Biocybernetics and Biomedical Engineering最新文献

{"title":"Classifying developmental delays with EEG: A comparative study of machine learning and deep learning approaches","authors":"Muhammad Usman ,&nbsp;Wen-Yi Lin ,&nbsp;Yi-Yin Lin ,&nbsp;Sheng-Ta Hsieh ,&nbsp;Yao-Tien Chen ,&nbsp;Yu-Chun Lo ,&nbsp;Chun-Ling Lin","doi":"10.1016/j.bbe.2025.04.001","DOIUrl":"10.1016/j.bbe.2025.04.001","url":null,"abstract":"<div><div>Early detection of developmental delays is crucial for improving children’s cognitive, social, and emotional outcomes through timely interventions. This study explores the potential of machine learning (ML) and deep learning (DL) to classify Electroencephalography (EEG) data from an oddball task, distinguishing between children with and without developmental delays. Participants underwent language assessments and EEG recordings, with subsequent analysis using Event-Related Potentials (ERPs), Event-Related Spectral Perturbations (ERSPs), and functional connectivity to characterize group differences. Three methodologies were employed in this research to classify EEG data. Firstly, statistical features are extracted from the EEG data and various ML algorithms are applied for classification, with feature selection techniques utilized to identify the most relevant features and enhance classification accuracy. Secondly, brain dynamics is utilized to incorporate ERP, ERSP, and functional connectivity measures as features for developmental delay detection. Similar to the first approach, feature selection techniques are again employed to enhance classification accuracy. Lastly, DL approaches are explored by implementing multiple convolutional neural networks (CNNs), including a 2D CNN (EEGNet), various hybrid CNN architectures integrating LSTM, GRU, and attention mechanisms, and a novel 1D CNN with a standardized convolutional layer (SCL) for improved stability and training performance. The effectiveness of each approach in accurately classifying EEG data for developmental delay detection is independently analyzed. The results demonstrate that the proposed 1D convolutional neural network outperforms both EEGNet and the employed ML classifiers. This model achieves an impressive accuracy of 96.4% and an F1 score of 96.6%, underscoring its potential as a valuable tool for early and accurate developmental delay detection using EEG data.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 229-246"},"PeriodicalIF":5.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143799347","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 sepsis diagnosis method based on Chain-of-Thought reasoning using Large Language Models","authors":"Weimin Zhang ,&nbsp;Mengfei Wu ,&nbsp;Luyao Zhou ,&nbsp;Min Shao ,&nbsp;Cui Wang ,&nbsp;Yu Wang","doi":"10.1016/j.bbe.2025.04.002","DOIUrl":"10.1016/j.bbe.2025.04.002","url":null,"abstract":"<div><div>Sepsis is a severe infectious disease with high incidence and mortality rates globally. Early diagnosis of sepsis is crucial for improving patient outcomes. Previous diagnostic methods heavily relied on subjective clinical experience, while the machine learning-based methods can only learn knowledge from a specific dataset. Recently, the rapid development of Large Language Models (LLMs) has significantly enhanced various downstream dialogue tasks by leveraging prior semantic knowledge. Therefore, it is of great interest to explore the potential of LLMs in sepsis diagnosis. This study proposed an early sepsis diagnosis method based on the Chain of Thought (CoT) reasoning using LLMs. First, the clinical data of a patients were transformed into a textual representation to form the prompt. Subsequently, a CoT was created to simulate the reasoning process of human medical experts and utilized the prior semantic knowledge in LLMs to achieve sepsis diagnosis. The proposed method was validated using real clinical data, demonstrating high classification performance with an accuracy of 0.87, recall of 0.98, and F1 score of 0.88. These metrics showed an improvement in F1 score by 7 to 8 percentage points compared to commonly used machine learning classifiers. The experimental results indicated that the proposed method can enhance the performance of early sepsis diagnosis, and the introduction of CoT enhanced the interpretability of diagnostic results, contributing to the application of LLMs in clinical diagnosis.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 269-277"},"PeriodicalIF":5.