Pub Date : 2025-04-01Epub Date: 2025-04-21DOI: 10.1016/j.bbe.2025.03.004
Ruben Valenzuela , Javier Corral , Mikel Diez , Thomas Provot , Francisco J. Campa , Saioa Herrero , Erik Macho , Charles Pinto
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.
{"title":"Validation of a markerless motion capture system for centre of mass kinematic analysis","authors":"Ruben Valenzuela , Javier Corral , Mikel Diez , Thomas Provot , Francisco J. Campa , Saioa Herrero , Erik Macho , 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}
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.
{"title":"A glimpse ahead: Forecasting 5.5-s human vigilance for enhanced safety in Industry 5.0","authors":"Ettore Cinquetti , Ilaria Siviero , Fabio Babiloni , Gloria Menegaz , 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, R<sup>2</sup> = 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}
Pub Date : 2025-04-01Epub Date: 2025-02-28DOI: 10.1016/j.bbe.2025.02.005
Shanshan Wang , Xiaoni Wang , Yuxin Zhao, Lin Xie, Jianbao Zhang
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.
{"title":"A feedback loop study of brain-heart interaction based on HEP and HRV","authors":"Shanshan Wang , Xiaoni Wang , Yuxin Zhao, Lin Xie, 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":"2025-04-01","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}
Pub Date : 2025-04-01Epub Date: 2025-02-24DOI: 10.1016/j.bbe.2025.02.001
Md Mohiuddin Soliman , Mohammad Tariqul Islam , Phumin Kirawanich , Muhammad E.H. Chowdhury , Touhidul Alam , Ayed M. Alrashdi , Norbahiah Misran , Mohamed S. Soliman
This research analyses contact pressure, sliding distance, and wear rate at the trunnion interface of hip implants during various activities to understand post-hip replacement outcomes. The study uses a numerical model and ISO-7206–6:2013 constraints with an AML hip implant. Greater Fx, Fy, and Fz forces broaden contact pressure distribution. The highest pressure occurs on the proximal superolateral surface, with the lowest on the anterior and posterior surfaces. The HIGH100 (individuals weighing above 100 kg) weight category demonstrates 2 times higher maximum and average contact pressure compared to AVG75 (individuals weighing 75 kg) for sit-down and knee bend activities. Force components and the duration of a full gait cycle influence sliding distance. Stance activities show the highest sliding distance due to rapid changes in force load during the gait cycle. For sit-down and knee bend activities, the total sliding distance is 2.5 times higher in the HIGH100 weight category compared to AVG75. Sliding distance primarily occurs at the proximal superolateral-inferomedial-anterior-posterior contact surface, decreasing distally. Based on contact pressure, sliding distance, and wear volume rate, jogging and stance activities pose the highest risk for hip replacement patients, while cycling is the safest. The HIGH100 weight group exhibits 5- and 4-times greater wear volume rates than AVG75 in sit-down and knee bend activities, respectively. The research findings align with wear degradation observed in retrieved hip implants, validating the study. These insights can assist patients in making informed decisions about performing activities after surgery while enabling physicians to provide accurate guidelines.
{"title":"Contact Pressure, sliding distance and wear rate analysis at trunnion of hip implant for daily Activities: A finite element approach","authors":"Md Mohiuddin Soliman , Mohammad Tariqul Islam , Phumin Kirawanich , Muhammad E.H. Chowdhury , Touhidul Alam , Ayed M. Alrashdi , Norbahiah Misran , Mohamed S. Soliman","doi":"10.1016/j.bbe.2025.02.001","DOIUrl":"10.1016/j.bbe.2025.02.001","url":null,"abstract":"<div><div>This research analyses contact pressure, sliding distance, and wear rate at the trunnion interface of hip implants during various activities to understand post-hip replacement outcomes. The study uses a numerical model and ISO-7206–6:2013 constraints with an AML hip implant. Greater F<sub>x</sub>, F<sub>y</sub>, and F<sub>z</sub> forces broaden contact pressure distribution. The highest pressure occurs on the proximal superolateral surface, with the lowest on the anterior and posterior surfaces. The HIGH100 (individuals weighing above 100 kg) weight category demonstrates 2 times higher maximum and average contact pressure compared to AVG75 (individuals weighing 75 kg) for sit-down and knee bend activities. Force components and the duration of a full gait cycle influence sliding distance. Stance activities show the highest sliding distance due to rapid changes in force load during the gait cycle. For sit-down and knee bend activities, the total sliding distance is 2.5 times higher in the HIGH100 weight category compared to AVG75. Sliding distance primarily occurs at the proximal superolateral-inferomedial-anterior-posterior contact surface, decreasing distally. Based on contact pressure, sliding distance, and wear volume rate, jogging and stance activities pose the highest risk for hip replacement patients, while cycling is the safest. The HIGH100 weight group exhibits 5- and 4-times greater wear volume rates than AVG75 in sit-down and knee bend activities, respectively. The research findings align with wear degradation observed in retrieved hip implants, validating the study. These insights can assist patients in making informed decisions about performing activities after surgery while enabling physicians to provide accurate guidelines.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 137-153"},"PeriodicalIF":5.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479429","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}
Pub Date : 2025-04-01Epub Date: 2025-04-21DOI: 10.1016/j.bbe.2025.04.003
Niloofar Fathalizade , Peyvand Ghaderyan
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.
