Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference最新文献_第4页

A Novel Machine-Learning-Based Noise Detection Method for Photoplethysmography Signals. 一种新的基于机器学习的光容积脉搏波信号噪声检测方法。

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Pub Date : 2024-07-01 DOI: 10.1109/EMBC53108.2024.10782126

Soheil Khooyooz, Anice Jahanjoo, Amin Aminifar, Nima TaheriNejad

引用次数: 0

A federated stroke segmentation to impact limited data institutions. 影响有限数据机构的联合卒中分割。

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Pub Date : 2024-07-01 DOI: 10.1109/EMBC53108.2024.10781772

Edgar Rangel, Santiago Gomez, Daniel Mantilla, Paul Camacho, Fabio Martinez

{"title":"A federated stroke segmentation to impact limited data institutions.","authors":"Edgar Rangel, Santiago Gomez, Daniel Mantilla, Paul Camacho, Fabio Martinez","doi":"10.1109/EMBC53108.2024.10781772","DOIUrl":"10.1109/EMBC53108.2024.10781772","url":null,"abstract":"Stroke, predominantly caused by blood vessel occlusion, is the second leading cause of death worldwide. DWI sequences facilitate characterization of brain-affected tissue, enabling lesion volume estimation, guiding treatment protocols, and aiding in prognosis approximation. However, radiological interpretations rely on neuroradiologist expertise, introducing subjectivity. Currently, computational solutions have allowed to support lesion characterization, but such efforts are dedicated to learn patterns from only one institution, lacking the variability to generalize geometrical lesion shape models. Moreover, some institutions lack training samples in annotated batches, which makes it difficult to achieve personalized solutions. This work introduces the first federated approach to stroke segmentation, leveraging data across institutions to impact institutions without data requirements. Models were trained on diverse institutional data and combined to obtain a robust solution for those without annotated datasets. Also, from such federated scheme was possible to measure the generalization capability of state-of-the-art architectures, evidencing new challenges in stroke care support.Clinical relevance- The validation of federated collaborative solutions to support stroke segmentations to transfer in clinical scenarios.","PeriodicalId":72237,"journal":{"name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","volume":"2024 ","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143558912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated Acoustic Analysis in Parkinson's Disease Using a Smartphone^. 使用智能手机对帕金森病进行自动声学分析。

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Pub Date : 2024-07-01 DOI: 10.1109/EMBC53108.2024.10782673

Gabriela T Acevedo T, Marc C Pappas, Jackson G Wolfe, Joshua Wong, Adolfo Ramirez-Zamora, Pamela R Zeilman, Diego L Guarin

{"title":"Automated Acoustic Analysis in Parkinson's Disease Using a Smartphone.","authors":"Gabriela T Acevedo T, Marc C Pappas, Jackson G Wolfe, Joshua Wong, Adolfo Ramirez-Zamora, Pamela R Zeilman, Diego L Guarin","doi":"10.1109/EMBC53108.2024.10782673","DOIUrl":"10.1109/EMBC53108.2024.10782673","url":null,"abstract":"Dysarthria is a common speech disorder in Parkinson's Disease (PD). The Dysarthria Analyzer software has emerged as a viable tool for automatic speech analysis in PD and quantification of dysarthria severity. However, most studies use the Dysarthria Analyzer with recordings obtained under tightly controlled conditions and high-quality microphones, and the utility of the Dysarthria Analyzer when used with recordings acquired under non-ideal conditions, such as in busy clinical settings, remains unexplored. This study investigates the Dysarthria Analyzer's performance in a setting more akin to a clinical environment using a smartphone. We obtained data from three groups, including healthy controls (HC), PD patients with their deep brain stimulation on (ON-DBS), and PD patients with their DBS off (OFF-DBS). We found a significant decrease in pitch variability and an increase in speech rate for the OFF-DBS group compared to the HC. Furthermore, most of the estimated values for the speech markers fall within the reported values in the literature. Our findings demonstrate that the Dysarthria Analyzer effectively extracts relevant speech markers even when used with recordings obtained under non-ideal conditions, emphasizing its potential for widespread clinical adoption.Clinical Relevance- Our findings demonstrate the potential of using smartphone recordings obtained in clinical environments for automatic objective speech analysis. These findings are relevant for developing a clinical tool that can be widely accessible and easily implemented during routine clinical visits of PD to improve the assessment of dysarthria in PD.","PeriodicalId":72237,"journal":{"name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","volume":"2024 ","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143559091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Facial Remote Photoplethysmography for Continuous Heart Rate Monitoring during Prolonged Cold Liquid Bolus Administration. 长时间冷液丸给药期间连续心率监测的面部远程光容积脉搏波描记术。

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Pub Date : 2024-07-01 DOI: 10.1109/EMBC53108.2024.10781709

Mahdi Momeni, Sophie Wuthe, Michaela Bitten Molmer, Emilie Lobner Svendsen, Mikkel Brabrand, Peter Biesenbach, Daniel Teichmann

