealed by means of a sensory glove","authors":"Luca Pietrosanti ,&nbsp;Martina Patera ,&nbsp;Antonio Suppa ,&nbsp;Giovanni Costantini ,&nbsp;Nicola Arangino ,&nbsp;Franco Giannini ,&nbsp;Giovanni Saggio","doi":"10.1016/j.bbe.2025.07.004","DOIUrl":"10.1016/j.bbe.2025.07.004","url":null,"abstract":"<div><div>Hand functions are vital for performing daily activities, ensuring independence, and maintaining quality of life. In Parkinson’s disease (PD), impaired hand function affects fine motor skills, dexterity, and coordination, leading to difficulties in self-care, communication, and work-related tasks. As such, correct hand function assessment in PD is among the crucial aspects in evaluating motor impairment, in guiding treatment and tracking disease progression. Here, we report objective results obtained in assessing hand (dys)functionalities using an on-the-shelves fingerless sensory glove, named MANUS Quantum Metaglove, capable of sensing the variations of an electromagnetic field (EMF) sourced on the dorsal part of the hand and revealed by EMF coils at the fingers tips. A total of 65 people (35 PD patients and 30 healthy subjects for reference) were asked to perform standard motor tasks, and both most affected and least affected hands were assessed for opening-closing, grasping and pronation-supination movements. Differing from the generally adopted spatiotemporal analysis, taking a cue from non-linear theory adopted in electronics, we focused on spectral characteristics of the measured signals, specifically examining harmonic content and related harmonic distortions. As a result, we report how the adopted sensory glove, ensemble with spectral analysis, can be able to consistently assess hand motor (in)abilities in PD subjects and healthy subjects. In fact according to our results, PD patients significatively performed with hand motion signals affected by harmonic distortions, which revealed that the greater the complexity of the motor task, the greater the spread of the signal across harmonic frequencies, whilst healthy subjects perform with signals mostly around the fundamental frequency, as a marker of movement smoothness.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 3","pages":"Pages 507-514"},"PeriodicalIF":5.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144694330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving the quality of respiratory signals extracted from the segmented mask area","authors":"Natalia Kowalczyk,&nbsp;Jacek Rumiński,&nbsp;Magdalena Mazur-Milecka","doi":"10.1016/j.bbe.2025.06.002","DOIUrl":"10.1016/j.bbe.2025.06.002","url":null,"abstract":"<div><div>The COVID-19 pandemic has underscored the importance of wearing facial masks and monitoring respiratory health to prevent the spread of the virus. In this study, we developed a model for segmenting facial masks in thermal images. We applied the model to segment face masks in different conditions, including a person walking toward the observing camera. The segmented regions were further processed using different erosion masks to analyze the influence of the selected sources on the quality of the estimated respiratory signals. The Signal-to-Noise Ratio (SNR) was used as a quality measure. Additionally, the extracted respiratory signals were compared with two reference signals: binary signals generated by participants who signaled the inhalation phase and pressure signals measured with a respiratory belt. Our findings show a high level of concordance between the respiratory signals derived from the segmented mask region and those from the respiratory belt, validating the effectiveness of thermal imaging for capturing respiratory patterns. Notably, the signal-to-noise ratio (SNR) was higher for the segmented mask than the detection methods used in previous works. Specifically, for the mask segmentation task, the mean SNR improved by 4.3 compared to facial mask detection. The segmentation model achieved a mean Average Precision (mAP) of 0.992 for segmentation tasks and 0.857 mAP at the 50–95 % threshold using the Yolov8 “nano” architecture. This study underscores the potential of thermal imaging for non-invasive respiratory monitoring and highlights the explainability and accuracy of selecting the facial mask region for signal extraction.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 3","pages":"Pages 457-468"},"PeriodicalIF":5.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144489483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}