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.
由于亨廷顿舞蹈症（Huntington's disease，HD）的临床首发症状不具有特异性，因此开发可靠且经济高效的亨廷顿舞蹈症（HD）检测系统是一项极具挑战性的任务。为了应对这一挑战，本研究首次通过标准分解技术和动态映射神经网络，在功能性近红外光谱（fNIRS）分析的基础上，全面集中地提出了一种自动化的亨廷顿舞蹈症检测系统。fNIRS是一种极具成本效益且更加精细的神经成像模式，可无创地测量血流动力学反应和神经血管耦合机制。考虑到血红蛋白浓度变化的非稳态性，所提出的系统开发了一种新的基于 fNIRS 的 HD 生物标记，即时变奇异值，以描述氧合血红蛋白和脱氧血红蛋白信号的时空特征。利用支持向量机、递归神经网络和级联前向神经网络进行了分类，以区分健康对照组（HC）和无症状（Pre-HD）或有症状（SHD）的 HD 受试者。此外，在一项比较研究中，还分别测试了轨迹矩阵大小、HD 临床类别、发色团类型和脑区对检测性能的影响。为了评估所提出的系统，我们使用了 fNIRS 数据集，其中包括 12 个 Pre-HD、15 个 SHD、29 个 Pre-HD 的 HC 和 33 个 SHD 的 HC。该方法的准确率非常高，Pre-HD 与 HC 相比达到了 95.61%，SHD 与 HC 相比达到了 95.63%。对比分析结果表明，该系统性能卓越，对影响因素具有很高的鲁棒性，在计算成本和检测性能之间实现了更好的权衡。
{"title":"An intelligent hemodynamic response analysis method to achieve prognosis and diagnosis of Huntington’s disease","authors":"Niloofar Fathalizade , 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}
Mental arithmetic can be helpful for the evaluation of neurodevelopmental disorders arising from atypical development of the brain. We propose a novel explainable machine learning method for classifying mental arithmetic calculation tasks from resting brain states and good from bad calculations using Electroencephalography. Empirical mode decomposition features are extracted from intrinsic mode functions of the average signals of all trials. Most relevant features to the mental arithmetic tasks are ranked by a random forest-based recursive feature elimination method. These features identify the changes in frequency bands of the brain rhythms, such as delta, theta, and alpha, during mental tasks for the first time in literature. These unique explainable features are also used to identify brain areas such as frontal, temporal, and occipital lobes involved in mental arithmetic tasks. Moreover, our approach describes the memory regions and that bad calculations excite the brain areas, mostly related to emotions such as frustration and anxiety due to stressful mental arithmetic. Using a random forest classifier, beating the state-of-the-art, this method achieved classification accuracies of 99.30 % and 98.33 % for resting vs calculation and good vs bad calculation brain tasks, respectively. Also, our method outperformed the state of art in handling the inter-subject variability and achieved 98.17 ± 0.47 % and 97.19 ± 0.95 % classification accuracies for resting vs calculation and good vs bad calculation tasks, respectively.
{"title":"Electroencephalograph (EEG) based classification of mental arithmetic using explainable machine learning","authors":"Murtaza Aslam , Fozia Rajbdad , Shoaib Azmat , Kausar Perveen , Morteza Naraghi-Pour , Jian Xu","doi":"10.1016/j.bbe.2025.02.002","DOIUrl":"10.1016/j.bbe.2025.02.002","url":null,"abstract":"<div><div>Mental arithmetic can be helpful for the evaluation of neurodevelopmental disorders arising from atypical development of the brain. We propose a novel explainable machine learning method for classifying mental arithmetic calculation tasks from resting brain states and good from bad calculations using Electroencephalography. Empirical mode decomposition features are extracted from intrinsic mode functions of the average signals of all trials. Most relevant features to the mental arithmetic tasks are ranked by a random forest-based recursive feature elimination method. These features identify the changes in frequency bands of the brain rhythms, such as delta, theta, and alpha, during mental tasks for the first time in literature. These unique explainable features are also used to identify brain areas such as frontal, temporal, and occipital lobes involved in mental arithmetic tasks. Moreover, our approach describes the memory regions and that bad calculations excite the brain areas, mostly related to emotions such as frustration and anxiety due to stressful mental arithmetic. Using a random forest classifier, beating the state-of-the-art, this method achieved classification accuracies of 99.30 % and 98.33 % for resting vs calculation and good vs bad calculation brain tasks, respectively. Also, our method outperformed the state of art in handling the inter-subject variability and achieved 98.17 ± 0.47 % and 97.19 ± 0.95 % classification accuracies for resting vs calculation and good vs bad calculation tasks, respectively.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 2","pages":"Pages 154-169"},"PeriodicalIF":5.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488564","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}
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.