{"title":"Facial Remote Photoplethysmography for Continuous Heart Rate Monitoring during Prolonged Cold Liquid Bolus Administration.","authors":"Mahdi Momeni, Sophie Wuthe, Michaela Bitten Molmer, Emilie Lobner Svendsen, Mikkel Brabrand, Peter Biesenbach, Daniel Teichmann","doi":"10.1109/EMBC53108.2024.10781709","DOIUrl":"10.1109/EMBC53108.2024.10781709","url":null,"abstract":"This study investigates non-contact heart rate (HR) monitoring through camera-based remote PPG during intravenous fluid bolus (FB) therapy. The experiment, at Odense University Hospital, Denmark, involved 4 volunteers and over 350 minutes of filming. We implemented a MATLAB-based HR extraction tool chain. The proposed method includes a two-stage process for dynamically determining regions of interest (ROIs), incorporating deep learning for facial landmarks detection and a subsequential consideration of subjects' facial dimensions. HR estimation uses chrominance-based (CHROM) and plane-orthogonal-to-skin (POS) PPG signal extraction methods, chosen for robustness against motion artifacts. Deviating from usual advice for other methods, omitting preprocessing minimizes signal processing still yielding a low error rate. The system achieved a mean error of fewer than 2 beats per minute (bpm), underscoring iPPG's alignment with ground truth. The results exemplify the feasibility of remote PPG monitoring in critical care and emergency settings.","PeriodicalId":72237,"journal":{"name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","volume":"2024 ","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143559522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Probing the Impact of Inner Retinal Network Changes on Subretinal Electrical Stimulation Responses. 探究内视网膜网络变化对视网膜下电击反应的影响

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Pub Date : 2024-07-01 DOI: 10.1109/EMBC53108.2024.10782307

Rongfeng Wang, Keith Ly, Jian Li, Michael L Italiano, Mohit N Shivdasani, David Tsai, Jia-Yi Zhang, Nigel H Lovell, Socrates Dokos, Tianruo Guo

{"title":"Probing the Impact of Inner Retinal Network Changes on Subretinal Electrical Stimulation Responses.","authors":"Rongfeng Wang, Keith Ly, Jian Li, Michael L Italiano, Mohit N Shivdasani, David Tsai, Jia-Yi Zhang, Nigel H Lovell, Socrates Dokos, Tianruo Guo","doi":"10.1109/EMBC53108.2024.10782307","DOIUrl":"10.1109/EMBC53108.2024.10782307","url":null,"abstract":"We investigated the influence of degenerated retinal networks on the efficacy of subretinal prosthetic devices in eliciting retinal neural responses. We present a computational model that incorporates intricate descriptions of retinal connectivity spanning neural layers, conductance-based cellular and synaptic parameters, and analytical formulas governing the electrical field. Our results suggest the possibility of selective modulation of functionally-distinct retinal pathways through subretinal stimulation, even in the absence of all photoreceptors. However, we observed a decreasing level of selectivity as inter-neuron synapse and gap junctions were progressively reduced. In addition, our model predicts a more pronounced influence of the integrity of the inner retinal network on electrically induced OFF compared to ON retinal ganglion cell activity. This phenomenon is ascribed to the unique inner retinal network properties of ON versus OFF pathways and changes in these properties upon photoreceptor loss. By precisely controlling the parametric values defining synaptic and gap junction connectivity in the inner retina, we can simulate the impact of different degrees of retinal degeneration on the retina's response to electrical stimulation. This model can assess the retinal network's response to remodeling events across different retinal degeneration stages, offering insights to guide the future development of retinal prosthetic devices and stimulation strategies. Such advancements hold promise for benefiting patients at various stages of retinal disease progression.","PeriodicalId":72237,"journal":{"name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","volume":"2024 ","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143559939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of Electrochemical Impedance Spectroscopy Data for Sputtered Iridium Oxide Electrodes. 溅射氧化铱电极的电化学阻抗谱数据分析。

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Pub Date : 2024-07-01 DOI: 10.1109/EMBC53108.2024.10781663

Henry M Lutz, Yupeng Wu, Cynthia C Eluagu, Stuart F Cogan, Kevin J Otto, Mark E Orazem

引用次数: 0

Cough Sound Based Deep Learning Models for Diagnosis of COVID-19 Using Statistical Features and Time-Frequency Spectrum. 基于统计特征和时频谱的咳嗽声深度学习新冠肺炎诊断模型

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Pub Date : 2024-07-01 DOI: 10.1109/EMBC53108.2024.10781593

Jina Kim, Jinseok Lee

引用次数: 0

Crucial events identify early stage of cardiac autonomic neuropathy progression from ECG signals. 关键事件识别早期心脏自主神经病变进展的心电图信号。

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Pub Date : 2024-07-01 DOI: 10.1109/EMBC53108.2024.10782197

Sara Nasrat, Korosh Mahmoodi, Ahsan Khandoker, Paolo Grigolini, Shiza Saleem, Herbert F Jelinek