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848345","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":"Physically motivated projection of the electrocardiogram—A feasibility study","authors":"Sebastian Wildowicz ,&nbsp;Tomasz Gradowski ,&nbsp;Paulina Figura ,&nbsp;Igor Olczak ,&nbsp;Judyta Sobiech ,&nbsp;Teodor Buchner","doi":"10.1016/j.bbe.2025.03.001","DOIUrl":"10.1016/j.bbe.2025.03.001","url":null,"abstract":"<div><div>We present PhysECG: a physically motivated projection of the 12 lead electrocardiogram, supported by a deep learning model trained on 21,799 recordings from the PTB-XL database and discuss its feasibility. The method allows to evaluate the epicardial activity (inverse problem of ECG imaging) and, in particular, to distinguish left and right ventricular activity, with statistical spread related to localization of the septum. The observed dyssynchrony resembles other experimental results. The foundations of the method are based on the molecular theory of biopotentials. The heart’s activity in view of the method is decomposed into two processes: the passage of the electric activation wavefront and the response of cardiomyocytes. We introduce the idea of the electrode-resolved activity function, which represents the mass of the ventricle in Phase 0 of action potential within the lead field of each electrode. The computations are fast and robust, with excellent convergence. We present the quality metrics for the reconstruction based on the model on the testing set selected from the PTB database. In order to prove feasibility, we present and discuss two healthy controls: male and female, and two pathologies: right bundle branch block, and anterior myocardial infarction. The results obtained using PhysECG seem to be in accordance with the changes evoked by pathology, which has to be confirmed by subsequent clinical studies. The method is based on ECG, and does not require reconstruction of body geometry, which presents an affordable solution for low and middle-income countries where access to imaging is limited.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 199-211"},"PeriodicalIF":5.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739246","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":"Validation of a markerless motion capture system for centre of mass kinematic analysis","authors":"Ruben Valenzuela ,&nbsp;Javier Corral ,&nbsp;Mikel Diez ,&nbsp;Thomas Provot ,&nbsp;Francisco J. Campa ,&nbsp;Saioa Herrero ,&nbsp;Erik Macho ,&nbsp;Charles Pinto","doi":"10.1016/j.bbe.2025.03.004","DOIUrl":"10.1016/j.bbe.2025.03.004","url":null,"abstract":"<div><div>In recent years, markerless optical systems for biomechanical movement analysis in sports, gait and balance assessments are being used as an alternative to conventional marker based measuring systems. This study compares the performance of the Zed 2i stereoscopic camera against a VICON system in a standing position under three conditions: quiet standing and two movements simulating disturbances in two directions, anteroposterior and mediolateral. This study originates from a collaborative project with a medical team that aims to objectively evaluate balance function in patients recovering from stroke. The displacement and velocities of the centre of mass were calculated and compared in two directions, x and y. A Bland–Altman analysis for non-parametric data, along with the coefficient of determination and mean square error, were used for statistical evaluation. The results demonstrate that the limits of agreement in both sway tasks were greater than those observed in static conditions. However, the coefficient of determination of the sway tasks indicates a significant degree of agreement between the two systems. In contrast, in the static condition, it appears that noise may have a greater influence on the signal than the centre of mass estimate, due to the limitation of the depth algorithm used to estimate the joint positions.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 278-286"},"PeriodicalIF":5.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143851331","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 glimpse ahead: Forecasting 5.5-s human vigilance for enhanced safety in Industry 5.0","authors":"Ettore Cinquetti ,&nbsp;Ilaria Siviero ,&nbsp;Fabio Babiloni ,&nbsp;Gloria Menegaz ,&nbsp;Silvia F. Storti","doi":"10.1016/j.bbe.2025.03.002","DOIUrl":"10.1016/j.bbe.2025.03.002","url":null,"abstract":"<div><div>In the context of Industry 5.0 and human-robot interaction, ensuring the safety of operators by avoiding human errors is crucial. Monitoring vigilance decrement is an essential aspect of this effort, aimed at mitigating safety risks and enhancing productivity. A potentially promising solution to this challenge is using a passive brain-computer interface (BCI) based on electroencephalography (EEG) recordings. However, its application in industrial settings has yet to be explored in-depth. This study uses EEG data to introduce a novel experimental protocol and analysis pipeline to predict vigilance degradation in an industrial research laboratory. The dataset was gathered from ten healthy volunteers who observed a robotic arm for 23 min. The EEG power spectrum over time was computed using the continuous wavelet transform (CWT). After confirming growth in power for the α band using a linear regression model, we forecast its trend using four models. As a conventional approach, we used the vector autoregressive (VAR) model, serving as a reference for comparison with three deep learning architectures: a temporal convolutional network (TCN), a gated recurrent unit (GRU) and an encoder-decoder (ED)-GRU. The proposed ED-GRU model outperformed the others showing accurate forecasts (mean absolute error = 0.048, R² = 0.726) up to 5.5 s. The findings suggest that monitoring vigilance degradation in Industry 5.0 is a feasible strategy to prevent human accidents and reduced performance during repetitive tasks.