{"title":"Tailored 3D microphantoms: An essential tool for quantitative phase tomography analysis of organoids","authors":"Michał Ziemczonok , Sylvia Desissaire , Jérémy Neri , Arkadiusz Kuś , Lionel Hervé , Cécile Fiche , Guillaume Godefroy , Marie Fackeure , Damien Sery , Wojciech Krauze , Kiran Padmanabhan , Chiara Paviolo , 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}
Pub Date : 2025-04-01Epub Date: 2025-04-03DOI: 10.1016/j.bbe.2025.03.005
Minsu Song , In-Hyeog Jee , Seungho Kim , Hansol Lee , Hyun-Joo Lee , Jun-Uk Chu
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.
{"title":"Visuo-tactile stimulated virtual mirror therapy (ViTaS-VMT) system for enhancing motor-related brain activities: Application on two amputees","authors":"Minsu Song , In-Hyeog Jee , Seungho Kim , Hansol Lee , Hyun-Joo Lee , 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}
Pub Date : 2025-01-01Epub Date: 2025-01-24DOI: 10.1016/j.bbe.2025.01.004
Alireza Karimi , Marie Darche , Ansel Stanik , Reza Razaghi , Iman Mirafzal , Kamran Hassani , Mojtaba Hassani , Elizabeth White , Ivana Gantar , Stéphane Pagès , Laura Batti , Ted S. Acott , Michel Paques
Objective
Aging results in significant structural and functional changes in the anterior segment of the eye, influencing intraocular pressure (IOP) and overall ocular health. Although aging is a well-established risk factor for primary open-angle glaucoma, a leading cause of irreversible blindness, the specific mechanisms through which aging drives morphological changes in anterior segment tissues and affects aqueous humor dynamics remain incompletely understood.
Methods
In this study, we employed cutting-edge light sheet fluorescence microscopy (LSFM) to capture high-resolution, volumetric images of cleared human donor eyes’ anterior segment tissues. This advanced imaging enabled a comprehensive morphological analysis of key parameters, including central and peripheral corneal thickness (CCT and PCT), iris thickness, anterior chamber area (ACA), and ciliary body area (CBA). By integrating these morphological parameters with computational fluid dynamics (CFD) models, we analyzed aqueous humor dynamics across n = 6 female human donor eyes, spanning a wide age range of 5 to 94 years (all of Caucasian descent).
Results
The CCT and PCT demonstrated thinning with age, accompanied by a reduction in ACA. In contrast, the CBA remained relatively stable across all age groups. Computational fluid dynamics analysis showed a decline in aqueous humor velocity and wall shear stress, with younger eyes exhibiting higher velocities and shear stress, compared to older eyes.
Conclusion
These findings emphasize the value of integrating LSFM and CFD approaches to provide a detailed understanding of how aging impacts the anterior segment and its fluid dynamics. This study contributes to the understanding of age-related ocular changes, highlighting the importance of considering these changes in the diagnosis and management of age-related eye diseases.