{"title":"Crucial events identify early stage of cardiac autonomic neuropathy progression from ECG signals.","authors":"Sara Nasrat, Korosh Mahmoodi, Ahsan Khandoker, Paolo Grigolini, Shiza Saleem, Herbert F Jelinek","doi":"10.1109/EMBC53108.2024.10782197","DOIUrl":"10.1109/EMBC53108.2024.10782197","url":null,"abstract":"Cardiac autonomic neuropathy (CAN) is a condition characterized by neuropathic damage resulting in aberrant regulation of heart rate, and often manifests as changes in the ECG signals characterized by specific features of complexity, such as crucial events. This research explored the relationship between CAN progression and complexity measures involving crucial events, which can be determined using the modified diffusion entropy analysis (MDEA). MDEA measures the scaling index (0.5 < δ < 1) of the diffusion trajectory made of the crucial events (defined using the method of stripes). ECGs from the CAN dataset were recorded for 20 minutes, and CAN was classified based on established criteria into three groups: normal (n=40), early (n=42), and definite (n=7) stages. Fifteen-minute segments of the ECG time series were preprocessed and denoised and multiscale modified diffusion entropy analysis (MSMDEA) was applied to quantify the scaling index δ. Significant differences between disease progression were detected by comparing the MSMDEA scaling index (δ) across 20 temporal scaling factors using post hoc analysis (p<0.05), whereas the original unscaled signal yielded no significant detection of the disease progression. Crucial events detection indicates that the normal ECG signal is closer to the highest critical complexity (δ=1 or μ= 2), associated with a healthy cardiac autonomic function. Hence, crucial event analysis can be an adjunct to precision cardiology to assess cardiac health conditions, specifically CAN, and their progression from early to severe stages.","PeriodicalId":72237,"journal":{"name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","volume":"2024 ","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143559140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

EEG Channel Localization and Selection via Training with Noise Injection for BCI Applications. 脑机接口中基于噪声注入训练的脑电信号通道定位与选择。

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Pub Date : 2024-07-01 DOI: 10.1109/EMBC53108.2024.10782774

Chun-Ming Huang, Wei-Lin Lai, Chih-Chyau Yang, Yi-Jie Hsieh, Chien-Ming Wu, Chu-Hui Lee

{"title":"EEG Channel Localization and Selection via Training with Noise Injection for BCI Applications.","authors":"Chun-Ming Huang, Wei-Lin Lai, Chih-Chyau Yang, Yi-Jie Hsieh, Chien-Ming Wu, Chu-Hui Lee","doi":"10.1109/EMBC53108.2024.10782774","DOIUrl":"10.1109/EMBC53108.2024.10782774","url":null,"abstract":"Electroencephalography (EEG) is crucial for monitoring brain activity in neuroscience and clinical applications. However, the multitude of channels recorded by scalp electrodes poses challenges, including impractical usage and high model complexity. This paper addresses the challenges of high dimensionality in EEG data and introduces an innovative EEG channel selection algorithm, LSvT-NI, based on model training and noise injection, achieving substantial reductions in channels, model size, and complexity while maintaining high classification accuracy. Validated through experiments on EEGNet and the BCI Competition IV 2a dataset, the algorithm proves beneficial for practical and cost-efficient scenarios. Specifically, experiments on the BCI Competition IV 2a dataset demonstrate that LSvT-NI with white noise and pink noise at 5dB SNR achieves a remarkable 77.3% and 72.7% reduction in channels, along with 11.7% and 11% reductions in model size, and 86.9% and 71.8% in computation complexity.","PeriodicalId":72237,"journal":{"name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","volume":"2024 ","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143559336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

KAMLN: A Knowledge-aware Multi-label Network for Lung Cancer Complication Prediction. KAMLN：用于肺癌并发症预测的知识感知多标签网络。

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Pub Date : 2024-07-01 DOI: 10.1109/EMBC53108.2024.10782283

Danqing Hu, Bing Liu, Xiaofeng Zhu, Xudong Lu, Nan Wu

{"title":"KAMLN: A Knowledge-aware Multi-label Network for Lung Cancer Complication Prediction.","authors":"Danqing Hu, Bing Liu, Xiaofeng Zhu, Xudong Lu, Nan Wu","doi":"10.1109/EMBC53108.2024.10782283","DOIUrl":"10.1109/EMBC53108.2024.10782283","url":null,"abstract":"Surgical resection is now the only curative approach for early stage lung cancer patients. However, postoperative complications pose a significant threat to the health and life of patients. The current complication prediction methods usually ignore the potential causal relationships between different complications, which may limit their predictive performances. To exploit this knowledge, we propose a knowledge-aware multi-label network (KAMLN) for complication prediction. In this approach, we first construct a knowledge graph to describe the potential causal relationships between different complications. Then, we design a neural network based on this knowledge graph to learn the relationships between different complications to achieve better predictive performances. Experiments using 593 lung cancer patients' data show that the KAMLN achieves a micro-AUC value of 0.664±0.100, which is better than the baseline methods. The SHAP analysis indicates lymph node dissection has a significant impact on multiple complications. Based on the experimental results, the proposed KAMLN can effectively utilize prior knowledge between different complications to achieve more accurate and fine-grained complication prediction.","PeriodicalId":72237,"journal":{"name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","volume":"2024 ","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143559650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0