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 258-268"},"PeriodicalIF":5.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143843739","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":"An intelligent hemodynamic response analysis method to achieve prognosis and diagnosis of Huntington’s disease","authors":"Niloofar Fathalizade ,&nbsp;Peyvand Ghaderyan","doi":"10.1016/j.bbe.2025.04.003","DOIUrl":"10.1016/j.bbe.2025.04.003","url":null,"abstract":"<div><div>The development of a reliable and cost-effective Huntington’s disease (HD) detection is a challenging task due to non-specific clinical first symptoms. To address the challenge, this is the first study to comprehensively focus on proposing an automated HD detection system based on functional near-infrared spectroscopy (fNIRS) analysis through a standard decomposition technique and dynamic mapping neural networks. fNIRS is a highly cost-effective and more refined neuroimaging modality that noninvasively measures hemodynamic responses and neurovascular coupling mechanisms. Considering the non-stationary nature of the hemoglobin concentration changes, the proposed system has developed a new fNIRS-based biomarker of HD, namely time-varying singular value, to characterize the spatiotemporal characteristics of the oxyhemoglobin and deoxyhemoglobin signals. The classification has been performed using a support vector machine, recurrent neural network, and cascade forward neural network to discriminate healthy controls (HC) from presymptomatic (Pre-HD) or symptomatic HD (SHD) subjects. Moreover, in a comparative study, the effects of trajectory matrix size, clinical categories of HD, type of chromophores, and brain regions have been tested on the detection performance, separately.</div><div>To evaluate the proposed system, the fNIRS dataset of 12 Pre-HD, 15SHD, 29 HC for Pre-HD, and 33 HC for the SHD has been used. The method has achieved remarkable accuracy rates of 95.61% for Pre-HD vs. HC and 95.63% for SHD vs. HC. The comparative analysis leads to the outstanding performance of this system and its high robustness against affecting factors, providing a better trade-off between computational costs and detection performance.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 287-295"},"PeriodicalIF":5.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854595","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":"Visuo-tactile stimulated virtual mirror therapy (ViTaS-VMT) system for enhancing motor-related brain activities: Application on two amputees","authors":"Minsu Song ,&nbsp;In-Hyeog Jee ,&nbsp;Seungho Kim ,&nbsp;Hansol Lee ,&nbsp;Hyun-Joo Lee ,&nbsp;Jun-Uk Chu","doi":"10.1016/j.bbe.2025.03.005","DOIUrl":"10.1016/j.bbe.2025.03.005","url":null,"abstract":"<div><div>To enhance the degenerated brain signal of amputees on motor area, a visuo-tactile stimulated virtual mirror therapy system was developed. The system consists of a motion-tracking glove, a vibration motor, and a monitor-integrated table. The system can provide virtual hand illusion for body agency and combine visuo-tactile stimulation to induce body ownership on the virtual hand. The virtual hand then mimics the healthy hand like mirror therapy, and subjects perform grasping with both hands while observing the mirrored virtual hand on the amputated side. The training lasted three days, including the gradual exposure to the system to measure the difference in brain activity on the first day. We measured electroencephalogram (EEG) during training, and functional magnetic resonance imaging (fMRI) of grasping was measured before and after the training. Two amputees volunteered for this preliminary study. Both participants showed changes in motor-related brain activity, with consistent increases in event-related desynchronization (ERD) amplitude, particularly in the supplementary motor area (SMA) and primary motor cortex. These findings suggest the system’s potential to enhance motor-related neural processes. We believe that the results of this preliminary study have provided evidence that the proposed system can reproduce the learning process and that brain activation can be improved by using the system. Based on the results, a future study will expand the number of subjects and the duration of training to provide a quantitative clinical evaluation of the proposed system.