{"title":"Impact of aging on anterior segment morphology and aqueous humor dynamics in human Eyes: Advanced imaging and computational techniques","authors":"Alireza Karimi , Marie Darche , Ansel Stanik , Reza Razaghi , Iman Mirafzal , Kamran Hassani , Mojtaba Hassani , Elizabeth White , Ivana Gantar , Stéphane Pagès , Laura Batti , Ted S. Acott , Michel Paques","doi":"10.1016/j.bbe.2025.01.004","DOIUrl":"10.1016/j.bbe.2025.01.004","url":null,"abstract":"<div><h3>Objective</h3><div>Aging results in significant structural and functional changes in the anterior segment of the eye, influencing intraocular pressure (IOP) and overall ocular health. Although aging is a well-established risk factor for primary open-angle glaucoma, a leading cause of irreversible blindness, the specific mechanisms through which aging drives morphological changes in anterior segment tissues and affects aqueous humor dynamics remain incompletely understood.</div></div><div><h3>Methods</h3><div>In this study, we employed cutting-edge light sheet fluorescence microscopy (LSFM) to capture high-resolution, volumetric images of cleared human donor eyes’ anterior segment tissues. This advanced imaging enabled a comprehensive morphological analysis of key parameters, including central and peripheral corneal thickness (CCT and PCT), iris thickness, anterior chamber area (ACA), and ciliary body area (CBA). By integrating these morphological parameters with computational fluid dynamics (CFD) models, we analyzed aqueous humor dynamics across <em>n</em> = 6 female human donor eyes, spanning a wide age range of 5 to 94 years (all of Caucasian descent).</div></div><div><h3>Results</h3><div>The CCT and PCT demonstrated thinning with age, accompanied by a reduction in ACA. In contrast, the CBA remained relatively stable across all age groups. Computational fluid dynamics analysis showed a decline in aqueous humor velocity and wall shear stress, with younger eyes exhibiting higher velocities and shear stress, compared to older eyes.</div></div><div><h3>Conclusion</h3><div>These findings emphasize the value of integrating LSFM and CFD approaches to provide a detailed understanding of how aging impacts the anterior segment and its fluid dynamics. This study contributes to the understanding of age-related ocular changes, highlighting the importance of considering these changes in the diagnosis and management of age-related eye diseases.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 1","pages":"Pages 62-73"},"PeriodicalIF":5.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143093057","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}
Pub Date : 2025-01-01Epub Date: 2024-12-04DOI: 10.1016/j.bbe.2024.11.001
Haoneng Lin , Jing Zou , Sen Deng , Ka Po Wong , Angelica I. Aviles-Rivero , Yiting Fan , Alex Pui-Wai Lee , Xiaowei Hu , Jing Qin
The Segment Anything Model (SAM) exhibits exceptional generalization capabilities in diverse domains, owing to its interactive learning mechanism designed for precise image segmentation. However, applying SAM to out-of-distribution domains, especially in 3D medical image segmentation, poses challenges. Existing methods for adapting 2D segmentation models to 3D medical data treat 3D volumes as a mere stack of 2D slices. The essential inter-slice information, which is pivotal to faithful 3D medical image segmentation tasks, is unfortunately neglected. In this work, we present the 3D Medical SAM-Adapter (3DMedSAM), a pioneer cross-dimensional adaptation, leveraging SAM’s pre-trained knowledge while accommodating the unique characteristics of 3D medical data. Firstly, to bridge the dimensional gap from 2D to 3D, we design a novel module to replace SAM’s patch embedding, ensuring a seamless transition into 3D image processing and recognition. Besides, we incorporate a 3D Adapter while maintaining the majority of pre-training parameters frozen, enriching deep features with abundant 3D spatial information and achieving efficient fine-tuning. Given the diverse scales of anomalies present in medical images, we also devised a multi-scale 3D mask decoder to elevate the network’s proficiency in medical image segmentation. Through various experiments, we showcase the effectiveness of 3DMedSAM in achieving accurate and robust 3D segmentation on both single-target segmentation and multi-organ segmentation tasks, surpassing the limitations of current methods.
{"title":"Volumetric medical image segmentation via fully 3D adaptation of Segment Anything Model","authors":"Haoneng Lin , Jing Zou , Sen Deng , Ka Po Wong , Angelica I. Aviles-Rivero , Yiting Fan , Alex Pui-Wai Lee , Xiaowei Hu , Jing Qin","doi":"10.1016/j.bbe.2024.11.001","DOIUrl":"10.1016/j.bbe.2024.11.001","url":null,"abstract":"<div><div>The Segment Anything Model (SAM) exhibits exceptional generalization capabilities in diverse domains, owing to its interactive learning mechanism designed for precise image segmentation. However, applying SAM to out-of-distribution domains, especially in 3D medical image segmentation, poses challenges. Existing methods for adapting 2D segmentation models to 3D medical data treat 3D volumes as a mere stack of 2D slices. The essential inter-slice information, which is pivotal to faithful 3D medical image segmentation tasks, is unfortunately neglected. In this work, we present the 3D Medical SAM-Adapter (3DMedSAM), a pioneer cross-dimensional adaptation, leveraging SAM’s pre-trained knowledge while accommodating the unique characteristics of 3D medical data. Firstly, to bridge the dimensional gap from 2D to 3D, we design a novel module to replace SAM’s patch embedding, ensuring a seamless transition into 3D image processing and recognition. Besides, we incorporate a 3D Adapter while maintaining the majority of pre-training parameters frozen, enriching deep features with abundant 3D spatial information and achieving efficient fine-tuning. Given the diverse scales of anomalies present in medical images, we also devised a multi-scale 3D mask decoder to elevate the network’s proficiency in medical image segmentation. Through various experiments, we showcase the effectiveness of 3DMedSAM in achieving accurate and robust 3D segmentation on both single-target segmentation and multi-organ segmentation tasks, surpassing the limitations of current methods.</div></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"45 1","pages":"Pages 1-10"},"PeriodicalIF":5.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143093056","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}
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