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 212-228"},"PeriodicalIF":5.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143767805","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":"Tailored 3D microphantoms: An essential tool for quantitative phase tomography analysis of organoids","authors":"Michał Ziemczonok ,&nbsp;Sylvia Desissaire ,&nbsp;Jérémy Neri ,&nbsp;Arkadiusz Kuś ,&nbsp;Lionel Hervé ,&nbsp;Cécile Fiche ,&nbsp;Guillaume Godefroy ,&nbsp;Marie Fackeure ,&nbsp;Damien Sery ,&nbsp;Wojciech Krauze ,&nbsp;Kiran Padmanabhan ,&nbsp;Chiara Paviolo ,&nbsp;Małgorzata Kujawińska","doi":"10.1016/j.bbe.2025.03.003","DOIUrl":"10.1016/j.bbe.2025.03.003","url":null,"abstract":"<div><div>We present a novel approach for benchmarking and validating quantitative phase tomography (QPT) systems using three-dimensional microphantoms. These microphantoms, crafted from biological and imaging data, replicate the optical and structural properties of multicellular biological samples. Their fabrication featuring refractive index modulation at sub-micrometer details is enabled by two-photon polymerization. We showcase the effectiveness of our technique via a round-robin test of healthy and tumoral liver organoid phantoms across three different QPT systems. This test reveals sample- and system-dependent errors in measuring dry mass and morphology. This approach constitutes a development of super phantoms for QPT — test objects that exist in both digital and physical form, replicate both the morphology and relevant aspects of physiology in specimens under healthy or diseased conditions, and underpin the assessment and refinement of imaging technologies and methodologies prior to clinical application.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 247-257"},"PeriodicalIF":5.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829014","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":"Observer-based linear state-dependent control for blood glucose regulation in type 1 diabetic patients with unknown delays","authors":"J. Castro-Gómez ,&nbsp;B. Targui ,&nbsp;O. Hernández-González ,&nbsp;G. Valencia-Palomo ,&nbsp;M.E. Guerrero-Sánchez","doi":"10.1016/j.bbe.2025.02.003","DOIUrl":"10.1016/j.bbe.2025.02.003","url":null,"abstract":"<div><div>This paper presents a control strategy for blood glucose regulation in the presence of a time-varying delayed input, where the delay is unknown. The proposed control scheme is based on an observer-based linear state-dependent (LSD) (a subclass of the general linear parameter varying (LPV) framework) control with <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> criterion. This proposed control regulates glucose levels in response to meal intake. A novel LSD system representation is used to relax the inherent conservativeness of the nonlinear system. First, the observer achieves an estimate of the current state vector despite the delayed input, where the time-varying unknown delay can be relatively long. Thus, the control law will perform well in the presence of a long unknown delay. The observer-based control scheme is validated by considering different meal disturbances and unknown delay scenarios.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 189-198"},"PeriodicalIF":5.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548599","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 feedback loop study of brain-heart interaction based on HEP and HRV","authors":"Shanshan Wang ,&nbsp;Xiaoni Wang ,&nbsp;Yuxin Zhao,&nbsp;Lin Xie,&nbsp;Jianbao Zhang","doi":"10.1016/j.bbe.2025.02.005","DOIUrl":"10.1016/j.bbe.2025.02.005","url":null,"abstract":"<div><div>Although growing evidences suggest heartbeat evoked potential (HEP) as a biomarker of interoception, little is known about how HEP is related to cardiovascular function. In the article, mental arithmetic and meditation tasks that respectively activate sympathetic and parasympathetic activities were designed, and electroencephalogram and cardiovascular parameters were recorded in healthy young males. Our findings revealed a decrease in HEP during mental arithmetic and an increase during meditation. A correlation between HEP and blood pressure was also observed, indicating that baroreceptor stretch may contribute to HEP generation. Furthermore, HEP showed a positive correlation with parasympathetic activity and a negative correlation with sympathetic activity. Collectively, these results suggest the presence of a potential negative feedback loop between the brain and heart, mediated by HEP.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 181-188"},"PeriodicalIF":5.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143519106","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}